| What it does | Amazon data and action layer for any AI
| Open-source AI agent orchestration platform for incident response and automation
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| Stage | Startup
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| Founded | 2025
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| Based in | US
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| Pricing model | Free trial
| Open source
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| Pricing | $97 per month after a 14-day free trial. Includes 2,000 AI tokens per month (4,000 for the first 3 months), 10,000,000 data rows, one seat, unlimited Seller Central, Vendor Central and Amazon Ads connections, MCP, REST API, BigQuery access, and write-back Actions. Add-ons: +$49 per 10M data rows, +$
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| Key features | - MCP and REST API access to 130+ Amazon tables
- Connect to any AI including Claude, ChatGPT, Gemini, Cursor
- Write-back Actions to update listings, prices, bids and orders
- BigQuery integration for custom queries and BI tools
- Unified data from Seller Central, Vendor Central and Amazon Ads
- About two years of historical data backfilled
- Amazon-approved for buyer PII handling
| - Incident response with agent investigation and pull request generation
- Automated workflows triggered on schedules or webhooks
- Agent summoning from GitHub, GitLab and Radicle with /ryph command
- Semantic memory system for shared and persistent agent learning
- Credentials kept behind gateways with no access in sandbox
- Customized environments per repository with cached dependencies
- Browser use for agent interactions with live watching
- Artifacts and pages for reports and overviews
- Deployment options from laptop to Kubernetes
- Tool proxy with allowlisted MCP server integrations
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| What makes it different | - Single normalized schema joining Seller, Vendor and Ads data
- Retains data history longer than Amazon's API windows
- Lower AI token consumption than Amazon's own MCP
- Writes off by default with optional dry-run preview
- No per-account billing for unlimited Seller, Vendor and Ads connections
| - Agents work without holding real credentials or keys
- Changes ship as patches that require review before merge
- Runs on your own infrastructure from laptop to cloud
- Semantic memory learns across runs with deduplication and contradiction handling
- Built-in safety assuming agents can be manipulated or exploited
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 23 ▲ +1 (up) since last check | Not checked yet ● no change since last check |
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| Trust Flow (Majestic) | 16 | 0 |
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| Citation Flow (Majestic) | 38 | 0 |
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| Referring domains (Majestic) | 124 | 0 |
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DataDoe
Ryph