Turn epics, bugs, reviews, releases, and internal delivery paths into governed agent workflows that fit your stack.
Agentic workflow deployment
Deploy agents into real engineering work.
We help teams turn agent experiments into controlled workflows across repos, tickets, reviews, CI, chat, and approvals.
Custom deploymentOne governed path
Your tools, agents, permissions, handoffs, and checkpoints wired together.
Driftblocked
Ownervisible
Actionstyped
Reviewrequired
Control plane preview
Work is visible while it is happening.
A workflow is not a prompt chain. It is an operating path where agents claim work, pass through gates, expose blockers, recover from failure, and stay inside the intent set by humans.
midfleet
Step 4 of 8: ImplementIteration 1 routed to address-engineer via hnd_0dI5f8o3ni7t.
waitingOwneraddress-engineer
ActionCommand delivery failed
Waiting onOperator recovery
Next stepResolve blocker or loop back
OperatorInspect blocker
Activity3h ago
Workflow pathclick a stage to inspect state
ImplementThe implementation is paused because command delivery failed.
What we can build
Start wherever the work already breaks.
The scope can be a single engineering path or a connected set of workflows across the organisation. We shape the system around the outcome, not a fixed template.
Connect repos, tickets, docs, CI, chat, approvals, and custom tools so agents can move work without losing context.
Define what agents can do, when humans approve, how actions are explained, and how your team extends the workflow after handoff.
Deployment sprint
Built like a deployment engagement, not an AI workshop.
We work inside your current engineering motion: understand the work, shape the agent paths, connect the required systems, set the guardrails, and leave behind workflows your team can inspect, change, and extend.
Map goals, teams, systems, tools, and where agent work currently breaks.
Turn the work into agent paths, checkpoints, permissions, and recovery loops.
Wire the workflows into repos, issues, reviews, docs, CI, chat, and agents.
Track output, drift, rework, approval load, and where to expand next.
Typical builds
Representative workflow shapes.
Examples of the guarded engineering paths we set up across repos, reviews, CI, and approvals.
A guarded engineering path across intake, planning, implementation, review, QA, and merge gates.
A multi-touchpoint workflow spanning CI, human approvals, release checks, and post-merge follow-through.
FAQ
Questions teams ask before we build.
Deployment, guardrails, scope, and pricing are shaped around the workflow you need.
We design and wire custom agent workflows for engineering work across intake, planning, implementation, review, QA, approvals, release paths, and cross-tool handoffs.
Yes. We shape the workflow around the stack you already use across repos, issue trackers, docs, CI, chat, and internal approval paths.
We define allowed actions, ownership rules, human checkpoints, and recovery loops so agents can move work without drifting out of scope.
Yes. We can start with one path or design a connected set of workflows across the engineering motion, depending on where the operational value is.
Pricing is scoped per request. It includes the platform costs and the workflow build work required for your environment.
You are left with a working path your team can inspect, extend, and operate, along with a clearer view of where to add the next controlled workflow.
Talk to us
Tell us where agents should create controlled output.
Good fits are teams already using AI coding tools, but missing the scaffolding that lets agents work across systems without drift, unsafe actions, or manual reassembly.
- Custom workflows and touchpoints in scope
- Human approvals and permissions by design
- Clear output measures from the start