| What it does | Transform documents into searchable knowledge with AI-powered cited answers
| The agent-native Growth OS that turns your AI agent into a disciplined growth hacker
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| Stage | Established
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| Founded | 2003
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| Based in | US
| US
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| Pricing model | Freemium
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| Pricing | SaaS: $30 per user per month (10% discount billed annually), includes 5GB storage, 30+ agents, SSO and audit logs. 15-day free trial with no credit card required. On-Prem Edition pricing available by contacting sales.
| Free: 1 member, 1 project, unlimited free contributors and viewers. Solo: $19.90/month for 1 member with unlimited projects. Team: $39/month for up to 3 members, then $10/month per extra member, with unlimited projects and private projects.
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| Key features | - AI-powered document Q&A with page/row/paragraph references
- 30+ pre-built AI Agents for contracts, compliance, invoices and more
- Multi-source document processing (PDF, DOCX, XLSX, PPTX, CSV and more)
- Connect Google Drive and Microsoft SharePoint with auto-sync
- Query SQL databases in plain English without SQL skills
- Website content indexing for live knowledge sources
- Bring your own LLM (OpenAI, Anthropic, Gemini, Llama)
- Role-based access control (RBAC) and full audit logs
- On-premises or private cloud deployment options
- Custom Agent creation on user-defined templates
| - Complete experiment backlog with candidate ideas
- Status tracking from idea to outcome
- Shared experiment learnings across team and agents
- ICE, PIE, RICE scoring frameworks with voting
- Enforced experiment stages with mandatory results and learnings
- MCP server for AI agent read and write access
- Skills that teach agents the methodology
- Plugin for Claude Code and Codex
- Web app for team review and collaboration
- OAuth security with granular permissions
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| What makes it different | - Every answer is cited to its source document—no hallucinations or invented claims
- Delivers finished work products instead of chat transcripts
- Data stays on your infrastructure with full deployment control
- Built for regulated industries with permission-aware design and full audit trails
- Choose and change your LLM independently from the platform
| - Agents cannot bypass the method: tests cannot close without measured results and written learnings
- Enforced workflow prevents confident guesses and invented wins
- Shared memory ensures experiments are never repeated and evidence is preserved
- Agents read and write to the same record as teams under identical rules
- Data stays in EU on Hetzner servers in Finland
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 7 ▲ +1 (up) since last check | 3 ▲ +3 (up) since last check |
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| Trust Flow (Majestic) | 19 | 1 |
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| Citation Flow (Majestic) | 22 | 18 |
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| Referring domains (Majestic) | 82 | 4 |
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OpenParser AI
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