Less heroics. More shipping.
Agents take incident triage, sprint drafts and PR queues off your senior engineers. 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.
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.
Releases coordinated, not chased.
Release readiness checked, changelog drafted, stakeholders notified, deploy prepared. Your release captain signs the go-no-go; agents handle the orchestration.
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.
Sprint plans drafted from the actual backlog.
Backlog groomed, capacity calculated, dependencies flagged, sprint draft ready before planning. Your engineering manager reviews it; the team walks in deciding what to ship.
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.
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.
DevOps automation, run for you.
CI/CD glue, deploy scripts, environment provisioning, dependency updates: drafted by agents, reviewed by your platform lead. Your engineers stop spending their week maintaining pipelines.
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.
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 →
Ready to pressure-test it?
Don’t see your exact process? Your teammate learns everyday work as it goes, and your plan includes one custom workflow, built around how your team actually works.
Frequently Asked Questions
Is my data private? Do you train on it?
Your data stays yours. The teammate reads what it needs to do the work, with access scoped to the resources its role requires. The models it reasons with run in Azure environments we operate under Microsoft's enterprise terms, never a public or consumer AI service, and nothing is used to train them. Every action is captured in an audit trail you control.
Do you replace employees?
No. Invellis picks up the repetitive work that fills your team's week, the routing, copying and chasing, so your people can spend their time on the work that needs them. Teams use the hours they get back to grow without burning out.
How are you different from Zapier, Make, or n8n?
Those are DIY builders: you build it, and you maintain it. With Invellis, we set up your AI teammate inside Microsoft 365, monitor it, and look after the upkeep. You see the outcome, not the configuration.
How can I learn more?
Three ways. Send us a note through the contact form, Book a Demo for a short call, or start a free trial.