[00] · The AI practice of WE AS WEB

We build AI capability inside regulated companies.

We identify, build and transfer governed AI workflows — on your own cloud, with the evidence to prove they work. Real engagements, measured in production.

The review produces: 2–3 candidate workflows · a risk map · an honest build/no-build call

[ FIG. 01 — ONE GOVERNED CHANGE ]ISSUEREFINEAGENT BUILDCHECKSEVIDENCETESTS ✓RUNTIME ✓REVIEW ✓HUMAN GATESHIPPED · PROOFEVERY STEP LEAVES EVIDENCE · HIGH-RISK ACTIONS STAY HUMAN-APPROVED
Agent-assisted delivery throughput · File 02
70%
Engineering-org adoption · File 02
0→1
AI capability at a regulated mutual · File 01
LIVE
Legacy-code lineage on their estate · File 01

Measured in production deployments across two engagements. Each figure is sourced, scoped and caveated in its case file below — we publish the measurement context, not just the number.

The AI practice of WE AS WEB — 1,200+ engineers · 15 global locations · NATO-certified security practice · banking, pharma, utilities, aviation.

What we leave behind, every engagement: deployed tools · audit trails · runbooks · trained teams · your cloud, your IP.

[01] · The problem

Most enterprise AI is theatre. Pilots that never ship. Products dropped in a black box. Agents that “say it’s done.”

Not AI strategy decks. Not chatbot pilots. Embedded engineers shipping governed workflows on your infrastructure.

We work the other way around: embedded with your teams, on your infrastructure, proving value on real material before anything big gets built. Sensitive data never leaves your estate, and nothing we ship is a black box.

Every engagement leaves evidence — what ran, what it measured, what remains blocked — and leaves capability behind: your people able to run and grow what we built together.

[03] · How we work

A partnership, not a product drop.

The same repeatable, low-risk cycle behind every case file — proving value before committing to build, and leaving capability with your teams.

  1. Step 01

    Discover

    Map the manual, repetitive, legacy-bound workflows that cost your teams the most time.

  2. Step 02

    Workshop

    Surface candidate AI use cases with your people; prioritise by value and delivery risk.

  3. Step 03

    Prototype

    Prove value on real material before any large commitment is made.

  4. Step 04

    Co-build

    Engineer internal tools alongside your teams, on your own secure infrastructure.

  5. Step 05

    Deploy & iterate

    Ship into your environment, gather evidence, and grow the use-case backlog.

[05] · For your risk register

The questions your security and procurement teams will ask. Answered up front.

Data boundaries

Everything runs inside your estate. Sensitive data never leaves it — by architecture, not by policy document.

Deployment model

Built and shipped on your own secure cloud, inside the controls and governance your regulators already expect.

High-risk actions

Destructive commands, mutating operations and risky merges are confirmation-gated, policy-bound and auditable.

Identity & access

Service identities stay distinct from human users — validated at setup, rotated, and audited.

Evidence & audit

Delivery produces evidence packages and audit trails, not assertions. “Done” is verifiable.

Exit

Knowledge transfer is a deliverable. Your teams can run, extend and govern everything without us.

[06] · Who's behind this

The AI Lab is the AI practice of WE AS WEB — an enterprise engineering consultancy serving regulated sectors: banking, pharma, utilities and aviation. 1,200+ engineers across 15 global locations, a NATO-certified security practice, and full IP ownership for every client.

Practice lead

Robert Pop · Chief AI Officer

LinkedIn ↗

[07] · Principles

Your IP, entirely

Everything we build together is yours — code, tools, documentation, backlog. Full IP ownership for clients is a firm-wide guarantee, not a negotiation.

Evidence over assertion

“Done” means checks, runtime proof and auditable handoff — for the agents we deploy and for ourselves. If we can’t measure it, we don’t claim it.

Capability stays with you

Knowledge transfer is a deliverable. Your teams end the engagement able to run, extend and govern what we built together — no vendor lock-in.

[Contact] · The first conversation is free — and useful

Tell us where the manual work hurts. We'll tell you what AI can actually lift.

A working session with our engineers — not a sales deck. You leave with two or three candidate workflows, a risk map, and an honest build/no-build recommendation.

Your review is with Robert Pop, Chief AI Officer.

© 2026 WE AS WEB · weasweb.com

Client names withheld unless approved · Engagements are real