What it takes to make autonomy hold.
Four disciplines that overlap on every serious agentic build. One of them alone is rarely enough.
Agentic Systems
Multi-agent architectures that plan, delegate and finish work instead of just answering.
We design the topology first: which agent owns which decision, where control passes, what a supervisor is allowed to override. Then we build it — planner and worker roles, typed tool contracts served over MCP so one integration is reachable by every agent, shared memory, and explicit stopping conditions so a loop can never run away. The result behaves like a team you can staff up, not a prompt you have to babysit.
- Agent topology and role design
- Planner / executor / critic loops
- Typed tool contracts, served over MCP
- Shared and per-agent memory design
- Escalation and hand-off protocols
Autonomous Workflows
End-to-end business processes handed to agents, with humans kept at the decisions that matter.
We start from a process you already run manually and map every step, exception and approval. Agents take the repetitive span; people keep the judgement calls, and the hand-off between the two is designed rather than accidental. Every run is replayable, so an exception becomes a test case instead of a mystery.
- Process mapping and automation scoring
- Human-in-the-loop approval gates
- Exception handling and fallbacks
- Replayable run history
- Rollout plan with reversible stages
Applied Intelligence
Retrieval, reasoning and domain knowledge wired into agents that answer with receipts.
An agent is only as good as what it can look up. We build the retrieval layer — chunking that respects document structure, hybrid search, reranking, and citations that point at a real source. Where the domain is narrow enough to be worth it, we fine-tune or distil to a smaller model and cut both latency and cost.
- Hybrid retrieval and reranking
- Structure-aware document pipelines
- Grounded answers with citations
- Fine-tuning and model distillation
- Golden datasets and eval harnesses
Agent Infrastructure
The unglamorous layer that decides whether an agent survives contact with production.
Traces for every step, tokens and cost attributed per run, evaluations that gate a deploy, and guardrails on both input and output. We instrument agents the way you would instrument a distributed system, because that is what they are. When something drifts, you see it in a dashboard rather than in a customer complaint.
- Step-level tracing and replay
- Offline + online evaluation suites
- Prompt and model version control
- Cost, latency and token budgets
- Input/output guardrails and red-teaming
The picture we draw on the whiteboard.
Every point follows the same flow field, gives way to your pointer and settles back to where it started. It is a visualisation, not a multi-agent simulation — the points never see one another, and the formation holds because each is tethered to a fixed home. We keep it because it is the picture we reach for when we argue that coherence across many agents comes from the topology you design, not from a longer prompt.
Every point follows the same flow field and returns to a fixed home. Nothing here talks to anything else: it illustrates the argument for designing agent topology rather than simulating it.
Three ways to start.
Different levels of commitment, same delivery standard. A sprint is the cheapest way to find out whether there is a case at all; the other two assume that answer is already yes.
Autonomy Sprint
Fixed feeA focused assessment of one workflow, ending in a working prototype of the riskiest part and an honest verdict on whether to proceed.
- Process mapping workshop
- Feasibility + value scoring
- Riskiest-assumption prototype
- Architecture recommendation
- Go / no-go with reasoning
Best whenYou suspect there is a case for agents but need proof before committing budget.
Build Partnership
MonthlyAn embedded team that designs, builds and ships the system into production, then stays long enough to widen its scope safely.
- Dedicated senior squad
- Full agentic system build
- Evaluation + observability stack
- Staged autonomy rollout
- Documentation and runbooks
Best whenThe decision is made and you need it built properly the first time.
Embedded Crew
RetainerSenior agentic engineers working inside your team on your board, transferring capability while shipping alongside your people.
- Engineers in your workflow
- Paired delivery and review
- Architecture guardianship
- Team training and enablement
- Rolling monthly scope
Best whenYou have engineers and want them fluent in agentic systems, fast.