# Interpret AI (interpretai.tech)

Builds reinforcement-learning training environments that give agents dense step-level rewards for CAD and robotics tasks.

- Atlas card: https://inite.ai/en/atlas/interpretai.tech
- Site: https://interpretai.tech
- For: Teams training AI agents on CAD drafting, manufacturing and robotics tasks that need step-level reward signals.
- Categories: agents
- Use 0/100 · alive 87/100

## Used for

- Build reinforcement learning environments for CAD modeling workflows
- Pinpoint the first invalid modeling step in failed agent rollouts
- Train robotics agents on simulated manufacturing tasks

## Price

Not read yet.

## For developers

- MCP server: tech.interpretai/PostAgent (namespace; open on 2026-10-26, 14 tools)
- Read 2026-10-26

## MCP server, measured daily

Server: https://api.postagent.sh/mcp, checked every day since 2026-10-26 (3 checks).

- Answered: measuring, 3 daily checks so far
- Median first answer: 174 ms
- Sign-in: none
- Context its tool definitions take: about 7232 tokens (14 tools)
- Tool definitions: B, 88/100
- Failing "params_described": 10 of 14 tools
- Warning "open_writes": create_letter, create_template, create_card_checkout, pay_mail_with_shared_payment_token, create_postcard_art
- Method: https://inite.ai/en/atlas/mcp/report

## Your data

- Certifications stated: none
- Read 2026-10-26

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Source: INITE Atlas, https://inite.ai/en/atlas/interpretai.tech. JSON: https://inite.ai/api/atlas/interpretai.tech. MCP: https://inite.ai/api/mcp (atlas_lookup).