What we build
What we build
We identify which workflows are worth automating, then build the AI systems to run them — with security, evaluation, observability, and ownership built in from the start.
Not sure which of these fits your situation? Start the Workflow Discovery → — a 12-question diagnostic that identifies which workflows are ready to automate and where your architecture needs work before you commit to a build.
Six capabilities. Start with an audit if you're not sure what to build — or go straight to the service that matches where you are.
Your team runs the same workflow every day — manually. That's recoverable time, but only if the automation is built on a process that's actually ready to carry it.
Process Automation
- LLM extraction with confidence scoring — manual transcription eliminated, not just reduced
- Human review routing for edge cases — people handle exceptions, the system handles the rest
- End-to-end audit trail — the process is compliance-ready from day one
Whether you're building your first automated workflow or fixing one already failing in production — agent systems need defined boundaries, approval gates, and a plan for when they fail.
Agent Orchestration Systems
- Risk-tiered approval gates — agents handle routine decisions, humans approve what matters
- Deterministic failure handling — no task degrades silently into a bad output
- Per-workflow cost telemetry — token spend is predictable before you scale
If your team is searching for answers across documents and systems — whether you've built something or are just starting — retrieval needs to be accurate, permission-aware, and measurable.
Knowledge Retrieval
- Permission-enforced retrieval at query time — the right content reaches the right person, enforced
- Evaluation harnesses with recall baselines — retrieval quality is measurable, not guesswork
- Structured ingestion and chunking — answers come from the right source, not just the most recent
Your AWRA score flagged security gaps. Or you already know your AI handles sensitive data and no one has ever tested what happens when a user tries to break it.
AI Security & Hardening
- Adversarial testing & prompt injection red-teaming — we attempt to break your system before someone else does
- Access control audit at the query layer — enforce who can reach what, at retrieval time, not via model instructions
- Data sensitivity review — map PII, regulated, and customer data flows through your AI stack and close the gaps
The workflows you automate are only as reliable as the platform running them. Without the right foundation, the first production incident becomes the last time users trust it.
Platform & Reliability Engineering
- Full-stack observability with alerting — incidents surface in dashboards, not customer complaints
- CI/CD pipelines with rollback capability — deployments don't break what's already running
- Cost telemetry and budget controls — infrastructure spend is trackable and predictable
Not sure which service you need — or whether you're ready to build at all? An audit gives you a structured answer, a prioritised set of findings, and a clear path forward before you commit to anything.
AI Readiness Audit
- AI Audit Lite — one workflow, one system. Covers process fit, architecture gaps, and data readiness. Delivered in two weeks. Includes a findings report and a prioritised action list.
- AI Audit Full — your full workflow portfolio or a complex multi-system build. Covers all four readiness constructs: automation leverage, production risk, economic confidence, and evidence quality. Delivered in two weeks. Includes an architecture decision record, full findings report, and a phased build roadmap.