| What it does | Autonomous AI coding agent with deterministic program repair
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| Stage | Not given
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| Founded | Not given
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| Based in | ID
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| Pricing model | Freemium
| Paid
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| Pricing | Core Basic: free (20 CLI / 15 Web runs per day, 50K daily AST tokens). Apex Pro: $11/month (100 CLI / 75 Web runs per day, 250K daily AST tokens). Sovereign Ultra: $44/month (400 CLI / 300 Web runs per day, 1.0M daily AST tokens). Annual subscriptions include 2 months free.
| $20 free credit to start. Per-review pricing: $0.20 per initial review when a PR opens (includes up to 1,000 lines changed), $0.08 per re-review on each update. Reviews over 1,000 lines cost an additional $0.30.
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| Key features | - 4.1µs C-ABI latency native Rust Sub-Cortex execution
- Zero dirty diffs with strict AST grammar validation and dry-run verification
- Support for 6 production languages: Python, Rust, TypeScript/JavaScript, Go, C/C++, and Java
- Polyglot language engines with direct Tree-sitter CST surgery
- Machine-to-Machine sub-cortex infrastructure for autonomous agents
- Zero Code Retention policy with ephemeral in-memory processing
- 91.3% AST token pruning for repository context efficiency
- Multi-file repository context with automated test-runner verification
- Automated 5-Whys Root Cause Analysis and SRE incident diagnostics
- System-wide dependency mapping and security audit capabilities
| - Reviews complete in about 30 seconds
- Automatic review on every pull request including drafts
- Single organization install with no per-user setup required
- Fresh review comment posted on each push with previous reviews collapsed
- Flags merge risks such as bugs, broken contracts, and security holes
- Private repository code not used to train foundation models
- Pay-per-review pricing model with no seat-based licensing
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| What makes it different | - Eliminates 95% of LLM token overhead through deterministic compiler verification instead of probabilistic inference loops
- Operates locally with strict Zero Code Retention policy—no code logging, storage, or model training usage
- Sub-microsecond repairs in CPU L1 cache without garbage collection pauses via native Rust FFI
- Engineered as M2M sub-cortex infrastructure for autonomous agents, not consumer chatbot utility
| - Independent review from a separate model, not the same session that wrote the code
- Consistent six-point checklist on every PR prevents wandering reviews
- Dramatically faster cost model than seat-based tools
- Single install for entire organization with no friction
- Keeps review time off the critical path of the software factory
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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) | Not checked yet ● no change since last check | Not checked yet ● no change since last check |
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| Trust Flow (Majestic) | 0 | 0 |
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| Citation Flow (Majestic) | 15 | 12 |
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| Referring domains (Majestic) | 2 | 1 |
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Kronumos
Pacecar