Questions, answered plainly.

A general chat assistant answers whatever you ask, in any order, and forgets the journey. Safua teaches one field in sequence, watches your real work with your consent, drives the session toward what you need next, remembers where you are over time, and proves what you became at the end.

Observation produces evidence; evidence is scored for independence, assistance level, correctness, and integrity; scored evidence becomes proof. Proof carries a confidence level: observed practice, verified applied task, or high-assurance credential.

Observation is consent-based and never silent. There is a visible indicator when Safua is watching, you can stop it with a single action, and raw screen frames are not stored by default. You see what it sees.

Pricing is not finalized yet. We will publish it once the product is ready and the economics are validated. The pricing model and the two paths are shown on the pricing page.

The desktop app is in development. Join early access and we will notify you when preview access opens. Nothing here implies the app, observation, scoring, or credentials are live yet.

Ten fields at launch: AI Engineer, Data Analyst, Software Engineer, Cloud/DevOps Engineer, Cybersecurity Analyst, Product Manager, UX Designer, BI Analyst, MLOps Engineer, and Data Engineer.

The career path runs over months toward becoming role-complete and ends in a high-assurance credential. The capability path runs over weeks toward a specific outcome and ends in a practical-competence credential. Both use the same scored proof pipeline.

No. Safua is built to be transparent, not to hide help. Every bit of assistance is recorded and factored into scoring, and proof measures what you can do unaided. Leaning on full solutions lowers the proof credit your work earns, so cheating defeats the point.