Reference builds, not client name-drops.
We don't publish client logos. Instead, here are illustrative implementations that show exactly how we'd architect and ship systems like these.
Healthcare AI Assistant
A grounded patient-facing assistant that answers questions over an approved medical knowledge base with citations and strict refusal logic.
The challenge
Patients need reliable answers, but a hallucinating assistant in healthcare is worse than none. The system had to ground every response in approved sources, cite them, and refuse confidently when out of scope.
Our approach
- 01Built a RAG pipeline over a curated, versioned medical knowledge base with hybrid retrieval and re-ranking.
- 02Layered grounding checks so any answer without sufficient source support is suppressed or escalated.
- 03Added PII redaction and a strict refusal policy for diagnostic or emergency requests.
- 04Instrumented faithfulness and relevance evaluation to catch quality regressions before release.
Architecture
Autonomous SOC Agent
A multi-agent system that enriches, correlates, and triages security alerts autonomously, escalating only what genuinely needs a human.
The challenge
Security teams drown in alerts, most of them noise. The goal was an agent that could investigate alerts like an analyst — gathering context, correlating signals, and deciding what matters — without acting recklessly.
Our approach
- 01Designed a supervisor agent routing to specialised enrichment, correlation, and triage agents.
- 02Gave agents typed tools for threat intel, log queries, and asset lookups with strict allow-lists.
- 03Required a critic agent to verify conclusions before any escalation or containment recommendation.
- 04Kept every consequential action behind a human approval gate with full trajectory replay.
Architecture
Enterprise Knowledge Assistant
A company-wide assistant that answers questions across scattered internal documentation with permission-aware retrieval and citations.
The challenge
Institutional knowledge was spread across wikis, drives, and ticketing systems. Employees wasted hours searching, and any assistant had to respect document-level access permissions.
Our approach
- 01Built connectors to ingest and continuously sync documents from multiple internal sources.
- 02Implemented permission-aware retrieval so users only ever see what they're authorised to access.
- 03Tuned chunking and hybrid retrieval to the corpus for high-precision grounding.
- 04Shipped a feedback loop where thumbs-down responses feed the evaluation set.
Architecture
Customer Support Automation
An automation pipeline that classifies, drafts, and resolves routine support tickets while routing complex cases to humans.
The challenge
A support team was overwhelmed by repetitive tickets. They needed automation that could resolve the routine 60% while never mishandling a sensitive or complex case.
Our approach
- 01Classified incoming tickets by intent and confidence before any action.
- 02Auto-drafted and, above a confidence threshold, auto-sent grounded responses from the help centre.
- 03Routed low-confidence and sensitive tickets to humans with a pre-drafted reply.
- 04Tracked deflection and CSAT to ensure automation never traded quality for volume.
Architecture
Clinical Documentation Agent
An ambient agent that drafts structured clinical notes from clinician–patient dialogue, with clinician review before anything is saved.
The challenge
Clinicians spend hours on documentation. The system had to draft accurate structured notes from conversation while keeping the clinician firmly in control of the final record.
Our approach
- 01Transcribed encounters and extracted structured clinical elements with a specialised pipeline.
- 02Generated SOAP-formatted draft notes grounded strictly in the transcript.
- 03Required clinician review and edit before any note could be committed.
- 04Measured edit distance and acceptance to continuously improve draft quality.
Architecture
Let's build something that ships.
Bring us a problem. We'll tell you honestly whether AI is the right tool — and exactly how we'd build it.