What we build
Agentic workflow design that starts with the operating model, not the model
The hardest part of building agentic systems is not the AI. It's deciding what an agent should and should not own. We do that work first, every time.
The discipline
Designing what an agent should own is harder than building the agent
Most agentic AI projects fail not because the agent can't do the work, but because no one mapped the decision surface before the build. The agent ends up making calls it shouldn't, or escalating ones it should be solving.
We treat workflow design as the primary deliverable. By the time we write our first line of agent code, the operating model is on paper, signed off by the operations leader, and translated into evaluation criteria.
The result: agents that ship to production on the first attempt, hit their SLAs in week one, and don't generate the long backlog of "edge cases" that sinks most autonomous systems.
Our 5-phase design process
From operating reality to a production agent in 60 days
Workflow archaeology
We sit alongside your team for two weeks, instrument the existing process end-to-end, and document every decision, exception, and handoff. No assumptions — only ground truth.
Decision boundary mapping
We mark every place a human exercises judgment. Some of those will become agent decisions. Most will not. The map is the contract for what we will and will not automate.
Agent topology design
We design the multi-agent system: which agents exist, what they own, how they communicate, and where the human sits in the loop. We default to the smallest topology that meets the SLA.
Evaluation harness first
Before we write production code we build the offline eval suite — golden datasets, regression tests, scoring rubrics. The harness is the spec; everything else is implementation.
Iterate to outcome
We ship to a shadow environment, score against the harness, and only promote when the agent meets the contracted accuracy and cost targets. Promotion is a decision, not a date.
Design principles
Four rules we don't break, even when the client asks us to
Workflows over chatbots
A workflow has inputs, outputs, SLAs, and exceptions. A chatbot has a conversation. We build workflows.
Boring tools first
If a SQL query, a webhook, or a spreadsheet rule will do the job, we use that. Agents are reserved for genuinely ambiguous decisions.
Human-shaped escape hatches
Every agent decision has a defined escalation path back to a person. We design the handoff before we design the agent.
Idempotent everything
Agents will retry. Networks will fail. Every action we take must be safe to repeat. This is non-negotiable.
62
Average days from kickoff to first agent in production
94%
Of designed agents meet contracted accuracy targets in week one
3.1×
Average throughput improvement on automated workflow paths
Ready to design your first agent?
A 30-minute discovery call is enough to know whether we're a fit.
Book Discovery Call →