Software Engineering

From Legacy to Lakehouse: The New Data Strategy with Databricks | Adroitent Home/ Blog/ From legacy to Lakehouse Blog · Data & AI From legacy to Lakehouse: the new data strategy for modern enterprises Failed AI initiatives, spiralling infrastructure costs, and data engineers firefighting pipelines instead of building business value all trace back to the same root cause. Here is why the Lakehouse — and Databricks — has become the answer. Adroitent InsightsData & AIDatabricks6 min read Key takeaways Legacy data warehouses were built for reporting on structured data — not for the velocity, volume, and variety that define enterprise data today. Data teams lose up to 70% of their time to brittle pipelines, data reconciliation, and ageing infrastructure. The Databricks Lakehouse unifies storage, governance, processing, and AI through Delta Lake, Unity Catalog, Apache Spark, MLflow, and AutoML. Enterprises that migrate report 30–40% infrastructure cost savings and AI moving from proof-of-concept to production in weeks rather than months. A phased migration — audit, govern, prioritize, run parallel, decommission — is what separates programmes that land from programmes that stall. There is a quiet crisis unfolding inside enterprise data teams worldwide, and its consequences show up everywhere: failed AI initiatives, spiralling infrastructure costs, and data engineers firefighting pipelines instead of building business value. The cause is a legacy data architecture that can no longer support the way modern enterprises need to compete. The solution is the Lakehouse — and Databricks is the platform leading that transformation. As enterprises accelerate their digital transformation journeys, they need a modern data strategy that can unify analytics, data engineering, governance, and AI on a single platform. This is where the Lakehouse architecture, powered by Databricks, is changing the way organizations manage and derive value from their data. The problemThe challenges of legacy data architectures Traditional data warehouses were built primarily for reporting and business intelligence workloads. They create real friction when organizations attempt to scale analytics and AI initiatives. Common challenges include: Data silos spread across multiple systems High infrastructure and licensing costs Complex ETL pipelines that increase latency Limited support for unstructured and semi-structured data Slow access to business insights Difficulty scaling AI and ML workloads As enterprises generate data from cloud applications, IoT devices, customer interactions, and digital platforms, maintaining separate systems for storage, analytics, and AI becomes increasingly inefficient and costly. The diagnosisWhy legacy data infrastructure fails modern enterprises Traditional data warehouses delivered reliable reporting on structured, predictable data, but they were never designed for the velocity and volume that defines enterprise data in 2026. Data teams spend up to 70% of their time managing brittle pipelines, reconciling inconsistent data, and maintaining ageing infrastructure. AI and ML initiatives stall because the governed, accessible data they require is perpetually out of reach. Business leaders wait days for insights that should arrive in minutes. The problem is the architecture — and that is precisely what Databricks solves. By the numbers 70% of data-team time spent maintaining pipelines and infrastructure instead of creating value 30–40% average infrastructure cost reduction after consolidating onto a Lakehouse Hours not days or weeks — the new cycle time for analytics that previously ran in batch Weeks not months — proof-of-concept to production AI on governed, unified data The platformWhat makes Databricks the right platform for Lakehouse migration Databricks’ Lakehouse architecture addresses those challenges by storing data in open object stores like S3, ADLS, or GCS while adding ACID transactions, metadata management, and indexing for reliable analytics. Built on open-source projects including Apache Spark, Delta Lake, and MLflow, the Lakehouse keeps data free from proprietary formats and closed ecosystems. Databricks is not just another cloud data platform. It is the most trusted and most adopted enterprise data and AI platform available today. Databricks introduced the Lakehouse to combine the best capabilities of data lakes and data warehouses into a unified platform. The Databricks Data Intelligence Platform lets organizations store, process, govern, analyze, and apply AI to a single source of truth. Four components do the work: Delta Lake An open-source storage layer that brings ACID transactions, schema enforcement, and versioned data management to cloud storage. Enterprises get the reliability and query performance of a warehouse combined with the flexibility and cost efficiency of a lake, without compromising either. On one platform, teams run SQL analytics, build and deploy machine learning models, process real-time streaming data, and develop generative AI applications — no duplication, no silos. Unity Catalog Enterprise-grade governance built directly into the platform, centralizing data discovery, access control, lineage tracking, and compliance enforcement across every workload and cloud. For enterprises operating across multiple geographies and regulatory environments, compliance becomes an automatic, platform-enforced standard. Apache Spark Processes data at a scale and speed legacy systems cannot approach — accelerating ETL pipelines, reducing processing times from hours to minutes, and enabling real-time analytics. MLflow and AutoML Close the loop between data and AI, giving teams a unified environment to experiment, train, track, and deploy models against the same governed, high-quality data that powers analytics. The result is AI that is faster to build, easier to trust, and simpler to scale. Unlike traditional architectures that require multiple technologies and constant data movement between systems, Databricks provides one integrated environment supporting: Data engineering Data warehousing Real-time analytics Machine learning Generative AI Data governance The roadmapHow to begin your legacy-to-Lakehouse migration A successful Databricks migration is not a single event. It is a structured journey that balances speed with stability. The most effective enterprise migrations follow a phased approach: Audit first. Run a comprehensive data audit to catalog existing sources, pipelines, and quality gaps. Govern before you migrate. Establish a governance framework using Unity Catalog ahead of moving data. Prioritize high-value workloads. Migrate these early to demonstrate ROI quickly. Run in parallel. Keep legacy and Lakehouse environments live together to validate outputs. Decommission progressively. Retire legacy systems as confidence in the new platform grows. The difference between migrations that succeed and migrations that stall is expertise. Certified Databricks engineers with hands-on mastery of

One Embedded Team, Four Live Applications | Adroitent Home/ Customer Stories/ Software Engineering Customer Story · IT Services · Software Engineering One Embedded Team, Four Live Applications, Zero Quality Drift The customer is a leading IT services provider delivering ongoing development and enhancement support to its own portfolio of end customers, spanning travel, logistics and e-commerce. Every project carried its own technology stack, its own release cadence and its own business priorities — and all of them ran at the same time. Adroitent Case FileIT ServicesAgile Delivery · Multi-Application Support4 min read The inflection pointFour codebases, four cadences, one delivery problem The customer needed reliable technical support that would let them seamlessly support their own end customers. That customer base was highly diverse, with multiple concurrent projects running in parallel. Each came with its own technology stack, release cadence and distinct business priorities, requiring a flexible, responsive and deeply collaborative support approach. 01Travel Travel-tracking platform Undergoing a complete rebuild from a legacy codebase carrying performance bottlenecks, response issues and long-term maintainability problems. 02Travel Configurable flight-notification system Designed to deliver highly accurate, rules-driven messaging based on dynamic conditions and individual customer requirements. 03Logistics Dock appointment & scheduling platform Enabling seamless coordination of pick-ups, deliveries and end-to-end supply chain visibility across multiple partners. 04E-commerce High-traffic e-commerce and CMS platform Powering online liquor retail operations in Australia, requiring scalability, reliability and a consistent user experience under load. The customer needed a delivery partner who could act as a true extension of their team — embedded, accountable and capable of driving agile execution across a diverse, evolving application landscape. They required consistent quality across multiple codebases, the flexibility to adapt to changing requirements, and the ability to meet externally committed go-live timelines for ongoing modernization work. The hard part was never building any one application. It was holding four of them to the same standard, at the same time. The interventionOne embedded team, one repeatable framework Adroitent placed a single embedded team across the portfolio and gave it a delivery framework that did not change from application to application. The cadence flexed; the standards did not. An agile model built for shifting priorities Adopted a hybrid Scrum model with daily backlog grooming, so priorities could move between applications without stalling the team Applied three-point estimation at task level, alongside enforced coding standards Ran UAT across every application in the portfolio, not only the ones nearing release Time-boxed modernization, delivered in parallel Each project was scoped end to end, from planning through release, on an agile overlapping-phase timeline Those timelines were built to hold against the customer’s own externally committed go-live dates Governance the customer could see Daily stand-ups kept work synchronized before issues ever reached the customer Weekly management reviews tracked risk, with status visible in JIRA in real time rather than in a periodic report The result was a consistent, auditable view of progress across every work stream The game changer QA discipline that scaled across four codebases Every check-in required a QA test request — no exceptions by application Every change set went through code review before it moved forward Continuous regression testing stayed in place throughout, not just before releases This consistency let one team support four live, unrelated applications without quality drifting on any of them QA per check-inMandatory code reviewContinuous regressionPortfolio-wide UAT By the numbers 4 Live applications supported 1 Embedded delivery team 3 Industries served in parallel 0 Quality drift across codebases The payoffFrom portfolio strain to a reusable model Optimized portfolio delivery Four live applications across different domains were supported by a single embedded team, reducing the need for separate pods, separate governance and separate QA. Improved quality and velocity Concurrent delivery was sustained across all four applications without compromising quality or delivery speed. Reduced maintenance burden Reliability issues and accumulated technical debt were addressed, creating a scalable and sustainable foundation across the portfolio. Enabled platform modernization Modernization was delivered on time, reducing migration risk and protecting business continuity. Created a reusable delivery model A repeatable framework covering grooming, code review, regression testing and JIRA visibility now extends to future engagements. The stack behind itTools & technology Build .NETMVC patternSQL Delivery & governance TFS — code repositoryJIRA — requirements & acceptance criteriaConfluence — user stories & project docsVisio — design This engagement was delivered as part of Adroitent’s Software Engineering Services practice. Good to knowFrequently asked questions What is an embedded delivery team, and how does it differ from staff augmentation? An embedded delivery team operates as an extension of the customer’s own organization, owning outcomes across planning, build, QA and release rather than filling individual seats. Staff augmentation supplies people who work under the customer’s process and management. An embedded team brings its own delivery framework, governance and accountability, which is what makes it viable to support several unrelated applications at once. How do you maintain consistent quality across multiple concurrent applications? Consistency comes from making quality gates mandatory rather than release-dependent. Every check-in raises a QA test request, every change set passes code review before it moves forward, and regression testing runs continuously instead of only ahead of a release. Because the same gates apply to every codebase, quality does not depend on which application a developer happened to be working in that week. What is a hybrid Scrum model with daily backlog grooming? A hybrid Scrum model keeps Scrum’s sprint cadence, ceremonies and estimation while borrowing continuous-flow practices for work that cannot wait for the next sprint boundary. Grooming the backlog daily rather than once per sprint lets priorities shift between applications without stalling a team, which matters when several customers set their own release cadences. What is three-point estimation and why apply it at task level? Three-point estimation captures an optimistic, most-likely and pessimistic figure for each item and derives a weighted estimate from the three. Applying it at task level rather than story level exposes uncertainty early and produces forecasts reliable enough to commit to externally, which is essential when go-live

Always-On Automotive Platform & GA4 Analytics | Adroitent Home/ Customer Stories/ Software Engineering Customer Story · Automotive · Software Engineering Driving Digital Excellence for a North American Automotive Leader with Always-On Reliability & Data Intelligence A leading North American automotive technology innovator, the customer empowers car dealers with an integrated digital platform that enhances the entire buyer journey — from trade-in valuations and payment calculations to service management and digital retail experiences. The customer’s ecosystem connects dealers and consumers through intelligent, high-performance applications. Adroitent Case FileAutomotiveGA4 · Support & Maintenance3 min read The inflection pointA pivotal inflection point As platform adoption surged, the customer faced a pivotal inflection point: Increasing need for always-on platform stability across dealer networks Rising expectations for faster issue resolution and zero disruption Demand for continuous product evolution to stay competitive Limited visibility into user behavior and engagement insights Urgent need to implement Google Analytics 4 (GA4) for next-gen analytics The challenge was clear: move from reactive support to a predictive, insight-driven digital operations model. The interventionProactive engineering meets data-driven intelligence Adroitent partnered with the customer to deliver a next-generation support and maintenance ecosystem, combining proactive engineering practices with advanced analytics through GA4. Always-On, proactive support model Shifted from reactive fixes to predictive issue resolution Continuous monitoring ensured risks were identified and resolved before impacting dealers or users Continuous innovation engine Delivered incremental enhancements and feature upgrades aligned to evolving business needs Ensured the platform stayed future-ready and competitive Quality built into every release Rigorous unit and functional testing frameworks Guaranteed zero regression and consistent product performance Agile at scale Adopted a Kanban-driven Scrum model Enabled continuous delivery, real-time visibility, and predictable releases The game changer GA4-Powered Data Intelligence Custom GA4 dashboards for real-time traffic and user behavior insights Seamless cross-platform integration ensuring unified analytics Deep visibility into user journeys, engagement patterns, and drop-offs Empowered teams to make faster, and smarter data-backed decisions GA4Custom dashboardsCross-platformReal-time insights By the numbers Improved platform stability Accelerated issue resolution Higher engagement & conversions Data-driven decisions By the numbers Improved platform stability Accelerated issue resolution Higher engagement & conversions Data-driven decisions The payoffFrom stability to strategic advantage Significantly improved platform stability Proactive monitoring and testing led to a sharp reduction in production defects, ensuring seamless dealer and consumer experiences. Accelerated issue resolution Structured support model enabled faster turnaround times, minimizing downtime and improving responsiveness. Higher engagement & conversions GA4-driven insights optimized user journeys, resulting in increased interaction across dealer tools and platforms. True data-driven decision making Teams gained clear, actionable visibility into user behavior, enabling continuous optimization and smarter business strategies. Stronger business outcomes Improved performance, enhanced engagement, and optimized operations, collectively contributed to a measurable improvement in the customer’s bottom line. The stack behind itTools & technology JIRAConfluenceGitHubDockerKafkaPHPLaravelRuby on RailsMongoDBPostgreSQLHerokuPower BI / Tableau This engagement was delivered as part of Adroitent’s Software Engineering Services practice. Good to knowFrequently asked questions What is proactive application support, and how does it differ from reactive support? Proactive support continuously monitors systems to detect and resolve issues before they affect users, using telemetry, alerting and preventive maintenance. Reactive support only responds after something breaks. Proactive models improve uptime, reduce disruption and lower the long-term cost of incidents. What is Google Analytics 4 (GA4) and why did businesses migrate to it? GA4 is Google’s analytics platform built on an event-based data model that tracks users across web and app. Google retired the older Universal Analytics in 2023, so businesses moved to GA4 to keep measuring traffic, engagement and conversions with privacy-focused, cross-platform reporting. How does data analytics improve digital product decisions? Analytics shows how users actually behave — which journeys convert, where they drop off, and which features drive engagement. Teams use these insights to prioritize the roadmap, remove friction, personalize experiences and measure impact, replacing guesswork with evidence. What does ‘always-on’ reliability mean for a digital platform? Always-on reliability means a platform stays available and performant continuously, even during updates or traffic spikes. It is achieved through proactive monitoring, redundancy, automated testing and rapid incident response, so users see minimal downtime and consistent quality. Make your platform always-on. Turn reliability into intelligence — and intelligence into outcomes. Start a conversation Explore Software Engineering Keep reading Related customer stories Software engineering Powering AI-driven travel experiences with DevOps and AWS Read story Software engineering Modernization of healthcare applications in the US 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

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

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.

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.

IT Support for Dental Brand in USA | Improved Efficiency Home/ Customer Stories/ Software Engineering Customer Story · Software Engineering Seamless IT Support Services for a Leading Dental Brand in the USA Seamless IT support services for a leading dental brand in the USA helped enhance operational efficiency and improve global operations. Adroitent Case FileIT SupportITIL · ServiceNow3 min read The inflection pointBusiness Challenge The customer is a global family of over 30 trusted dental brands, united by a shared purpose: to partner with professionals to improve lives. Headquartered in California, USA, the company helps its partners deliver the best possible patient care through industry-leading products, solutions, and technology. The customer’s comprehensive portfolio includes dental implants and treatment options, orthodontics, and digital imaging technologies, covering an estimated 90% of dentists’ clinical needs for diagnosing, treating, and preventing dental conditions as well as improving the human smile. As the customer expanded its global operations in different regions, there was a growing need to provide robust IT support services to both its internal teams and its customers. Manage IT support for a diverse range of hardware and software assets, including laptops, mobile devices, and internal applications. Implement standardized processes for role-based access management across various departments and applications. Provide timely support for over 400 applications, including SAP, Oracle, Microsoft, ERP, SaaS, Business Intelligence tools, ServiceNow, etc. across varied departments. Establish a knowledge base to assist internal teams and customers in resolving common IT issues on the go at a faster pace with minimal downtime. Over 400 applications, a global footprint — and a growing need for robust IT support. The interventionSolution Delivered Adroitent partnered with the customer to provide comprehensive IT support services for the customer’s global operations. A dedicated team, comprising engineers and senior engineers, was established to manage daily operations and support requests. Hardware & software support Providing hardware and software support for laptops, mobile devices, and internal applications. Role-based access management Managing role-based access by creating accounts and providing access based on user roles, following ITIL best practices. Application support Handling support requests for various applications, ensuring timely resolution and minimal downtime. Knowledge base development Developing and maintaining a knowledge base with over 200 articles to assist users in troubleshooting common issues. Tools / Technologies Leveraged A standardized, ITIL-aligned support stack ServiceNow for IT service management and ticketing. SAP and Oracle for enterprise resource planning. Microsoft applications and tools. Various ERP, SaaS, and Business Intelligence applications. Internal customer applications: providing support for proprietary internal platforms. ServiceNowSAPOracleMicrosoftITIL By the numbers Scalable support Minimized downtime 120-150 tickets/day 200-article knowledge base By the numbers Scalable support Minimized downtime 120-150 tickets/day 200-article knowledge base The payoffBusiness Outcomes Scalable support The structured IT support approach ensured the customer to efficiently scale its IT support operations to accommodate growth and regional requirements, which enhanced service quality across its global footprint. Minimized downtime Teams established a first point of contact (POC) for IT support that ensured prompt response to outages and support requests. Faster incident resolution and proactive monitoring led to reduced system outages and productivity improvement. Quicker ticket resolution Teams resolved around 120-150 tickets per day, with 200 tickets in progress, and efficiently handled support requests quickly. Streamlined IT support operations Standardized IT support workflows and automation reduced manual errors and inefficiencies during ticket resolutions. Knowledge base Support team developed a comprehensive knowledge base with 200 articles that significantly reduced the time to resolve common issues and empowered users with effective resolution options. Enhanced operational efficiency By standardizing processes through ITIL, the customer achieved greater efficiency in IT service delivery, leading to faster resolution times and improved resource utilization across its global operations. The stack behind itTools & technology ServiceNowSAPOracleMicrosoftERPSaaSBusiness IntelligenceITIL This engagement was delivered as part of Adroitent’s Software Engineering Services practice. Good to knowFrequently asked questions What are managed IT support services? Managed IT support services provide ongoing management of an organization’s hardware, software, applications and user support — typically through a dedicated team and service desk — so issues are resolved quickly, access is governed, and internal teams stay productive. What is ITIL and why does it matter for IT support? ITIL (Information Technology Infrastructure Library) is a widely adopted framework of best practices for IT service management. Following ITIL standardizes processes like incident, access and knowledge management, leading to faster resolution and more consistent service quality. What is role-based access management? Role-based access management grants users permissions based on their job role rather than individually. It streamlines account provisioning, strengthens security and compliance, and reduces errors by ensuring people can access only the systems their role requires. How does a knowledge base improve IT support? A knowledge base is a curated library of articles and solutions to common issues. It lets users and support staff resolve recurring problems faster, reduces ticket volume, and preserves institutional knowledge so support scales without proportionally growing headcount. What is a first point of contact (POC) in IT support? A first point of contact is the single, defined entry for all support requests. Establishing one ensures every outage or request is logged and triaged promptly, speeds incident response, and gives users a consistent, reliable path to resolution. Scale IT support across your global operations. ITIL-aligned service desk, role-based access and knowledge bases that cut downtime. 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