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Multi-Agent Systems
When a task exceeds what one model can hold — in scale, specialisation, or the need for cross-checking — we design systems of agents with explicit contracts between them. Orchestration is deterministic code; the agents are the only probabilistic parts.
When you need this
The situations we are called into.
Document volumes or case loads exceed what single-model pipelines can process reliably.
You need independent verification: one agent's output checked by others before it counts.
A process spans systems and departments, each demanding different context and different permissions.
Approach
How the engagement runs.
Task decomposition
The work split into units a single agent can own end to end, with success criteria per unit.
Orchestration architecture
Deterministic control flow — pipelines, fan-out, verification gates — with agents as replaceable workers.
Contract design
Typed schemas for everything passed between agents, validated at the boundary, so drift fails loudly.
Failure-mode engineering
Timeouts, retries, quorum checks, and containment for the ways agent systems actually fail in production.
Load testing and rollout
Throughput, cost, and quality measured at production scale before production depends on it.
Deliverables
What you hold at the end.
Orchestration layer
Agent specifications and typed contracts
Failure-containment patterns
Throughput and cost model
Scale-test report
Related research
The evidence behind this practice.
White paper · 2026
Multi-agent systems in production: reliability patterns
Failure modes observed when orchestrating multiple LLM agents on business-critical tasks, and the containment patterns that keep them recoverable.
In preparation
Contact
Talk to our engineers.
Describe the situation you are in. The person who replies is the person who would do the work.