Agent Strategy
You know AI agents are the move. You don't know which workflows to target first. We run sprints against your real data and tell you exactly where agents will deliver.
Read moreAgent type
Multi-agent systems for work one agent can't finish
Some workflows are too complex, too cross-functional, or too high-stakes for a single agent. Multi-agent systems decompose the work, assign specialized agents, coordinate handoffs, and keep a supervisor in the loop. We design them, build them, and run them in production.
Trusted by teams building and running mission-critical platforms
Challenges
The challenge with the status quo
Single agents are great for well-bounded tasks. They struggle when the work spans systems, expertise, or decision authority. Stacking more capability onto one agent makes it brittle and harder to govern. The fix is more agents, with clear roles and orchestration between them.
Workflows span multiple systems, departments, and decision authorities
01Single agents get bloated, slow, and harder to test as scope grows
02Cross-team handoffs lose context every time work changes hands
03Audit and oversight get harder when one black box does everything
04Approach
How we deliver in production
How multi-agent systems get built, from mapping the work through to running them in production.
01
Workflow decomposition
We break the workflow into discrete jobs — each one bounded enough for a single agent to own well.
02
Agent role design
We define each agent's responsibility, tools, data access, and handoff protocol. Like designing a team org chart.
03
Orchestration & guardrails
We build the supervisor layer — who routes what, when humans get pulled in, how disputes resolve, and how failures are handled.
04
Observability
We instrument every handoff, decision, and tool call. You can replay any run, debug any failure, and prove what happened to compliance.
Outcomes
What you get
The typical shape of a multi-agent build, plus what we commit to.
Typical team size in a production multi-agent workflow
3-7
agents per system
Share of workflow steps that no single agent could own end-to-end
40%+
complexity handled
Every handoff, decision, and action logged with full lineage
100%
auditable
Capabilities
What we deliver
What multi-agent systems do in practice, and what you can hold us to.
01
Supervisor Architecture
A coordinating agent routes work, monitors progress, and pulls humans in on exceptions. No agent operates without oversight.
02
Specialized Roles
Each agent has a narrow, well-defined job. Easier to test, tune, and replace than one giant agent.
03
Cross-System Handoffs
Agents coordinate across CRM, ERP, data warehouse, and internal APIs — without context loss.
04
Dispute Resolution
When two agents disagree, escalation rules and tie-breakers kick in. Humans can intervene at defined points.
05
Replay & Debug
Every run is replayable. You can rerun a failed workflow from any step and see exactly what each agent did.
06
Compliance-Ready
Full audit trails per agent, with role-based access. SOC 2, HIPAA, and SOX-friendly out of the box.
How to get one
The engagements that build multi-agent systems
Most multi-agent systems engagements start with strategy, move through engineering, and end up in operations. Pick where you are.
Start here
Bring us the end-to-end process
The one that crosses four systems and three teams. We will tell you where to split it across agents, how they hand off, and what stays under human control.