For CTOs

Increase throughput without lowering the bar.

Give teams an AI delivery layer with visible plans, isolated execution, required tests and human-reviewed pull requests, not an opaque shortcut around engineering practice.

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The Sprints view: upcoming, active and completed sprints, with the finished sprint open to its burn-down chart

How AnedAI fits the way you work.

  1. 01

    Standardize the path to code

    Work begins from a connected intent and implementation plan. Every agent receives the same constraints, context and acceptance criteria before it touches the repository.

    An issue where the AnedAI agent explains its approach and opens a pull request

  2. 02

    Keep execution contained

    Each build runs in its own sandbox and follows the repository's checks. The output arrives as a reviewable pull request rather than an untracked production change.

    The roadmap timeline: capabilities laid out by month, grouped by status

  3. 03

    See delivery at every level

    Trace from company intent to capability, sprint, issue and code. Leaders get portfolio visibility while engineers retain the detail needed to make sound decisions.

    The Sprints view: Sprint 12 open to its burn-down, trailing by six issues, with its completed sprints below

Ask AnedAI

Ask AnedAI instead of hunting through your tools.

The questions engineering leaders ask every week. Today each one is a hunt across tools. In AnedAI it is one question, with the sources attached.

Without AnedAI

  1. GitHubSearch the codebase
  2. ConfluenceRead the API docs
  3. SlackAsk each team

3 tools, and you still have to stitch the answer together.

@anedai What breaks if we change GET /me?

anedaiAgent

Three things: the web ActionMenu, the mobile admin route guards, and the rule that users only see what they can do.

  • Contract: GET /me · scopes
  • web
  • mobile

One question one answer, with the sources linked.

Ready when you are.

Start with a bounded project and evaluate the complete plan-to-PR workflow.

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