| What it does | From Requirements to Code. Verified.
| Small model. Big decisions.
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| Stage | Not given
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| Founded | Not given
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| Based in | CY
| CA
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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/
| Test plan: 125 million free input tokens per month with test_sk keys. Production plan: $0.04 per million input tokens with prod_sk keys (no charge for output tokens). Minimum credit bundle of $10 to unlock production access.
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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
| - Classification with score distribution and confidence
- Text and image extraction
- Yes/no decisions with probability
- Entity recognition and extraction
- Field verification against source
- Multi-level classification (classify-tree)
- OpenAI SDK compatibility
- Sentiment or tone rating
- Question answering with source spans
- SDK support for TypeScript and Python
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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
| - Optimized for bounded decisions with millisecond latency, avoiding slow token-by-token generation
- Extremely cost-effective at $0.04 per million input tokens with no output token charges
- 125 million free test tokens monthly with no card required
- Production-ready with REST API, SDKs, and CLI interfaces
- Structured responses enable direct application logic without additional parsing
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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 | 18 ● no change since last check |
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| Trust Flow (Majestic) | 18 | 28 |
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| Citation Flow (Majestic) | 34 | 31 |
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| Referring domains (Majestic) | 68 | 42 |
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Reqode
milliseconds.ai