Agent design
Each agent is purpose-built for a specific task — research, drafting, validation, routing — with its own tools, prompts and guardrails.
Services
Multi-Agent Workflow
Complex problems, solved by a team of AI agents
When a single AI cannot handle the full workflow, we build a team of specialised agents — each an expert at one part — orchestrated to collaborate, hand off context and deliver results that no single model could.
- Specialised agents for each sub-task
- Orchestrator manages handoffs and state
- Parallel execution for speed
- Human-in-the-loop checkpoints
- Observable with full trace logging
What this engagement covers
Scoped to your situation — we start with what you already have rather than a fixed package.
Orchestration layer
A coordinator agent manages task assignment, handoffs, state and error recovery across the team of specialised agents.
Tool integration
Agents call APIs, query databases, read documents and interact with external systems as part of their task execution.
Parallel execution
Independent sub-tasks run simultaneously, with results merged when dependencies allow — cutting total processing time significantly.
Observability
Full trace logging for every agent action, decision and handoff so you can audit, debug and optimise the entire workflow.
Human checkpoints
Configurable approval gates at critical decision points where a human reviews and authorises before the workflow continues.
Small first, then scale what works
Six stages, with a decision point after the pilot. Nothing grows until it has shown value.
01
Workflow Audit
Understand the current manual process, systems, users, inputs and outputs.
02
Architecture
Choose the smallest practical automation architecture.
03
Pilot
Build one usable workflow.
04
Integration
Connect APIs, browser workflows, internal tools, databases, AI models or third-party systems.
05
Validation
Test reliability, edge cases, user approval and expected output.
06
Scale
Expand only after the pilot demonstrates value.
What you get
- Multi-agent system designed for your specific workflow
- Orchestration logic with state management and error handling
- Observability dashboard with trace visualisation
- Documentation and runbook for operations and iteration
Tools we reach for
Chosen per project, not per habit. If your team already runs something that works, we build on it.
- Claude
- LangGraph
- CrewAI
- Python
- PostgreSQL
- Redis
- Docker
- AWS
FAQ
Multi-Agent Workflow — common questions
Single agents work for focused tasks. Multi-agent is for workflows that require different skills — research, analysis, drafting, validation — where one agent's output feeds another's input.
Other things we build
Have a workflow in mind?
Tell us about the process. We'll review it and suggest the most practical next step.