Multi-agent AI systems
Specialised agents coordinating under a supervisor, with shared memory and clear handoffs.
- Engagement
- Phased build with a review gate after the baseline
- Typical timeline
- 8–10 weeks
- Starts with
- A single-agent version of the task, run against twenty real cases to find where it breaks.
Most work described as needing a team of agents needs one well-built agent and better tools. The design earns its cost in a narrower case: when the job genuinely splits into roles with different context and different permissions, and a single agent has measurably stopped coping.
Complex work split into steps that can be inspected and trusted.
What we build
Concrete artefacts, handed over and documented.
- 01
An orchestrator you can read, routing between agents is explicit code, not an emergent conversation between chatbots
- 02
Narrow roles with narrow tools: the researcher cannot write to your database, the writer cannot spend money
- 03
A critic step that checks the result against the original brief before anything is handed back
- 04
A budget ceiling for the whole run, because cost multiplies with every role you add
- 05
Traces showing which agent said what, in order, with the time and tokens each consumed
- 06
The single-agent baseline kept alive for comparison, so the added complexity has to keep earning its place
What changes
Work that needed three specialists in sequence runs as one job
A bad output can be traced to a role, a tool or a brief rather than blamed on the model
Complexity survives only where it beats the simple version by a measured margin
How it runs
01Baseline
We build the single-agent version first and run it against twenty real cases to find exactly where and why it fails.
02Roles and orchestration
Only the roles the baseline justified, each with its own tools, context and spending limit.
03Harden and hand over
Budgets, traces, failure paths and a documented way for your engineers to add a role without our help.
Chosen per project. Named here so you can see the shape of it.
- LangGraph
- Anthropic Claude
- OpenAI
- Temporal
- Langfuse
- Postgres
Questions we get asked
Tell us the outcome, not the tooling.
Send us the situation you are in. We will tell you which discipline it belongs to, what we would do first and what it costs, including when the answer is to wait.