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Enterprise AI Services Empowered a Global Publishing Leader with an AI Agent

Leave a Comment / AI, DROIT /

Enterprise AI Agent for Publishing: 4X Growth | Adroitent Home/ Customer Stories/ Artificial Intelligence Customer Story · Publishing · Artificial Intelligence Enterprise AI services helped develop an AI Agent that improved the customer’s reader user base by 4X and their ROI by 3X. The customer is a global leading publishing company offering a range of professional print and digital publications, books, and textbooks in specialties such as health, tax, accounting, and legal. The group serves customers in over 100 countries catering to millions of users across the globe. Adroitent Case FilePublishingAzure OpenAI · LLM3 min read The inflection pointCustomer Business Need In today’s age with more importance to customer experience dominating all businesses, this publishing services customer also wanted to ease the access of its journals and articles to millions of readers and were looking around the possibilities of an AI solution. Ease and quicken the display from their existing collection of journals and articles — which runs in millions — to users based on every user search An AI agent to seamlessly access articles and journals by delivering topic-page generation, article summaries and results summaries Other much-needed publishing-industry in-demand use cases to enhance user experience Adroitent’s Enterprise AI services improved the customer’s reader user base by 4X and their ROI by 3X. The interventionSolution Delivered — an AI agent leveraging LLMs Adroitent partnered with the customer to develop an AI agent (engine) leveraging LLMs to quicken user access — with a topic-page generator, article summary generator, search results summary generator, and various other use cases to engage their readers. Topic-page AI Generator Automatically creates topic-focused pages, with related articles, related topics and topical ads for monetization Below the topic page, the article summary and source-articles list are also displayed Related Questions AI Generator For any topic or keyword searched, generates all related questions to quicken access to the required content instantly Addresses long-tail keywords and niche queries to attract a wider audience and drive organic traffic Article Summary AI Generator Instantly generates an article summary in a few lines for any article, lengthy or small Identifies key points and provides a shorter version while retaining its essential meaning Article Results Summary AI Generator For any keyword searched, generates all keyword-related results summaries Enables users to quickly pick the accurate article of their choice, with error-free extraction Solution highlights The Topic-page Generator Deep-dived into the customer’s database to discover the topic name and search the matched terms The AI agent picked the most relevant or trending subheadings for the topic page The top 10 subheadings were arranged in a sequence for a given or chosen topic keyword Article abstracts were used to create summaries, with quick validation and authentication of results Azure GPT-4.0PythonSQL ServerAWSLLMs By the numbers 4X reader user base 3X ROI Higher organic traffic Better reader engagement By the numbers 4X reader user base 3X ROI Higher organic traffic Better reader engagement The payoff4X readers, 3X ROI Faster Access to Information The AI agent generates concise summaries of complex topics, helping users quickly find and understand the information they need. Increases Organic Traffic By targeting long-tail keywords and niche queries, it attracts a broader audience and boosts organic search visibility. Improves Reader Engagement The AI agent enhances the overall user experience by delivering accessible, relevant, and personalized content. Delivers Actionable Insights It enables quick analysis of audience data to identify trending topics, helping publishers tailor content to user interests. Drives Content Ideation The topic-page generator suggests related and emerging themes, supporting the creation of fresh and relevant content. Enhances Learning Outcomes By offering structured and engaging content delivery, the AI agent enriches the learning experience for readers. Supports Data-Driven Strategy Performance tracking of AI-generated content provides insights into reader behavior, informing future content planning. Accelerates Topic Discovery The AI suggests related articles and topics based on user behavior, broadening content exposure and user exploration. Saves Time Summarizes long-form content into digestible snippets, enabling users to absorb key insights quickly. The stack behind itTools & technology Azure GPT-4.0PythonSQL ServerAWSLLMs This engagement was delivered as part of Adroitent’s Artificial Intelligence Services practice. Good to knowFrequently asked questions What is an AI agent? An AI agent is a software system that uses large language models and tools to autonomously carry out multi-step tasks — retrieving information, reasoning over it and generating outputs like summaries or pages — with little human intervention, adapting its actions to each request. How do large language models summarize articles? An LLM reads the full text, identifies the main ideas and relationships, and generates a shorter version in natural language. Extractive and abstractive techniques, prompting and retrieval help produce accurate, concise summaries while preserving meaning. What is a topic-page generator in digital publishing? A topic-page generator automatically assembles a focused page for a subject — pulling relevant articles, related topics, summaries and sometimes ads — using AI to select and sequence the most relevant content, helping publishers scale content and improve discovery. How does AI improve content discovery and SEO for publishers? AI surfaces relevant content by matching user intent, generating related questions and long-tail topic pages, and summarizing results. This improves internal discovery, targets niche queries, and increases organic search visibility and reader engagement. Which models power enterprise AI content applications? Enterprise content applications commonly pair hosted LLMs such as Azure OpenAI’s GPT-4 family with databases like SQL Server and cloud infrastructure such as AWS to retrieve, generate and serve content securely at scale. Put an AI agent on your content. Turn your library into instant, personalized reader experiences. Start a conversation Explore Artificial Intelligence Keep reading Related customer stories GCC solutions Scalable engagement model empowered a global consulting firm Read story Software engineering Driving digital excellence for a North American automotive leader Read story Software engineering Powering AI-driven travel experiences with DevOps and AWS Read story More from Adroitent: all customer stories · insights & blog · adroitent.ai

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Empowering Modernization of Healthcare Applications for a Leading Global Healthcare Technology Solutions Provider in the US

Modernization of Healthcare Applications for Cerner Healthcare Technology Provider

.Net, Software Engineering /

Modernization of Healthcare Applications for Cerner | Adroitent Home/ Customer Stories/ Software Engineering Customer Story · Software Engineering Modernization of Healthcare Applications for Cerner Healthcare Technology Provider Our Customer is a global leader in health information technology, dedicated to advancing healthcare delivery and improving the health of communities worldwide. Adroitent Case FileHealthcare ITHL7 · FHIR · .NET4 min read The inflection point Our Customer is a global leader in health information technology, dedicated to advancing healthcare delivery and improving the health of communities worldwide. The organization serves over 27,000 facilities globally, including more than 2,650 hospitals, 3,750 physician practices, 40 employer sites, and 1,600 retail pharmacies. By delivering integrated clinical and financial platforms, Cerner empowers healthcare providers to streamline operations and manage revenue cycles efficiently through innovative technology. As a massive global entity, Cerner faced the complex task of evolving its legacy systems to meet modern healthcare standards. Legacy systems transformation: A large portfolio of legacy Visual Basic applications required migration to a more scalable, efficient, and future-ready platform. Interoperability challenges: There were significant gaps in seamless data exchange across clinical, financial, and enterprise systems, necessitating the adoption of advanced integration capabilities. Application modernization needs: Critical applications, including inpatient pharmacy and registration modules within the Customer’s Millennium Suite, required a structured modernization approach to enhance functionality and performance. Reliability and performance assurance: Mission-critical production applications needed strengthened operational oversight to ensure high availability, stability, and optimal performance. A massive global entity, evolving its legacy systems to meet modern healthcare standards. The interventionSolution Adroitent played a pivotal role in the architecture, design, and integration of core solutions within the Cerner ecosystem. Adroitent maintained a long-standing, high-capacity partnership with the customer to ensure the continued stability and seamless operation of their mission-critical systems. Duration of involvement: 10+ Years. Team size: 45+ specialized professionals. Methodology: Agile. Design, and development Led architecture, design, development, quality certification, integration, and support for multiple core solutions within the Customer’s Healthcare ecosystem. Modernization approach Defined target architectures for mission-critical uplift programs and successfully migrated legacy Visual Basic applications to the .NET platform that improved the scalability, performance, and maintainability. Teams also played a key role in defining the target architecture for multiple mission-critical uplift programs such as Inpatient Pharmacy and Registration from their Healthcare Millennium Suite. Interoperability & API development Designed and implemented healthcare integrations using HL7 and FHIR standards. This included building FHIR-based RESTful APIs to support both modern and legacy hybrid integration scenarios. Quality engineering Developed custom quality certification and testing tools to strengthen automated quality control. Ensured system stabilization by conducting rigorous performance and memory testing and resolved root-cause issues through crash analysis to ensure system stability. Crash analysis and performance tuning Stabilized mission-critical applications through in-depth crash analysis, performance tuning, and root-cause resolution to ensure production reliability. Agile methodology Adopted Agile practices, delivering features through structured sprint cycles to ensure timely implementation, continuous feedback, and iterative improvement. The engagement A long-standing, high-capacity partnership Duration of involvement: 10+ Years Team size: 45+ specialized professionals Methodology: Agile Continued stability and seamless operation of mission-critical systems HL7 / DICOMFHIR R4SMART on FHIR.NET PlatformMirthRhapsodyOAuth 2.0 By the numbers Enhanced scalability Seamless interoperability Improved quality & reliability Clinician-centric results By the numbers Enhanced scalability Seamless interoperability Improved quality & reliability Clinician-centric results The payoffBusiness Outcomes Enhanced scalability Successful migration to .NET improved the performance and maintainability of the customer’s critical healthcare applications. Seamless interoperability Enabled unified data flow across labs, radiology, pharmacy, and external devices via standardized FHIR and HL7 interfaces. Improved quality & reliability Automated quality control and root-cause resolution led to stabilized production environments for mission-critical apps. Clinician-centric results Modernized UIs (PowerChart) and streamlined clinical workflows allowed physicians to focus on patient care rather than the underlying technology. The stack behind itTools & technology Secure network protocolsHL7/DICOM standardsFHIR R4CDAX12 (EDI)SMART on FHIR.NET PlatformOpen EngineMirthRhapsodyCloverleafOAuth 2.0TLS/SSLToken-based exchange This engagement was delivered as part of Adroitent’s Software Engineering Services practice. Good to knowFrequently asked questions What is healthcare application modernization? Healthcare application modernization is the process of upgrading legacy clinical and administrative software — re-platforming, re-architecting or rebuilding it — to improve scalability, security, interoperability and maintainability while preserving critical functionality and data. What are HL7 and FHIR, and why do they matter? HL7 and FHIR are healthcare data-exchange standards. HL7 defines messaging for clinical and administrative data; FHIR is a modern, API-friendly standard using RESTful web services. Together they let different health systems share patient data securely and consistently. Why migrate legacy Visual Basic applications to .NET? Migrating from legacy Visual Basic to .NET improves performance, security and maintainability, unlocks modern frameworks and cloud services, and reduces the risk and cost of running unsupported technology while preserving critical business logic. What is SMART on FHIR? SMART on FHIR is an open standard that lets third-party applications securely plug into electronic health record systems using FHIR APIs and OAuth 2.0 authorization, enabling interoperable, app-based clinical tools that run across different EHR platforms. How is interoperability achieved between clinical systems? Interoperability relies on shared standards (HL7, FHIR, DICOM, X12), integration engines such as Mirth, Rhapsody or Cloverleaf, and secure APIs. These translate and route data between labs, pharmacy, radiology and enterprise systems so information flows consistently. Modernize your mission-critical systems. Migrate legacy apps and connect them with standards-based interoperability. Start a conversation Explore Software Engineering Keep reading Related customer stories Software engineering Driving digital excellence for a North American automotive leader Read story Software engineering Powering AI-driven travel experiences with DevOps and AWS Read story Software engineering End-to-end support for a North American AutoTech leader Read story More from Adroitent: all customer stories · insights & blog · adroitent.ai

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Staffing Provider

Databricks-Based Predictive Analytics Improved Demand and Placement Forecasting Accuracy for a Leading US Staffing Provider

Leave a Comment / Databricks /

Databricks Predictive Analytics for a US Staffing Provider | Adroitent Home/ Customer Stories/ Databricks Customer Story · Databricks Forecasting the workforce: Databricks predictive analytics How Adroitent unified fragmented recruitment data on the Databricks Lakehouse for a leading US staffing provider — operationalizing ML across the staffing lifecycle to forecast demand, placements and attrition. Adroitent Case FileStaffing & WorkforceDatabricks · Delta Lake · MLflow3 min read The inflection pointData everywhere, foresight nowhere The customer is a leading US-based staffing and workforce solutions provider supporting multiple industries at scale, with a network of over 10,000 contractors across the healthcare, IT and financial services sectors. Fragmented systems left them reacting rather than anticipating. Fragmented data across ATS, CRM, VMS, payroll and other systems Manual forecasting of demand and candidate availability Inability to accurately predict placement success, employee attrition and revenue trends Limited reporting without predictive or forward-looking insights Slow Time-to-Fill (TTF) rates for niche roles Reporting tells you what happened. Prediction tells you what’s next. The interventionA Lakehouse for the staffing lifecycle Adroitent leveraged the Databricks platform to unify data, apply advanced analytics and operationalize machine learning models across the staffing lifecycle — empowering the customer with streaming and real-time analytics. Unified data platform Consolidated structured and semi-structured data from ATS, CRM, VMS and payroll Brought into Databricks using Delta Lake Medallion architecture Bronze: raw ingestion of candidate, job, placement and sales data Silver: cleaned, standardized and enriched datasets. Gold: curated, ML-ready feature tables Governance & security Unity Catalog deployed so sensitive PII stayed secure and compliant with US data privacy regulations Centralized governance with secure role-based access and audit-ready controls ML & predictive analytics Demand forecasting for open roles and future requisitions; placement success prediction Attrition and redeployment risk scoring; revenue and pipeline forecasting The game changer Models in production, insight in the dashboard ML model development and validation using Databricks MLflow Predictive insights delivered through dashboards for recruiters, sales leaders and C-level executives Accelerated data engineering through reusable frameworks and components Analytics-optimized Lakehouse architecture with ongoing managed services DatabricksDelta Live TablesUnity CatalogMLflowMedallion By the numbers Improved forecasting accuracy Faster decision-making Streamlined workforce planning Better placement outcomes By the numbers Improved forecasting accuracy Faster decision-making Streamlined workforce planning Better placement outcomes The payoffPredict, plan, place Improved forecasting accuracy Predictive models delivered materially better accuracy for demand and placement forecasting across the staffing lifecycle. Faster decision-making Actionable data insights, surfaced through dashboards, enabled recruiters and leaders to decide faster. Streamlined workforce planning Manual intervention was reduced, with planning driven by curated, ML-ready data rather than spreadsheets. Better placement outcomes Predictive demand insights improved candidate placement decisions and reduced time-to-fill on niche roles. Enhanced operational efficiency Efficiency improved organization-wide, supporting stronger global business growth. The stack behind itTools & technology Databricks PlatformDelta Live TablesDelta LakeUnity CatalogMLflowMedallion Architecture This engagement was delivered as part of Adroitent’s Databricks & AI Analytics practice. Good to knowFrequently asked questions What is a Databricks Lakehouse? A Lakehouse combines the low-cost, flexible storage of a data lake with the reliability, governance and performance of a data warehouse. On Databricks it lets BI, streaming and machine-learning workloads run on one governed copy of the data. What is the medallion architecture (Bronze, Silver, Gold)? It’s a layered pattern for refining data. Bronze holds raw ingested data; Silver holds cleaned, standardized and enriched datasets; Gold holds curated, business-ready tables and ML features — so quality improves at each stage and lineage stays clear. What is Unity Catalog used for? Unity Catalog provides centralized governance across a Databricks estate: role-based access control, auditing and data lineage. It’s how organizations keep sensitive data such as PII secure and compliant while still making data broadly usable. What is MLflow? MLflow is an open-source platform for managing the machine-learning lifecycle — tracking experiments, packaging models, and managing deployment and versioning. It’s what turns a promising model into something reliably running in production. How does predictive analytics improve workforce planning? By forecasting demand, candidate availability, placement success and attrition, teams can act ahead of need — pre-building talent pipelines, reducing time-to-fill, and planning revenue and capacity on evidence rather than intuition. Turn your data into foresight. Databricks Lakehouse, governance and production ML — end to end. Start a conversation Explore Databricks Keep reading Related customer stories Databricks Secure healthcare data access via a Databricks Lakehouse Read story GCC solutions Scalable engagement model empowered a global consulting firm Read story Software engineering Driving digital excellence for a North American automotive leader Read story More from Adroitent: all customer stories · insights & blog · adroitent.ai

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Secure and Compliant Healthcare Data Access Enabled through Databricks Lakehouse Implementation

Databricks /

Secure Healthcare Data Access via Databricks Lakehouse | Adroitent Home/ Customer Stories/ Databricks Customer Story · Databricks Governed by design: a HIPAA-aligned Lakehouse How Adroitent unified EHR, claims, lab and radiology data on a Databricks Lakehouse for a large healthcare provider network — delivering AI-ready analytics with HIPAA-aligned governance over sensitive PHI. Adroitent Case FileHealthcareDatabricks · Unity Catalog · HIPAA3 min read The inflection pointSilos, fragile pipelines, sensitive data The customer is a large healthcare provider network operating across multiple facilities, aiming to modernize its data and analytics environment to improve clinical, operational and financial insights — while maintaining strong controls over sensitive healthcare information. Data silos across EHR, claims, laboratory, radiology and other clinical and operational systems, limiting unified data access and insights Slow analytics and delayed reporting caused by legacy and fragile ETL pipelines, impacting timely decision-making Limited data governance and inconsistent access controls, creating challenges in securely managing sensitive PHI datasets Challenges enabling ML and AI use cases — readmission risk prediction, capacity forecasting, revenue leakage detection — due to unreliable and duplicated data sources In healthcare, insight is worthless without governance. The interventionA Lakehouse on the medallion pattern Adroitent implemented a Databricks Lakehouse architecture using the Medallion pattern (Bronze, Silver and Gold) to create a unified, governed and AI-ready data platform. Bronze — data ingestion Ingestion from EHR records, claims data, HL7/FHIR messages and lab data Raw data landed into Delta Live Tables to support data reliability Silver — transformation Standardization, deduplication, patient/provider entity resolution, ICD/CPT code normalization and data quality rules Pipeline orchestration via Databricks-native workflows with structured monitoring Gold — curated data Curated data for quality measures, revenue cycle dashboards, clinical ops and population health BI enablement and model-ready feature tables for ML orchestration Data reliability & performance Standardized on Delta Live Tables for ACID reliability, schema enforcement and historical versioning Improved trust and auditability across the platform The game changer Unity Catalog and HIPAA-aligned controls Centralized access control, auditing and lineage across workspaces and data assets Role-based and attribute-based access for PHI vs non-PHI datasets, with row/column-level controls where required Audit logging and lineage visibility for compliance and investigations HIPAA-aligned configuration approach based on Databricks HIPAA guidance Unity CatalogDelta Live TablesMLflowHL7 / FHIRHIPAA By the numbers Secure, compliant PHI access Faster data onboarding Accelerated reporting AI-ready data products By the numbers Secure, compliant PHI access Faster data onboarding Accelerated reporting AI-ready data products The payoffSecure, trusted, faster Secure, compliant access to sensitive data Effective governance through Unity Catalog delivered secure, compliant access to sensitive healthcare data, with audit-ready controls over PHI. Faster patient data onboarding Reusable data ingestion patterns accelerated the onboarding of new patient data sources. Improved patient reporting Streaming and real-time analytics improved the timeliness and quality of patient reports. Accelerated reporting & decisions Comprehensive dashboards accelerated reporting, enabling faster and more informed decision-making. Improved trust in analytics Standardized, curated datasets and governed data access raised confidence in the numbers. Accelerated ML initiatives Feature-ready data products accelerated the customer’s machine-learning initiatives. The stack behind itTools & technology Databricks PlatformDelta Live TablesUnity CatalogMLflowHL7 / FHIRMedallion Architecture This engagement was delivered as part of Adroitent’s Databricks & AI Analytics practice. Good to knowFrequently asked questions What is a healthcare data lakehouse? A healthcare lakehouse unifies clinical, claims, lab and operational data in one governed platform that supports both BI reporting and machine learning — replacing siloed warehouses and fragile pipelines with a single reliable source. How is HIPAA compliance handled in a cloud data platform? Through layered controls: encryption, network isolation, strict role-based and attribute-based access to PHI, comprehensive audit logging and lineage, and configuration aligned to the cloud provider’s HIPAA guidance — plus contractual safeguards such as a BAA. What are HL7 and FHIR? HL7 and FHIR are interoperability standards for exchanging health information between systems. FHIR is the modern, API-based standard, making it far easier to move clinical data reliably between EHRs, applications and analytics platforms. What are Delta Live Tables? Delta Live Tables is a Databricks framework for building reliable data pipelines declaratively. It brings ACID transactions, schema enforcement, data-quality expectations and historical versioning — so pipelines are auditable and trustworthy rather than fragile. What is PHI and why does governing it matter? PHI is Protected Health Information — any health data that can identify an individual. Governing it is a legal obligation under HIPAA and a matter of patient trust: access must be controlled, limited to those who need it, and fully auditable. Unify health data without compromising it. Governed Databricks Lakehouse platforms for regulated industries. Start a conversation Explore Databricks Keep reading Related customer stories Databricks Databricks predictive analytics for a US staffing provider Read story GCC solutions Scalable engagement model empowered a global consulting firm Read story Software engineering Driving digital excellence for a North American automotive leader Read story More from Adroitent: all customer stories · insights & blog · adroitent.ai

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Modernizing and Maintaining a Legacy Platform

Modernizing and Maintaining a Legacy Legal Management System

IT Support, Software Engineering /

Legacy LMS Modernization: IBM AS/400 & RPG | Adroitent Home/ Customer Stories/ Software Engineering Customer Story · Software Engineering Keeping a legacy LMS alive: AS/400, RPG & compliance How Adroitent took end-to-end ownership of maintaining and modernizing a decades-old legal management system across IBM AS/400 (RPG, LANSA), PowerBuilder and Java — while delivering a US 1099 tax-compliance overhaul. Adroitent Case FileLegal SoftwareAS/400 · RPG · Compliance3 min read The inflection pointA complex, multi-layered legacy estate The customer’s core application, LMS, spans multiple layers and versions — built on IBM AS/400 with RPG and LANSA for back-end processing and PowerBuilder and Java for the front end — and needed ongoing maintenance and modernization across LMS 4, LMS 5 and LMS Plus, plus a major US 1099 tax-reporting overhaul. Maintaining LMS 4, a legacy RPG/LANSA system Supporting feature enhancements across LMS 4, LMS 5 and LMS Plus Integrating compliance-driven changes within short timelines Managing multi-channel communication and ticket lifecycle via Zendesk & Jira Navigating VPN access and security issues while collaborating remotely Keep decades-old software stable, supported and compliant. The interventionEnd-to-end modernization & support Adroitent provided end-to-end ownership of modernization, support and enhancement activities across all LMS layers of the customer’s system. Feasibility analysis Full-lifecycle delivery with feasibility analysis for RPG/LANSA code changes New feature addition for LMS Plus Testing process Unit, System Integration and User Acceptance Testing with the product owner End-to-end testing of all peripheral applications with issue resolution at every stage 1099 tax-reporting overhaul Rebuilt tax-form logic and shifted output format from PDF to CSV Ensured compliance with the latest U.S. Government standards Agile practices Daily SCRUM ceremonies — sprint planning and backlog refinement Direct customer communication throughout delivery The game changer A 1099 tax-compliance overhaul in 2.5 months Rebuilt 1099 tax-form logic (MISC, NEC) end-to-end Shifted output format from PDF to CSV per US Government standards Delivered across LMS 4 and LMS 5 within 2.5 months Full ownership of the ticket lifecycle from Zendesk to resolution RPGLANSAPowerBuilderJavaZendeskJiraSelenium By the numbers Ensured business continuity Delivered 1099 compliance Streamlined ticket lifecycle Resolved VPN connectivity By the numbers Ensured business continuity Delivered 1099 compliance Streamlined ticket lifecycle Resolved VPN connectivity The payoffContinuity, compliance, trust Ensured business continuity Proactive maintenance kept the LMS platform stable and available. Delivered 1099 compliance Successfully delivered the 1099 compliance project within 2.5 months across LMS 4 and LMS 5. Improved collaboration Better collaboration and visibility using Jira and Confluence workflows. Streamlined ticket lifecycle Full ownership of the ticket lifecycle from Zendesk intake through to resolution. Secure remote support Resolved critical VPN access issues, ensuring secure and seamless remote support. Strengthened trust Consistent delivery and rapid response to production issues improved performance and operational efficiency. The stack behind itTools & technology RPGControl Language (CL)LANSAPowerBuilderJavaZendeskJiraConfluenceSelenium This engagement was delivered as part of Adroitent’s Software Engineering Services practice. Good to knowFrequently asked questions What is IBM AS/400 (IBM i)? IBM AS/400, now known as IBM i, is a reliable midrange server platform widely used for business applications. It runs languages like RPG and integrates the database, security and operating system into one system, and many enterprises still rely on it for stable, mission-critical workloads. What is legacy application maintenance and modernization? It is the ongoing work of keeping older software running — fixing issues, adding features and meeting compliance — while gradually upgrading its architecture, code or platform to improve performance, security and maintainability without disrupting the business. What are RPG and LANSA used for? RPG is a programming language for business applications on IBM i/AS-400, strong at data processing and reporting. LANSA is a low-code platform that extends and modernizes IBM i applications, enabling web and mobile front-ends over legacy back-ends. What changed in US 1099 tax reporting (MISC and NEC)? US 1099 forms report non-employee and miscellaneous income. The IRS reintroduced Form 1099-NEC and revised 1099-MISC, and agencies increasingly require structured electronic formats such as CSV instead of PDF, so software must update its form logic and output to stay compliant. Why not just replace a legacy system entirely? Full replacement is costly and risky because legacy systems hold years of critical business logic and data. Maintaining and incrementally modernizing preserves that value, ensures continuity and compliance, and spreads risk — often more pragmatic than a big-bang rewrite. Keep your legacy systems running and compliant. Proactive maintenance and modernization for mission-critical legacy software. Start a conversation Explore Software Engineering Keep reading Related customer stories Software engineering Driving digital excellence for a North American automotive leader Read story Software engineering Powering AI-driven travel experiences with DevOps and AWS Read story Software engineering Modernization of healthcare applications in the US Read story More from Adroitent: all customer stories · insights & blog · adroitent.ai

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End-to-End Support Services for a North American AutoTech Leader

IT Support, Software Engineering /

Modernizing and Maintaining a Legacy Platform (IBM AS/400) Legal Management System (LMS) for Enhancing Platform’s Operational Efficiency About the Customer Our customer is a tech-forward automotive platform provider serving many dealers and consumers across North America. Their software suite powers trade-in valuations, payment calculators, digital brochures, videos for sales and service, and much more. With over 7,000 dealer websites utilizing its capabilities, the company is leading the auto tech industry with advanced platforms. Customer Challenges The customer’s platform had issues and problems that spanned across configuration, data/feeds, and code, often around product boundaries and hosting environments. Some of the pain points were: Fragmented handoffs between support triage and engineering Configuration issues and code issues Handling issues of core services enabled by the customer to their dealers   Solution Delivered Adroitent was chosen as the preferred partner by the customer to enable end-to-end support for their applications. Adroitent teams deep dived into the customer’s system and enabled an integrated support model that aligned with the customer’s business goals. This ensured single-threaded ownership from incident intake to fix and release for configuration, code issues, etc. Procedure adopted for Issue Resolution Dealers reporting issues: Dealers initially coordinated with the customer’s support team at the first level to report their issue. A preliminary investigation was performed by the customer’s support team for issue resolution by diagnosing and identifying the issue. Issue handling: Minor issues were handled by the support team; unresolved issues were logged in Jira, which were handled by Adroitent’s team. Issue type identification: Issues were categorized into Config issues, code issues, or data issues. A Jira ticket was created and assigned to the developer. The developers resolved the issue which was further tested and finally deployed to the production environment. Technology Leveraged Issue & Project Management: Jira Frontend & SDK: TypeScript/JavaScript, Angular Analytics: GA4, Shift Analytics Source Control: GitHub Deployments: Heroku (multi-environment) Cloud & Hosting: AWS Business Outcomes By partnering with Adroitent, the customer achieved significant improvements in issue resolution efficiency. Our team ensured that complex challenges were addressed swiftly and effectively, minimizing disruptions across their extensive dealer network. This strategic support model enabled the customer to concentrate on product innovation and core business operations while maintaining reliable, uninterrupted services for their dealers. We enabled a seamless dealer experience driven by faster triage, proactive resolution, and enhanced service continuity.

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What is the Role of AI Agents in Recruitment in 2025?

Leave a Comment / Articles /

The Role of AI Agents in Recruitment in 2025 | Adroitent Home/ Blog/ The role of AI agents in recruitment in 2025 Insights · Artificial Intelligence What is the role of AI agents in recruitment In 2026, AI agents are playing a pivotal role in reshaping recruitment strategies for enterprises and multinationals, making the process faster, data-driven, and candidate-centric. Adroitent InsightsArtificial IntelligenceTalent Acquisition5 min read Key takeaways AI agents move recruitment from time-consuming manual screening to a proactive, strategic, efficient process. They bring cognitive capabilities — understanding context, recognizing patterns, and adapting matching algorithms as they learn. Benefits include faster time-to-hire, higher quality of hire, bias reduction, and predictive workforce planning. Talentalign is Adroitent’s job-description-driven AI agent, built by the AI Center of Excellence (AICoE). IntroductionAI agents are reshaping recruitment In 2025, Artificial Intelligence (AI) agents are playing a pivotal role in reshaping recruitment strategies for enterprises and multinationals, making the process faster, data-driven, and candidate-centric. These AI agents are bound to transform every facet of the recruitment life cycle, moving it from a time-consuming process to a proactive, strategic, and efficient process. The challengesMajor recruitment challenges faced by recruiters in 2025 Traditional recruiters relied more on manual screening, smaller networks, and older versions of Applicant Tracking Systems (ATS). Some of their common challenges include: Sifting resumes: Recruiters struggle manually sifting through thousands of applications for specific skill sets that becomes a time-consuming task. Greater competition: While drawing from global talent pools, recruiters face intense competition from others for the same pool of skilled professionals. Timely hiring: Businesses need faster hiring for project-specific roles by recruiters. Any delay in hiring impacts project delivery, innovation cycles, and ultimately brand value. Candidate experience: Due to delayed feedback from recruiters, the candidates might shift to other sources. Today’s candidates expect faster feedback and seamless experience from first touchpoint to offer acceptance. Thus, traditional Human Resource Information Systems (HRIS) and Applicant Tracking Systems (ATS) alone are no longer sufficient. This is where AI agents step in as the strategic orchestrators of talent. In 2025, enterprises and businesses require scalable, intelligent, and automated AI agents to keep pace with their dynamic global expansion demands. The shiftWhat is the role of AI agents in recruitment? AI agents in recruitment represent a fundamental move from traditional keyword-driven candidate search methods to AI agents that bring cognitive capabilities. These agent capabilities mirror human intelligence while operating at speed, accuracy, and scale. These AI systems understand context, recognize patterns, and make intelligent decisions analyzing complex, and multi-dimensional criteria to shortlist profiles. Unlike rule-based old systems, AI agents adapt their candidate matching algorithms based on real-time outcomes, becoming more accurate and effective as they learn over time to shortlist profiles. This learning capability is particularly valuable for enterprises, multinationals, and GCCs, which often need to fill highly specialized roles with shorter timelines. AI agents are not replacing recruiters; they are empowering them to be more strategic. In practiceThe transformative role of AI agents in recruitment In 2025, AI agents will be deeply embedded across the entire recruitment lifecycle, performing a myriad of intelligent tasks such as: Semantic Job Description Analysis: AI agents go beyond keyword matching, semantically analyze job descriptions, understand the context, experience levels, etc. and shortlist the right candidates with high matching scores. Intelligent Profile Matching: AI agents scan internal and external talent pools (ATS, LinkedIn, GitHub, niche forums, etc.) to identify candidates whose profiles contextually align with job requirements. Automated Scoring & Ranking: AI agents automatically score and rank candidates based on their overall role fit, significantly reducing the manual effort of screening. Automated Summaries & Justifications: AI agents generate natural language summaries explaining why a candidate is a strong fit. Chatbots & Virtual Assistants: Intelligent chatbots handle initial candidate queries 24/7, personalizing communication and guiding candidates through the application process. Interview Scheduling: AI agents automate scheduling across multiple time zones, sending reminders and coordinating with hiring managers, reducing no-shows. AI-driven Assessments: For technical roles, AI agents administer and evaluate coding and technical assessments, providing objective performance data. Behavioral & Cognitive Analysis: AI agents analyze recorded video interviews for communication patterns and cognitive abilities, without human biases. Real-time Market Insights: AI agents monitor talent markets to provide strategic insights for workforce planning and compensation strategies. Predictive Analytics: AI agents predict future talent needs based on project pipelines, technology trends, and attrition patterns. The benefitsWhat are the benefits of AI-driven recruitment for enterprises? The implementation of AI agents in recruitment represents a paradigm shift from reactive to proactive talent acquisition powered with cognitive thinking capabilities. AI agents excel at what traditional recruitment tools struggle with — understanding the nuanced requirements of complex technical roles and identifying the right candidates for the right job role. Some of the benefits include: Accelerates time-to-hire Scalability and higher quality of hire Enhances recruiter productivity with more focus on candidate experience Bias reduction Real-time market intelligence and market insights Predictive analytics for strategic workforce planning Cost efficiency CaveatsData privacy and compliance aspects to ponder While AI agents bring immense value, enterprises need to evaluate the below aspects: Data privacy & compliance: Proper understanding and complying with GDPR, local data laws, and other policies should be taken into account. Bias in algorithms: Continuous monitoring is required to prevent hidden biases in AI models. Change management: Recruiters need training to work alongside AI agents effectively. Candidate perception: Striking the right balance between automation and human touch is the need of the hour for businesses in 2025. ConclusionThe future outlook The role of AI agents in recruitment for enterprises and businesses in 2025 is transformative. They are not just tools but strategic enablers that allow businesses to scale, innovate, and attract world-class talent in highly competitive global markets. By combining the efficiency of AI with the empathy of human recruiters, enterprises can create a future-ready ecosystem that empowers both growth and innovation. These agents are not replacing recruiters; they are empowering recruiters to be more strategic, efficient, and ultimately, more successful in securing the talent

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Meet Talentalign: The Future of Smart Hiring

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Meet Talentalign: The Future of Smart Hiring | Adroitent Home/ Blog/ Meet Talentalign: the future of smart hiring Insights · Artificial Intelligence Meet Talentalign, the future of smart hiring Tired of sifting through resumes with no right match? Talentalign is Adroitent’s job-description-driven AI agent that matches profiles to roles and shortlists the right candidates in minutes, not weeks. Adroitent InsightsArtificial IntelligenceTalent Acquisition6 min read Talentalign matches resumes to job descriptions and shortlists the right candidates in minutes. Key takeaways Talentalign is Adroitent’s job-description-driven AI recruitment agent, powered by the DROIT Platform and developed using LLMs. It analyzes job descriptions, matches and shortlists top candidates in minutes, and delivers closely-ranked profiles with a greater than 80% matching score. It reduces bias through objective, data-driven analysis and integrates with your ATS — supporting SAP SuccessFactors, Workday, and other third-party platforms. Business benefits include significant time savings, superior quality of hire, higher recruiter productivity, and cost efficiency. IntroductionThe 2025 talent landscape In today’s hyper-competitive talent landscape, the stakes for hiring are higher than ever. Enterprises need to fill critical roles quickly with the best candidates. Yet, most recruiters continue to spend countless hours sifting through thousands of resumes, only to find a frustratingly low percentage of relevant candidate matches. If your recruitment team is exhausted from this relentless search for the right fit, embracing AI is the best approach to find the right fit faster. The challengeThe recruiter’s struggle: why traditional sourcing methods fall short Recruiters today face a wide set of challenges that slow down hiring, increase costs, and sometimes cause them to miss the right candidate. Recruiters often receive numerous resumes per role, but only a small percentage are a good match. Some of the recruiter’s struggles include: Manual screening: Recruiters spend many hours manually screening profiles, which is a time-consuming process that increases the likelihood of overlooking the right fit. Manual reviews lead to poor applicant-to-interview conversion rates. High volume with low relevance: Hundreds of resumes flood in for every job opening, but many aren’t a good fit for the role, which makes recruiters’ tasks harder. Human bias: Conventional screening by recruiters not only slows the process but can also lead to missed talent, unconscious bias, and inconsistent hiring decisions. Fake profiles: Today, fake profiles are a significant drain on recruiters, requiring higher scrutiny of such profiles, which demands more time. Feedback delays: Sometimes, due to lack of proper feedback from recruiters, can leave applicants disengaged. This leads to inconsistent candidate experience due to delayed screening and feedback loops. Traditional Applicant Tracking Systems (ATS) and sourcing methods often fall short in today’s fast-paced hiring landscape due to a lack of speed and profile match precision. These traditional systems offer only keyword-based filtering and lack context-driven matching of candidate search. That’s where Talentalign steps in. The productWhat is Talentalign? Powered by Adroitent’s DROIT Platform, Talentalign is an AI agent that empowers recruiters to instantly match resumes to Job Descriptions. Talentalign is an innovative AI agent for recruitment developed using LLMs to revolutionize the way you hire. Talentalign is a unique job description-driven AI agent for GCC leaders, HR Directors, HR Leaders, Recruiters, Talent specialists, etc. This AI agent improves recruiters’ productivity with faster closures and high quality hires. What does Talentalign do? Adroitent’s Talentalign is engineered to empower your recruiters by leveraging AI algorithms. This agent profoundly understands the job description to get the right fit. It is a smart recruitment agent that understands what makes a candidate truly right for a role. Analyzes job descriptions, identifies and matches profiles to job roles Shortlists top candidates in minutes Speeds up screening with intelligent scoring Generates a candidate summary for their role fitment Enables data-driven hiring decisions within minutes, not days Enhances recruiter productivity In practiceTalentalign: empowering recruiters with the right fit in minutes, not weeks 1. AI-Powered Resume Screening Advanced algorithms: Talentalign AI agent uses advanced algorithms to analyze resumes, extracting detailed skills, experiences, and role fit instantly. Its unique algorithms match candidates with job descriptions contextually and not just keywords. Evaluates Job Description: This AI agent evaluates job descriptions, understands the role requirements, evaluates candidates contextually, and delivers closely-ranked profiles with a greater than 80% matching score. This agent identifies critical requirements and interprets business context to shortlist candidates. Analyzes resumes: Talentalign analyzes hundreds of resumes in minutes, extracting and ranking the most relevant candidates. Instant shortlisting: Identifies top candidates instantly, so your recruiters focus only on the best matches, enabling effective candidate interactions. Hiring teams receive instant shortlisted candidates along with their matching skill set scores. Continuous learning: Each hire improves Talentalign accuracy through a continuous learning loop, refining future recommendations as the agent continues to learn from data. 2. Reduces bias Objective analysis: This AI agent removes personal bias by relying on data-driven algorithms that assess skills and experience. Diversity, Equity, and Inclusion: Promotes a more diverse workforce by ensuring all candidates receive fair and equal consideration. 3. Speed, Efficiency, and Better Experience Quick feedback: Candidates receive personalized compatibility assessments, keeping them engaged and boosting your employer’s reputation. Actionable analytics: Get instant reports on candidate pools, hiring trends, and recruitment ROI to optimize strategies. 4. Scalable and Integrative This AI agent scales with you and can process numerous applications much faster with more speed and accuracy. This AI agent seamlessly integrates with your applicant tracking system (ATS), supports SAP SuccessFactors, Workday, and other third-party platforms. The right fit in minutes, not weeks. The benefitsBusiness benefits with Talentalign Significant time savings: Eliminates hours of manual resume sifting, while recruiters can spend less time searching and more time engaging with candidates. It reduces screening time for recruiters significantly with automated profile evaluation and frees up their time. Talentalign ensures positions are filled faster with quicker candidate shortlisting. This empowers organizations to capitalize on opportunities and reduces time-to-hire with faster closures. Superior quality of hire: By understanding the true essence of a role, Talentalign ensures a more precise match with a job description-driven shortlisting. Enhances recruiter productivity: Talentalign transforms recruiters

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Sitecore Helix Architecture: A Layered and Modular Development Standard

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Sitecore Helix Architecture | Modular Development Guide Home/ Blog/ Sitecore Helix architecture: a layered and modular development standard Insights · Software Engineering Sitecore Helix Architecture: a layered and modular development standard Sitecore Helix is a set of official design principles and conventions that organizes a Sitecore solution into Foundation, Feature, and Project layers — the gold standard for building maintainable, scalable enterprise implementations. Adroitent InsightsSoftware EngineeringSitecore CMS12 min read Sitecore Helix organizes a solution into Foundation, Feature, and Project layers for maintainability at enterprise scale. Key takeaways Sitecore Helix is a set of official design principles and conventions from Sitecore for building modular, maintainable, and scalable solutions on the Sitecore Experience Platform. It organizes a solution into three layers — Foundation, Feature, and Project — and is characterized by three elements: Layers, Coupling, and Cohesion. The Golden Rule of Helix: dependencies flow downwards only (Project → Feature → Foundation), ensuring clarity and reduced complexity. Benefits include reusability, low complexity, low maintenance, easy troubleshooting, improved productivity, and significant cost reduction. IntroductionWhat is Sitecore Helix architecture? In today’s rapidly evolving digital landscape, enterprises require robust, scalable, and easily maintainable content management systems (CMS). Enterprises, in their quest to deliver seamless digital experiences, need CMS platforms that are powerful, scalable, and easy to manage. This is where Sitecore Helix Architecture steps in, providing a robust framework that transforms how large organizations build, manage, and evolve their Sitecore solutions. Sitecore Helix is a set of design principles and development guidelines introduced by Sitecore to promote modular, maintainable, and scalable solutions on the Sitecore Experience Platform. Sitecore Helix Architecture has emerged as the gold standard for building enterprise-grade Sitecore implementations that can adapt to complex business requirements while maintaining code quality and developer productivity. Sitecore Helix is a collection of recommended practices and conventions for the solution architecture of Sitecore product implementations. Moreover, Helix is a set of official guidelines and recommended practices from Sitecore, wherein each component is independent, reusable, and designed for a specific purpose, empowering enterprises and businesses to construct complex digital ecosystems with unprecedented agility. Key facetsKey facets of Sitecore Helix architecture Sitecore Helix architecture is modular and is based on breaking down the solution into effective logical modules. Each module is focused on a single responsibility, making the system easier to understand, develop, test, and extend. The main purpose of Helix is to provide developers with efficient guidelines to help them build future-proof solutions that are easy to maintain. The Sitecore Helix is characterized by three elements: Layers Coupling Cohesion 1. Layers In Sitecore Helix architecture, a layer refers to a logical grouping of code and functionality based on its responsibility and role within the solution. Layers are used to enforce modular development, separation of concerns, and maintainability. Layers further consist of three main divisions: Foundation Layer: This layer holds the low-level, cross-cutting concerns such as logging, data access, or indexing that are shared across multiple features. This is the bedrock layer that contains low-level and cross-cutting concerns that are fundamental to the entire solution. Let us think about some of the shared services, base templates, common utility functions, and integrations with core enterprise systems (CRM, ERP, etc.) wherein any change here significantly impacts many other layers for reusability and is named as Foundation layer. Feature Layer: This layer contains the reusable business features like navigation, search, news, etc; wherein each feature is self-contained and independent. Each module in this layer represents a specific, self-contained business feature such as a news listing, product catalog, search functionality, or a promotions module. Specifically, these Feature modules should be independent of each other, promoting isolated development and deployment. Project Layer: This layer contains project-specific code and configuration, such as page types and layouts. It orchestrates features but doesn’t contain business logic. This layer brings everything together, more like the composition layer, where you can assemble the features and foundation elements to create specific websites, microsites, or digital channels. It provides the overall context, layouts, and site-specific configurations, typically containing minimal custom code. 2. Coupling It refers to how modules relate to each other referring to the dependencies between the modules. Typically, low coupling indicates modules are independent and changes in one do not affect others. 3. Cohesion As the name suggests means ‘sticks’ something together, referring to how closely related are the functions within a module. While Sitecore Helix promotes low coupling between the modules, it also encourages high cohesion within each module. High cohesion refers to one module taking up single responsibility. The golden ruleWhat is the Golden Rule of Helix? Dependencies flow downwards. Project modules can depend on Feature and Foundation modules. Feature modules can depend only on Foundation modules. Foundation modules can only depend on other Foundation modules. This strict hierarchy ensures clarity and reduces complexity. For enterprises, Helix is not just a recommendation — it should be a strategic imperative. The benefitsBenefits of Sitecore Helix architecture for enterprises and businesses There are profound benefits for enterprises and businesses with Sitecore Helix architecture. Some of them have been given below: Development-based Accelerated development cycles: With clear boundaries and reduced interdependencies, the development teams can work in parallel on different features. This fosters true agile development, ensuring faster iterations and quicker time-to-market for new functionalities, and in enabling better digital experiences. Enhanced code reusability: Helix architecture’s flexibility to design features as independent modules ensures, they can be easily reused across multiple websites, brands, or even future projects. This saves significant development time and cost, promoting consistency across your digital properties with enhanced code reusability. Improved code quality and testing with modular code: Helix enforces architectural patterns that naturally lead to better code quality. The clear separation of concerns makes code more readable, testable, and maintainable. This is particularly valuable for enterprises that need to maintain solutions over many years. Modular code is easier to test, both in isolation and as part of the overall system. The modular nature of Helix makes it easier to implement comprehensive testing strategies. Each feature

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Empowered A Leading Automobile Manufacturer in Japan

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Empowered A Leading Automobile Manufacturer in Japan with Global Application Support Services and Improved Operational Efficiency About the Customer The customer is a leading automobile manufacturer in Japan and is named as the sixth largest car manufacturer in the world. The company sells its vehicles under various brands, with in-house performance tuning products and has been producing vehicles for over 80 years. The company has been delivering a diverse portfolio of vehicles under multiple brands including high-performance models. Their global operations span across Europe, North America, and Asia, with distributed application environments tailored for each regional hub. The Business Challenge With multiple operational environments across Japan (East & West), Northeast Asia, and Europe, the customer faced increasing complexity in maintaining and supporting its Azure-based infrastructure. Their application environments required: Consistent troubleshooting and patching Timely certificate and password updates Disk cleanup and regular VM health monitoring Database backup and fine-tuning Migration to newer versions of Azure services in response to Microsoft’s sun setting of legacy features Thus, the customer needed a reliable application support services provider for managing their region-wide proactive issue resolution, maintaining stable infrastructure without service disruption, and avoiding application-level HTTP errors like 502/503, which were critical for their business continuity. Adroitent’s Solution – Seamless Global Application Support Services Adroitent designed a comprehensive application support strategy, tailored to the customer’s multi-region Azure environment. The solution included: Core Support Activities Quarterly patching and troubleshooting Annual certificate renewals Ad-hoc disk cleanups and space optimization Regular VM password updates and Active Directory (AD) account generation Azure version migration across environments to align with Microsoft’s upgrade cycles Full coverage for over 100 Virtual Machines, including: Database servers (Primary & Secondary) Content, Batch, APA, CPAA servers, and AD Servers Automated processes & monitoring with PowerShell scripting for: Disk cleanup Database patching Legacy-to-modern Azure migrations VM Scale up and Scale down – need based Log collection and management Capping memory for reducing the usage of the software Rollbacks and VM backups for fail-safe updates Integration with JP1 Monitoring tool for real-time alerts and event logs Access via VPM login and centralized maintenance server for secure remote troubleshooting Monitoring alerts via mails for quicker resolutions Technologies Leveraged Microsoft Azure Cloud Platform – Scalable hosting and infrastructure PowerShell Scripts – Automation for disk cleanup, patching, migrations JP1 Monitoring Tool – Real-time performance and health alerts of CPU utilization React.js – For dynamic UI experiences Business Outcomes Zero downtime: Reduced the errors of 502 or 503 errors post implementation ensuring continuous availability of business-critical applications. Security & compliance: Passwords and certificates were updated on time across all VMs and servers, ensuring proper strengthening of security. Successful Azure migration: Smooth transition to updated Azure versions was carried out across global environments, ahead of Microsoft’s deprecation (Sun setting) deadlines. Streamlined monitoring: Issues were detected and resolved quickly via automated alerts with effective patching mechanisms. Operational efficiency: Improved operational efficiency with reduced downtime with seamless and stable application availability across regions of customer’s operations.

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