Automatically build, test, and deploy your AI projects

Automatically tests new code changes, builds them, and deploys your AI project live, then alerts your team of the result.

How the work actually flows

It branches. Exactly one path is taken; a person is alerted when a step fails.

Pattern: Exclusive Choice (4) · Simple Merge (5)

flowchart TD trig>"code change pushed"]:::trig s0["pull latest code"]:::task s1["run automated tests"]:::task s2["notify team of result"]:::task trig --> s0 s0 --> s1 gx{"× did tests pass"}:::gate s1 --> gx p00["build and package project"]:::task gx -->|"tests passed"| p00 p01["deploy to hosting platform"]:::task p00 --> p01 p10["skip deployment"]:::task gx -->|"tests failed"| p10 jn{"○ notify team"}:::gate p01 --> jn p10 --> jn jn --> s2 out[/"tested build deployed live"/]:::out pay{{"faster reliable releases"}}:::pay s2 --> out out --> pay esc(("Alerts a person")):::human s1 -. "if it fails" .-> esc esc -.-> out classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
Starts itA stepA personOne path onlyPaths rejoinResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
Messaging & NotificationsAPI & Webhook IntegrationDevOps & IT Operations
Connects
VercelSlack

The problem it solves

You want to ship AI features quickly, but manually testing and deploying every code change is slow and easy to get wrong. Bugs and broken builds are more likely to reach production when a person has to remember every deployment step.

Who it fits

Teams building and shipping AI-powered products who want a reliable release process.

How it works

  1. A new code change or a scheduled check kicks off the process
  2. The latest code is pulled and automatically tested
  3. If tests pass, the project is built and packaged
  4. The new build is deployed to your hosting platform
  5. Your team is notified in Slack whether it succeeded or failed
What you get

Deployments that finish without anyone watching

New code changes get tested, built, and deployed automatically, with your team notified the moment it's done.

What you get

A tested, deployed version of your AI project, with a pass/fail notification.

What you need

A code hosting account, a deployment platform account such as Vercel, and a Slack workspace.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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