Embedded intelligence—inside real workflows.
We use AI where it materially improves throughput, quality, or decisions—then ship it as part of a production-grade system. Governed by design, observable in operation, and maintainable over time.
Client-hosted by default. Designed to fit your controls, data handling, and operating model.
Where it fits
We prioritise use-cases where value is measurable and control requirements are clear. This is the short list of patterns we reliably ship.
Workflow acceleration
Assistive drafting, summarisation, and decision support inside the tools teams already use.
- In-app copilots
- Faster review cycles
- Clearer handoffs
Extraction & classification
Documents, messages, routing, triage—structured outputs with traceability.
- Document pipelines
- Inbox triage
- Routing + tagging
Knowledge & retrieval
Find the right information fast, with access controls and source traceability.
- Grounded answers
- Search across systems
- Citations to sources
Ops & incident support
Assistive operations that reduce noise and speed up investigation without breaking process.
- Triage support
- Guided runbooks
- Operational visibility
How we deliver
A consistent path from discovery to governed operation—built to run on your infrastructure.
Engagement
Start small, prove value, then scale with controls.
Typical engagement starts with an assessment. Outputs and controls scale with risk tier.
Assess
Align on workflow, outcomes, and constraints. Define what “good” looks like before building.
- Workflow discovery
- Baseline KPIs
- Risk tier + controls
- Delivery plan
Build
Embed intelligence into real systems with acceptance criteria and operational readiness.
- Production integration
- Evaluation checks
- Observability + audit events
- Runbooks + rollout
Evolve
Iterate safely with governed updates and measured improvements over time.
- Controlled iteration
- Regression testing
- Quality/latency tuning
- Roadmap refinements
Governance
AI is treated like any production component: scoped, tested, observed, and versioned. Controls are right-sized to risk.
Default stance
Clear defaults. Right-sized controls. Client-hosted by default.
- Runs on client infrastructure
- Audit events and observability built in
- Evaluations and regression checks per use-case
- No training on client data by default
Risk-tiered controls
Controls scale with risk and impact.
Human oversight
Review and approvals where the workflow requires it.
Evaluation & regression
Checks in CI; versioned prompts/models; repeatable test sets.
Monitoring & auditability
Runtime behaviour observed, logged, and traceable.
Client-hosted by default
Designed to run on your infrastructure, aligned to your policies.
Data posture
No training on client data by default (opt-in only).
Ready to embed AI safely?
Start with an email. We’ll align on workflow, expected outcomes, and the control posture required to run this in your environment.