Step 1
You engage.
Drop a workflow into the form, or pick the AI agent for your role and walk through it with them. We capture the pain in your words, the role-owner, the tools in play.
AI Agent for Engineering
Less heroics. More shipping.
Your senior engineers spend the week on incident triage, sprint planning, and PR review queues instead of building. Agents triage the pages, draft the sprint plan, and sweep the PR queue. Your engineering lead signs every artifact before it ships.
What changes in your engineering week.
Some of the repetitive jobs agents run for engineering leaders — there's more where these came from. Click the one that's eating your week.
Engineering metrics that explain themselves.
DORA metrics, velocity, deploy frequency, lead time — pulled from your tools, with the weekly narrative on what moved already drafted. Your engineering lead reviews and signs.
See the workflow
Releases coordinated, not chased.
Release readiness checked, changelog drafted, stakeholders notified, deploy approved. Your release captain signs the go-no-go; agents handle the orchestration.
See the workflow
On-call that doesn't burn out the senior engineer.
Pages triaged, runbook surfaced, similar past incidents linked, draft response written. Your on-call decides; agents handle the comms and the doc.
See the workflow
Sprint plans drafted from the actual backlog.
Backlog groomed, capacity calculated, dependencies flagged, sprint draft ready before planning. Your engineering manager approves; the team walks in deciding what to ship.
See the workflow
AI code review — every PR pre-checked for logic, security, style.
The agent reviews the actual code. Logic, style, security, test coverage all flagged before a human opens the PR. Reviewers see a summary and the open questions; senior eng time goes to architecture, not nits.
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Developer experience that actually improves.
Build times, CI flakiness, deploy friction, dev surveys — measured against real activity. The platform team gets a prioritized fix list each cycle. You decide what ships next.
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DevOps automation, run for you.
CI/CD glue, deploy scripts, environment provisioning, dependency updates — drafted by agents, approved by your platform lead. You stop hiring just to maintain pipelines.
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Code review queue management — stale PRs nudged, reviewers rebalanced.
Different angle from the AI review above: this one runs the queue. Stale PRs get nudged, overloaded reviewers get rebalanced, low-risk dependency bumps get merged after agent checks. Your senior reviewers only see changes that actually need them.
See the workflow
Don't see yours? If it's repetitive and an engineering leader still needs to sign off — we probably run it. Tell us the workflow →
How it works
From your first reach-out to agents running across your role.
Four phases. The lift sits with us — yours is naming the work and signing off on what ships.
Step 2
We come back with a proposal.
A proposal lands in your inbox — the workflow we'd target first, the access we'd need, what we'd commit to deliver. We follow up with a call to walk through it.
Step 3
We start with the smallest meaningful slice.
One workflow, agents take it off your team's plate. End-to-end, on real data.
Step 4
We scale into adjacent workflows.
Once the pilot proves out, we expand — the next workflow in your role, then the next. One operator, covering more of the queue you used to carry.
Ready to pressure-test it?
Talk to an agent or drop a note. We'll come back with a proposal.
FAQ
Frequently Asked Questions
Is my data private? Do you train on it?
Your data stays yours. Agents read what they need to do the work. Nothing is stored on our side. Nothing is used to train models. Every action is captured in an audit trail you control.
Do you replace employees?
No. AI Ops is built to skip the support layer of repetitive execution beneath your senior role-owner — not to replace the role-owner. Your team keeps every judgment call; agents handle the routing, copying, and chasing that fills the week.
What happens if the AI makes a mistake?
Every action is reviewable in an audit trail. Sensitive steps pause for human approval before they execute, so mistakes are caught before they ship — not after. If something goes wrong, we own the fix as part of the managed-service retainer.
How are you different from Zapier, Make, or n8n?
Those are DIY builders — you build, you maintain. We are a managed service: we map the workflow, deploy the agents, monitor them, and own the upkeep. You see the outcome, not the configuration.
How can I learn more?
Two ways. Submit the short form just below and a member of our team will follow up within a business day. Or open the chat bubble in the bottom-right corner — the agent can walk through your situation and answer questions on the spot.
Let's look at your workflow together.
Talk it through with an operator now, or send a note. Tell us what's eating your week — we're here to take routine work off your team's plate so they move faster on what matters.
Engineering
Your Engineering agent
LIVE · TALK OR TYPE
Talk it through with your operator.
A few minutes with the operator who knows this kind of work. Tell them what's slowing you down; if it's a fit, we'll line up a human follow-up to take it further.
Talk or type — your choice. No phone number needed.
ASYNC · 1 BUSINESS DAY REPLY
Or send us your workflow.
Tell us what eats your week. We read every one and reply within a business day.
