Scale AI across the enterprise — safely.
Pilots are easy; scaling AI across departments is not. We help leadership teams build the strategy, shared platform, governance and skills needed to turn isolated experiments into an enterprise capability.
Overview
Our Enterprise AI practice combines advisory and engineering. We assess AI maturity, define the target operating model and a portfolio of use cases, and stand up a shared AI platform — model access, data connectors, security, evaluation and cost management — that every team can build on.
We put governance in place early: acceptable-use policies, risk classification, model and vendor review, and alignment with emerging regulation and standards such as the EU AI Act and ISO/IEC 42001 — and we train your people so adoption sticks.
What you get with us.
AI strategy & roadmap
Maturity assessment, value cases and a sequenced portfolio of initiatives.
AI platform engineering
A secure, shared foundation for models, data, prompts, evaluation and cost control.
AI governance & risk
Policies, risk tiers, model inventories and controls aligned to regulation.
AI Center of Excellence
Operating model, roles and playbooks to scale delivery across business units.
FinOps for AI
Usage tracking, chargeback and optimization of model and GPU spend.
Adoption & training
Role-based enablement for executives, builders and everyday users.
A clear path, phase by phase.
A proven, phased approach. Timings are typical and depend on your scope, data and systems.
Assess maturity
Review strategy, data, platforms, skills, risk and current AI use across the business.
Strategy & portfolio
Agree ambition, value cases and a sequenced portfolio of initiatives.
Foundations
Stand up the shared AI platform and governance: policies, inventory, risk tiers, controls.
Center of Excellence
Operating model, roles, playbooks and training to scale delivery.
Scale & measure
Deliver use cases on the shared foundation and report value and risk regularly.
Ways to work with us on Enterprise AI.
AI Strategy & Roadmap
A clear, board-ready plan for where AI creates value.
- Maturity assessment
- Value cases & prioritisation
- Target operating model
- 12–24 month roadmap
AI Governance Programme
Responsible AI that satisfies risk, legal and security.
- Acceptable-use policy
- AI inventory & risk tiers
- Controls mapped to EU AI Act, ISO/IEC 42001, NIST AI RMF
- Review & approval workflow
AI Platform & CoE
A shared platform and team to scale AI safely.
- Model gateway & access
- Shared RAG & evaluation tooling
- FinOps for AI
- CoE playbooks & training
Where Enterprise AI delivers value.
Acceptable-use policy
Clear rules for staff use of AI tools.
AI inventory
Every AI system and vendor feature, with an owner.
Risk tiering
Proportionate controls by impact and data sensitivity.
Model gateway
One secure entry point to approved models.
FinOps for AI
Usage tracking, budgets and chargeback.
Training paths
Role-based learning for leaders, builders and users.
The stack we work with.
Vendor-neutral: we choose tools to fit your environment.
Frameworks & standards
AI platforms
Data platforms
Security & governance
Enterprise AI: common questions
Where should an enterprise AI programme start?
With a short maturity assessment, an interim acceptable-use policy and an inventory of current AI use — then a prioritised portfolio of use cases on a shared, governed platform.
Do we need an AI Center of Excellence?
Most organisations scaling AI beyond a few teams benefit from one: a small central team that provides the platform, standards, reusable components and advice, while business teams deliver use cases.
How do you align with AI regulation?
We map your controls to the frameworks that apply to you — such as the EU AI Act, ISO/IEC 42001 and the NIST AI RMF — and build them into the platform. This is not legal advice; we work alongside your counsel.
How do you measure the value of AI across the enterprise?
With baselines and a common scorecard per use case — productivity, quality, cycle time, revenue impact and run cost — reported regularly to leadership.
Enterprise AI in practice
A GenAI knowledge assistant for a consulting firm
How retrieval-augmented generation could let consultants find past proposals, methods and expertise in seconds.
Read moreA post-quantum cryptography roadmap for a bank
How a bank could inventory its cryptography, prioritise long-lived data and plan a phased migration to NIST post-quantum standards.
Read moreShipping AI use cases while building a firm-wide AI platform
How an FDE team could deliver the first AI use cases for a consulting firm while laying reusable platform foundations.
Read moreRelated articles
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A hype-free guide for business leaders: what today’s quantum computers can and can’t do, realistic timelines, and the three things worth doing now.
“Harvest Now, Decrypt Later”: The Quantum Threat That’s Already Here
Why encrypted data stolen today could be read by a future quantum computer, how to tell which of your data is at risk, and what to do about it.
FDE vs Consulting vs Staff Augmentation: Choosing the Right Delivery Model
How forward deployed engineering compares with traditional consulting, fixed-scope projects and staff augmentation — and how to choose for your situation.
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Learn moreReady to build what’s next?
Tell us about your project. Our consultants in Florida and Hyderabad will get back to you within one business day.