Case Study

SAIBA Audit: AI readiness as a reviewable system

SAIBA

AI projects often start with too many assumptions. Which systems exist? Which data can be used? Where do humans approve? What is the first workflow worth building?

SAIBA Audit was built to make that analysis concrete, shareable, and repeatable.

SAIBA Audit dashboard

The challenge

Workshops and discovery notes can quickly become unstructured. That makes it hard to compare opportunities, document risk, and give the customer a clear next step.

The solution

The audit flow brings category scoring, workflow models, data and tool notes, privacy overview, and report export into the same app.

What changed

The customer gets a concrete basis for decision-making. SAIBA gets a better bridge from first conversation to scope, prototype, and implementation.

Technologies

Technology Usage
React + Vite Audit interface and report views
Supabase Auth, database, and storage
Playwright / Vitest Regression testing and QA

Services delivered by SAIBA

  • Workflow audit
  • Readiness scoring
  • Report design
  • Privacy and access model

Want to start with a concrete AI readiness overview?

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