A busy open-plan engineering floor: engineers at dual monitors, a team talking at a whiteboard behind them.

Custom software · AI products · Production engineering

Software you can run a business on.

Senior engineers who build AI products, take prototypes to production and strengthen the systems your business already runs on.

Built with Lovable, Bolt, Replit or Cursor? The Quick Security Check reports what is exposed in 48 hours, and its fee is credited toward the App Readiness Review. All prices

Photography is illustrative.

Engineering at production volume.

automated tests
20,900+
CI runs
16,800+
commits
11,000+
database migrations
2,500+

Counted 22 Sep 2026 from the repositories and CI history of three codebases our engineers built and run, including a production telehealth platform. Rounded down. How we counted

How we work

Engineers direct it. AI speeds it up. Every change is checked.

  1. A founder on a phone call at a cafe table, with a video call open on her laptop.

    01

    Talk to an engineer

    A free first call about what you have and what you need. Not a salesperson.

  2. An engineer marks up a printed review with a red pen at a desk at night.

    02

    Get a priced first step

    A short discovery or assessment, in writing, priced before any billable work.

  3. Two engineers pair at dual monitors, one pointing at a line of code.

    03

    Build, review, ship

    Small steps in your repository. A model reviews every change; a senior engineer merges it.

The Oracis AI engineering system A scoped brief goes to a dispatcher, which assigns work to AI model seats: architect, researcher, designer and engineer. Each seat runs in an isolated sandbox under a hard spending cap. The engineer's change goes to an independent reviewer model; findings loop back for repair. A human engineer reads the diff and merges it to production. Input Scoped brief Dispatch Architect system design $ cap Researcher live sources $ cap Designer concepts, copy $ cap Engineer code + tests $ cap each seat: isolated sandbox, provider‑enforced budget Reviewer independent model finding → repair → re-review Human merge Output Production The Oracis AI engineering system A scoped brief goes to a dispatcher, which assigns work to AI model seats: architect, researcher, designer and engineer. Each seat runs in an isolated sandbox under a hard spending cap. The engineer's change goes to an independent reviewer model; findings loop back for repair. A human engineer reads the diff and merges it to production. Input Scoped brief Dispatch each seat: isolated sandbox · provider‑enforced budget Architect system design $ cap Researcher live sources $ cap Designer concepts, copy $ cap Engineer code + tests $ cap Reviewer independent model finding → repair → re-review Human merge Output Production
Fig. 0How work moves through the Oracis engineering system

How the system works, and its limits →

Products

Built by the same engineers. Available on their own.

Oracis Engineering builds and rescues software for clients. We also build products of our own, and you don't need one to use the other.

  • Private preview · invitation only

    Fleet by Oracis

    Capabilities for existing engineering workflows.

    An engineering runtime for AI-assisted teams. The runtime Oracis engineers use every day: bounded engineering workers, repository intelligence, research, review and repair, browser tools, cost controls and operational evidence. Its hosted jobs, independent validation, evidence and lessons are offered to invited organizations in private preview.

    Explore Fleet →
  • Coming Christmas 2026 · Target launch · In development

    Provenyard

    One connected application to work in.

    Research. Plan. Build. Improve. One connected workspace. The all-in-one AI workspace we're building for research, planning and software creation, with Fleet supplying the engineering execution underneath. Engineering work, with proof.

    Explore what we're building →

Need a team to build, improve or rescue your software? That is still what Oracis Engineering does. Discuss your project →

Bring the product. Bring the prototype.

An AI feature, a new product, or an AI-built app that needs production engineering. Start with what you want to build.