| What it does | Agentic operations platform for digital marketing with automated workflows, knowledge bases, and predictive optimization
| Catch where AI agents get stuck on your API or MCP server, rank problems by impact, and draft fixes as pull requests
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| Stage | MVP
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| Founded | Not given
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| Based in | Not given
| US
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| Pricing model | Freemium
| Freemium
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| Pricing | Agency plan: $5,000 per month (free during private beta for 10 agencies). Includes 368,000 credits per month, unlimited seats and clients. Free tools available without account or payment.
| Open source: free. Team: $199/month with 14-day free trial (1 API or MCP service, 25,000 reports/month, 15 coding-agent runs/month). Business: $799/month (up to 3 services, 250,000 reports/month, 60 coding-agent runs/month). Extra coding-agent runs: $6 each.
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| Key features | - AI specialists with custom roles and knowledge bases
- Compartmentalized living RAG knowledge bases
- Visual workflow builder with triggers, nodes, and logic
- Predictive CRO test generation and simulation
- Multi-model orchestration across Anthropic, OpenAI, Google, and Groq
- Image and video generation from brand knowledge
- Chrome plugin to capture web content
- Per-run cost tracking and usage dashboard
- Workflow export and import as JSON
| - Session replay for MCP servers to identify failed agent sessions
- Clustering reports by agent goals and workflows
- Priority ranking weighted by frequency, failed workflows, and affected accounts
- Claude Code generates pull requests with tests
- Review queue with diff, tests, agent reports, and evidence
- Isolated git worktree prevents unauthorized code push
- Schema validation and rate limiting for feedback
- Open Agent Feedback Protocol with TypeScript and Python SDKs
- GitHub integration for draft PR creation
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| What makes it different | - Built specifically for marketing teams with first-class CRO, SEO, and content workflows
- Model-neutral platform supporting multiple LLM providers without vendor lock-in
- Knowledge that compounds and grows with use instead of resetting each session
- Cost transparency with per-run estimates and usage dashboards by model and user
- Full data ownership with compartmentalized storage and export capability
| - Only AI agent failures on successful HTTP responses get detected and ranked
- Automated pull request drafts with your approval required before shipping
- Session replay captures failures even when agents don't report them
- Pay only for coding-agent runs, not feedback submission
- Open protocol and SDKs can be self-hosted at no cost
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 10 ● no change since last check | 1 ● no change since last check |
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| Trust Flow (Majestic) | 0 | 1 |
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| Citation Flow (Majestic) | 14 | 14 |
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| Referring domains (Majestic) | 1 | 4 |
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Lattice Ops
Backloop