AI agents for engineering teams. More shipped. Same team. Higher bar.
Echelar's AI agents take requests from anyone in the company to a reviewed, tested pull request on your architecture. Ship more of the roadmap without adding headcount, while your engineers spend their time on decisions instead of re-reading AI drafts.
A 45-minute live call. We connect one repository, and you can remove access after.
See the pathMore code, faster. Same delivery speed.
Copilots made implementation fast. Review, testing and incidents still run on the same senior engineers, so more AI code means a longer queue in front of them.
Today, AI speeds up one stage. Work piles up at review and testing, and delivery runs at the same speed.
Today, AI speeds up one stage. Work piles up at review and testing, and delivery runs at the same speed.- Business needFounder, ops, salesManual
- RequirementsA spec someone writesManual
- ArchitectureWhoever knows the systemManual
- PlanningEngineering leadManual
- ImplementationCopilot or app builderAI-assisted
- ReviewA senior engineer, if anyManualWork waits here
- TestingCI, if it existsManualWork waits here
- IncidentsWhoever is on callManual
What changes for your team.
Echelar is a governed team of agents, not one more assistant beside the work.
- Pull requests arrive reviewed, fixed and checked.
A separate PR Reviewer reads each change against your architecture and docs. A blocking finding goes to a separate fix Session, on demand or through the echelar label, and checks are recorded on the exact head commit.
- Anyone can start the work.
Product, ops and support ask in Slack, Linear or Echelar. Your engineers review and merge, so the bar stays theirs.
- Recurring work becomes an Automation.
Pull request review and alert investigation start on their own trigger, and documentation is re-checked on every change. Each Automation is versioned, audited and enabled by a person.
- Context compounds instead of walking out the door.
Memory carries its source and confidence and is demoted when the code changes. A correction your team repeats becomes a proposed Skill, disabled until someone enables it.
Agents propose, build and review. Only people merge, deploy and enable.
Measure accepted work, effort and cost.
Agree what a useful result looks like before implementation. Evaluate the accepted change, the effort left with your team and the cost to deliver it.
- What Echelar shipped and spent.
Agree request-to-accepted-change time, review effort, rework and execution cost against your baseline.
- The cost of accepted work.
Assess completed work alongside model and execution costs, review time and exceptions. Compare like-for-like jobs before expanding the scope.
How teams start.
One repository and one painful job, then wider as the evidence builds up.
- 01Connect one repository
Install the GitHub App on the repository that hurts most. Before turning the PR Reviewer on, you can rehearse it privately on pull requests your team already merged.
- 02Pick one painful job
Pull request review, incident investigation, documentation, or a backlog that never moves. Echelar takes it from the next request.
- 03Add Automations as trust builds
When a job works, Echelar drafts the Automation that repeats it. It stays disabled until a person enables it.
- An isolated sandbox per Session
- Your own model keys, encrypted
- A model budget per Session
- Owner, admin and member roles
- Versioned Automations a person enables
- An audit record for every Automation fire
Questions engineering leaders ask first.
How is this different from Cursor, Claude Code or Copilot?
Those tools make each engineer faster at writing code. Echelar takes the path around the code for the whole team: requests from anyone, planning on your architecture, review, fixes, checks and a record of what it cost. Keep the tools your engineers like.
Where does our code run?
On Echelar's control plane, in an isolated sandbox per Session, scoped to your organization. It does not run inside your infrastructure. The security overview has the details.
Can we try the reviewer before it comments on live pull requests?
Yes. Rehearsal runs the PR Reviewer on pull requests your team already merged and keeps those reviews private. It is optional, and the decision to enable is recorded.
What can agents change?
Agents read, plan and build in a sandbox. Code changes go only to the branch of the pull request a Session is working on.
What does it cost?
You bring your own model keys and pay providers directly. Echelar is in early release, and early teams agree pricing with the founder.
Bring the repository you'd never trust to a demo.
Not the toy repo. The one held together by tribal knowledge. We'll point Echelar at it live. You'll see what it reads, what it builds, what it catches, and where it stops for your call.
A 45-minute live call. We connect one repository, and you can remove access after.