| What it does | From Requirements to Code. Verified.
| Shared project context for AI coding agents
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| Stage | Not given
| Startup
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| Founded | Not given
| 2024
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| Based in | CY
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| Pricing model | Not given
| Freemium
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| Pricing | Startup: Free for up to 3 users and 3 projects. Cloud Starter: $9 per user/month with unlimited users and projects. Cloud Pro: $19 per user/month with unlimited users, projects, 1,000 included AI credits per licensed user per month, and priority support. Self-hosted: Starting at $3,000 per instance/
| Starter: Free with 10,000 credits every month, 1 user, up to 15 projects. Pro: $19/month with 25,000 credits every month, 1 user, unlimited projects. Elite: $49/month with 100,000 credits every month, 1 user, unlimited projects. Team: $79/user/month with 200,000 credits per seat pooled, 3+ users, $2
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| Key features | - Specification Management: Manage connected requirements, data entities, APIs, interfaces, wireframes, and test cases in a versioned product model with traceable relations and branch-aware revisions
- Change Management: Define each product change through a Change Request that connects goal, affected specifications, project branch, implementation impact, and linked issue
- Architecture & Software Units Blueprints: Define subsystem architecture and software unit blueprints with implementation rules, responsibilities, dependencies, and file boundaries linked to product sp
- AI Assistants: AI Analyst, AI Test Designer, AI Architect, and AI Product Expert for refining specifications, designing tests, developing architecture, and reviewing implementation
- MCP for AI Coding Agents: Give coding agents branch-aware specifications, architecture guidance, software units, file traces, and Change Request context through MCP
- Specification and Code Alignment Verification: Check that code matches specifications and follows architecture rules as the system evolves
- Test Management: Organize test cases, test runs, execution, and result history
- MCP for QA Agents: Give QA agents prepared test runs, cases, steps, and expected outcomes through MCP to record execution results
| - Hosted code search with indexing and dependency graphs
- Save and retrieve project decisions with reasoning
- Record lessons from past work to guide future tasks
- Plans, runbooks, and handoffs for agent coordination
- MCP integration with Cursor, Claude Code, Codex, Grok
- Change impact analysis and code health metrics
- Team collaboration with shared workspaces
- Privacy controls and access permissions
- ContextCode CLI and VS Code extension
- Knowledge Atlas to explore code and project connections
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| What makes it different | - Preserves product context across tasks, agents, and code changes through a structured, verified product model
- Reduces handoffs and coordination by delegating whole features with connected specifications and implementation scope
- Prevents architecture drift by connecting implementation with subsystem architecture rules, unit guidelines, and component responsibilities
- Built for complex products where a single feature touches connected data, APIs, interfaces, and business rules across multiple repositories and systems
- Keeps product model current as specifications and implementation change using AI assistance and team review
| - Switch agents without re-explaining the project
- Decisions and lessons carry over across sessions and tools
- Full-featured free plan with 10,000 monthly credits
- High code recall (99.38%) and memory accuracy (91.4%)
- Evidence-based answers with source attribution
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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) | 28 ● no change since last check | 29 ● no change since last check |
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| Trust Flow (Majestic) | 18 | 5 |
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| Citation Flow (Majestic) | 34 | 36 |
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| Referring domains (Majestic) | 68 | 109 |
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Reqode
ContextStream