Cheva Labs Logo
Cheva Labsweb

About Cheva Labs

AI knowledge without a sales agenda.

Cheva Labs is an independent educational project for understanding AI systems, evaluating choices, and learning how the technology works from model to hardware.

See how we evaluate choices

What guides the work

Six commitments, held together.

Public good
Public education
Explain AI so people can understand the tradeoffs, test claims, and make their own decisions.
Autonomy
Independent judgment
Commercial popularity does not decide what gets recommended, measured, or criticized.
Inspection
Open methods
Publish enough context, assumptions, and code for readers to inspect how a conclusion was reached.
Evidence
Reproducible work
A result should include the environment and procedure needed to test it again—not only the final number.
Data rights
Privacy-aware choices
Treat local inference, data boundaries, retention, and permissions as practical design constraints.
Objectivity
Vendor-neutral comparison
Compare tools by the work they enable, the friction they create, and the limits users actually encounter.

The mission

Build decision literacy.

AI education should help people reason about models, subscriptions, hardware, privacy, and system design without depending on a leaderboard or a sales pitch.

Cheva Labs connects concepts to practical tests: what the system does, where it fails, what it costs, and whether it fits the workflow around it.

How the work earns trust

Question. Method. Correction.

  1. 01

    Define the question

    State the task, constraints, success criteria, and what would change the conclusion.

  2. 02

    Show the method

    Record the model, hardware, prompts, tools, settings, and evaluation procedure.

  3. 03

    Invite correction

    Publish limitations and make it possible for others to reproduce or challenge the result.

Integrity pledge

No sponsored ranking. No paid placement. No hidden affiliate incentive.

When a relationship could influence the work, disclose it. When evidence is incomplete, say so. When a result changes, correct it.

Inspect the Lab