# Panto AI — tools that shaped CodeVetter

> Canonical page: https://codevetter.com/inspiration/panto

Design documents, tickets, and code history can be relevant to review.

## What we admire

Panto’s approach to reviewing with multiple context sources stood out in our landscape survey. A changed function can satisfy its local tests while still violating a product requirement recorded elsewhere.

## The principle that stayed

More sources can improve review only when the system identifies where each claim came from. A plausible business rule inferred from prose is a lead, not an observed runtime result.

## Where CodeVetter stands

CodeVetter’s intent and business-rule work preserves source identity and uncertainty. Panto is a research reference; our local verifier does not import Panto’s context or scanning service.

## Sources

- [Panto official site](https://www.getpanto.ai/) — the creator's own source
- [CodeVetter codebase-context research](https://github.com/Codevetter/codevetter/blob/main/docs/knowledge/codebase-context-tools-landscape.md) — the CodeVetter project record

This is independent appreciation, not endorsement, partnership, code reuse, or feature parity.

## Public product links

- [CodeVetter](https://codevetter.com/)
- [Download](https://codevetter.com/download)
- [Documentation](https://codevetter.com/docs/)
- [Source](https://github.com/Codevetter/codevetter)