3 platforms
AI Platforms
Products we build, run and sell — engineered for a specific enterprise outcome rather than a demo.
Artificial Intelligence
Enterprise AI, from the first decision to the hundredth use case
Three AI platforms, a full services line and the engineering bench underneath them. Whether you are choosing what to fund, unblocking a stalled pilot or industrialising a portfolio, the work starts in a different place — so start where you are.
Five groups, nineteen destinationsOne delivery spine
Most enterprises do not have an AI problem. They have a sequencing problem, a data problem and an accountability problem — and the AI programme is where all three become visible at once.
In short
What Adroitent's AI practice covers
Adroitent is an AI-native enterprise services partner. The AI practice spans three product platforms — DROITai for agentic operations, Devailey for software engineering and Talentalign for talent — and a services line covering strategy, governance, agentic systems, data foundations, engineering, testing and embedded delivery.
The distinguishing claim is not the model work. It is that the same organisation writes the roadmap, builds the data foundation, ships the system, proves it works and can hand the whole capability over to your team. Twenty years of enterprise delivery sit underneath all of it.
Explore the practice
Five groups. Nineteen ways in.
6 services
AI Services
Deciding what to build, what it is worth, who is accountable for it, and how the agents that run it stay inside their authority.
5 capabilities
ML & Data Science
The models and the estate they depend on. No AI programme outruns the quality of the data underneath it.
4 disciplines
Engineering & Delivery
The distance between a capable model and a working system — closed by engineers, evaluation harnesses and people who sit in your stand-ups.
Featured
AI Factory
One use case is a project. Twenty is an operating capability. The industrialised delivery model that makes the tenth use case cost a fraction of the first.
Adjacent
The stack underneath
AI rarely lands on its own. These are the practices most often engaged alongside it.
Where to start
Start where you actually are.
The board has approved AI and nobody has decided what to fund first.
AI Strategy
Every use case stalls on data nobody can find, trust or afford at production volume.
Data & AI Foundations
A prioritised use case has been stuck in pilot for two quarters and nobody can name the blocker.
Forward Deployed Engineers
Copilots are saving minutes. You need something that finishes the process.
Agentic AI
A regulator, an auditor or a customer has started asking who signed off on the model.
Governance & Risk
Something is live and you cannot prove it still works as well as it did at launch.
AI Testing
The tenth use case is costing what the first one did.
AI Factory
How we deliver
Outcome-led, AI-native delivery.
Assess & strategise
We start with your outcome and a measurable value case — not a rate card. Use cases are scored on value at stake, data readiness and regulatory exposure before anything is funded.
Architect
Secure, scalable solutions designed with governance built in from day one, on a provider-neutral architecture so model choice stays a routing decision rather than a strategic commitment.
Build & integrate
AI-native engineering and AgileSourcing teams deliver fast, with evaluation harnesses and audit trails written alongside the first sprint rather than after go-live.
Run & improve
We operate, measure and continuously improve against the metrics that matter — quality, latency and unit cost reported in the same review.
Why Adroitent
The grown-up in the room for enterprise AI.
Not a model lab, not a generic IT firm
We pair AI-native platforms with an enterprise services backbone, so the agility is real, measurable and delivered. Where a product accelerates your roadmap we will say so; where it does not, we will not sell it to you.
One partner across the whole path
The same organisation writes the roadmap, builds the data foundation, ships the system and proves it works. The handoffs that normally kill AI programmes do not exist here.
Regulated-industry delivery
Two decades inside healthcare, life sciences, financial services and the public sector, where evidence, traceability and validation were the job long before AI arrived.
Built to hand over
Documentation, runbooks and evaluation suites are deliverables. Where you want the capability in-house, teams transfer to you under a Build-Operate-Transfer arrangement.
20
years of enterprise delivery
500+
professionals globally
6,000+
person-years shipped
3
global delivery hubs
Frequently asked
Artificial Intelligence, answered.
What AI services does Adroitent offer?
Three product platforms — DROITai, Devailey and Talentalign — and a services line covering AI strategy and consulting, AI governance and risk management, agentic AI and orchestration, data and AI foundations, AI engineering, AI testing and governance, forward deployed engineers, and the AI Factory delivery model. Enterprise AI, generative AI, NLP, computer vision, predictive analytics and intelligent automation sit within that line.
Where should we start if we have not begun?
With AI Strategy & Consulting. A twelve-week engagement takes you from executive alignment to a funded, sequenced roadmap with the first use case in build. Where a use case backlog already exists, a compressed four-week sprint goes straight to build.
Do we have to buy the platforms to use the services?
No. The services are delivered on your stack and your choice of model provider. DROITai, Devailey and TalentAlign shorten the distance from strategy to working software where they fit, and are declined where they do not.
How does Adroitent handle responsible and compliant AI?
Governance is designed into the roadmap from week one rather than added at review. Controls are aligned to ISO/IEC 42001 and EU AI Act obligations through our AI Governance & Risk Management practice, and the evidence those controls demand is produced by our AI Testing & Governance practice.
How do you measure AI ROI?
Every engagement starts with a bottom-up value case: build cost, run cost, inference spend, expected margin or cycle-time impact, and the break-even month. Unit economics are tracked from the first sprint and reported alongside quality, so leadership can audit the gains rather than take them on trust.
Can you run what you build, or hand it over?
Either. Managed operations, or transfer to a client-owned team or dedicated GCC under a Build-Operate-Transfer arrangement, typically over 36 months with a zero-CAPEX operating model during the operate phase.
SEI CMMI Level 3 Appraised
ISO 9001:2015 Certified
ISO 27001:2022 Certified
ISO 42001:2023 Certified
Agility. Delivered.
Ready to make agility real?
Book a working session with our experts. We will map a specific, measurable path from AI platforms to production outcomes inside one quarter.