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Services

From clarity to capability.

Four ways we work with GCCs, training-led and outcome-measured. Most engagements start with a 30-minute clarity session.

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What we do

We make your centre AI-native, starting with your people.

AI Enablement & Training

Make your teams AI-fluent. Role-based programmes for leaders, engineers and functions that turn the playbook into practice. Skills that stick, not slideware.

AI Advisory

Diagnose where you stand, choose your move, frame a one-page roadmap HQ can read in five minutes. From pilots to production, not a PoC graveyard.

AI-Accelerated Delivery

Bring AI into your go-to-market. Enhance Product and timelines without breaking what works.

AI as a Product

Help your Centre build the AI the enterprise runs on. We build real products against real workflows, like turning a case file into a structured review, then help you make it yours.
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AI Enablement & Training

Make your teams AI-fluent, and keep them that way.

Most AI training is a certificate nobody uses. Ours is role-based and built on the playbook your leaders are reading. Skills that show up in the work, not the slides.

Leaders

Diagnose, decide and govern. Run the Diagnose → Move framework, set decision rights and kill criteria, and align HQ, so AI work moves instead of stalling.

Engineers

AI-assisted development with guardrails. Where AI raises throughput and where it threatens stability, and the quality gates that let you ship faster without breaking what works.

Functions

Finance, risk, HR and operations. AI in the actual workflow, not a demo disconnected from your systems and data, with outcomes a leader can put on a dashboard.

Formats that fit how a centre actually works.

Live workshops, multi-week cohorts, embedded coaching, and hands-on diagnostics from the playbook. We start with where your teams are, and leave the capability behind, not a dependency on us.

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AI Advisory

Most AI roadmaps don't survive contact with a steering committee. Ours are built to.

A roadmap that lists everything AI could do isn't a roadmap, it's a menu. We start from a diagnosis of where the centre actually stands, not where its tools do, and frame the one move a sponsor can approve in a single sitting.

Representative pattern

From a dozen scattered pilots to one funded roadmap

A typical centre we diagnose has AI running in six to twelve places at once: a chatbot pilot here, a coding-assistant trial there. None of it coordinated, none of it measured the same way, and no one able to say which of it is actually working.

We run the centre through Diagnose → Move: score where it actually sits on the maturity curve, retire the pilots that won't clear the bar, and frame the one initiative worth funding as a single page a sponsor can approve in the room.

Maturity diagnosis Portfolio triage One-page roadmap Sponsor-ready framing
What changes
Before A dozen unlinked pilots, no shared scorecard, no named owner
After One funded initiative, a named owner, a kill-date if it doesn't clear the bar
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AI-Accelerated Delivery

AI can double your throughput or double your incident rate. The difference is where you put the guardrails.

Most "AI coding assistant" rollouts hand every engineer a tool and hope. We find the specific stages of your delivery pipeline where AI raises throughput without raising risk, put quality gates around exactly those stages, and measure the difference.

Representative pattern

Where AI actually moved the needle, and where we kept it out

In a typical delivery audit, AI-assisted coding cuts first-draft time on routine, well-tested code paths substantially, and does close to nothing for the stages that actually determine ship dates: code review, integration testing, release coordination.

We map the pipeline stage by stage, place AI where the audit says it earns its keep, add the review gates that catch what it gets wrong, and leave the stages where a person's judgement is still the fastest path alone.

Pipeline audit Stage-by-stage rollout Quality gates Throughput measured, not assumed
Where it lands
Helps Boilerplate, test scaffolding, first-draft implementation
Holds the line Code review, release sign-off, production incidents
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AI as a Product

Most "AI as a product" offers stop at the roadmap. We build the real thing.

Before we tell a client to build AI into their own product, we build a working version against a real operational workflow first, not a slide. Here's what that looks like in practice.

Illustrative build

Turning a case file into a structured review, automatically

In regulated financial services and life sciences, every case, a claim, an adverse-event report, a credit or underwriting file, needs a structured review: the facts extracted, checked against policy and prior cases, and written up for a human reviewer to sign off. That review is usually manual, and it eats hours per case.

The product parses the case file, extracts the structured facts a review needs, drafts the narrative sections against the reviewer's own notes, and surfaces the most relevant policy clauses or prior cases automatically, live, from an uploaded file.

Document parsing Policy & precedent matching AI-drafted narrative Field-level provenance
Every field, tagged by source
Extracted data Structured facts, pulled from the case file itself
Reviewer input Notes and judgement, entered by the human reviewer
AI draft Narrative sections, drafted from the above
Policy match Matched policy clauses or prior cases, cited by source

Same product, two ways to run it. The constraint is what your data governance allows, not what the product can do.

Air-gapped

Runs entirely on your infrastructure

No data leaves the network. No external API calls, no cloud dependency, works fully offline if required. For environments where data residency isn't negotiable.

  • Zero external calls
  • Full data residency
  • Fit for classified or fully offline environments
Frontier model, via API

Fastest path to the highest capability ceiling

Uses the latest frontier models over API. Fastest to stand up, and improves automatically as the underlying models do. For teams whose governance allows cloud model access and want to move quickly.

  • Fastest time to value
  • Always on the model frontier
  • Fit for teams cleared for cloud AI

How we engage

Start small. Prove a number. Scale what works.

01 · Clarity session

A 30-minute read on where your centre stands and the one move to make next. No deck required.

02 · Audit & enablement

An SDLC / process audit to find the highest-ROI place AI belongs, then train the team that owns it.

03 · Pilot to production

One tightly-scoped proof, run as a hypothesis with a date, then a one-page roadmap HQ can approve.

An hour to answer. A year saved.

Book a 30-minute GCC AI clarity session. We'll tell you where your centre stands and the one move to make next.

Book a clarity session