What this engagement includes
Whether internal helpdesks or customer-facing copilots, we connect models to vetted knowledge and APIs - not the open web by default.
We collaborate with security and legal on data handling, retention, and human-in-the-loop patterns where regulations apply.
How we deliver
We tailor and sequence these workstreams around your priorities, timeline, and internal constraints.
Use-case & policy
Scope, disallowed topics, PII handling, and success metrics.
Knowledge & tools
Connectors to docs, tickets, or APIs; tool calling with limits.
Evaluation
Test sets, regression checks, and dashboards for quality and drift.
Deployment
Hosting choices, secrets, monitoring, and operator documentation.
Our work
View our recent work below - each card links through to the live site.
We can walk through relevant case studies and references on a call - many of our clients ask for NDA-backed detail before we share specifics.
Typical flow
A reference sequence; we adapt depth and gates to your organisation.
- 01Pilot
Feasibility slice
Narrow scenario on a curated corpus to validate accuracy and UX.
- 02Harden
Safety & scale
Guardrails, rate limits, logging, and red-team style testing.
- 03Launch
Controlled rollout
Phased users, feedback capture, and support workflows.
- 04Improve
Continuous tuning
Retraining on new content, eval updates, and cost reviews.
| # | Stage | What happens |
|---|---|---|
| 01 | Pilot Feasibility slice | Narrow scenario on a curated corpus to validate accuracy and UX. |
| 02 | Harden Safety & scale | Guardrails, rate limits, logging, and red-team style testing. |
| 03 | Launch Controlled rollout | Phased users, feedback capture, and support workflows. |
| 04 | Improve Continuous tuning | Retraining on new content, eval updates, and cost reviews. |
Who we work with
Support teams, professional services, and product companies adding AI features - from SMEs piloting copilots to enterprises with model governance boards.
Infrastructure
We integrate with major model providers and can run in your cloud tenancy (AWS, Azure, GCP) with private networking as required.
Deliverables
Concrete outputs, documented and handed over with the build.
- Use-case definition and guardrails
- Connection to your knowledge base or APIs
- Evaluation and monitoring basics
- Operator documentation
Engagement model
Partnership patterns we document in the SOW or master agreement.
- -Proof of concept before full production
- -Collaboration with your security and legal teams as required
Commercial model
Cost reflects retrieval architecture, evaluation depth, risk controls, and model usage (often pass-through). We quote after discovery.
We start with a focused discovery (paid or unpaid, depending on complexity). You receive a written scope or SOW: milestones, acceptance tests, and a defined change process. NDAs and your procurement steps are routine.
Fixed scope
Documented requirements, milestones, and acceptance criteria. Delivery targets an agreed release or go-live.
When it applies
A narrow use case, curated corpus, and human-in-the-loop before broader rollout.
Phased programme
Successive increments with checkpoints, integrations, and change control as scope evolves.
When it applies
Production guardrails, logging, multiple tools or data domains, and security or legal review cycles.
Ongoing partnership
Retained monthly capacity for maintenance, incremental features, releases, and operational support.
When it applies
Monitoring, prompt and eval updates, and iteration as usage and content change.
Fees are quoted per engagement after discovery. Third-party cloud, licensing, and usage charges are usually billed to your accounts unless we agree otherwise.
Talk to our team