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AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
Connects Git repos to answer plain-English questions about your code with file references and dependency context.
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
An AI lab building compact Liquid Foundation Models that run on-device on phones, laptops and cars rather than in the cloud.
AI web-app and API vulnerability scanner with real traffic; solid security tool.
No public pricing
Free trial available
Free trial available
No public pricing
No public pricing
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦Natural-language search across a codebase
- ✦Architecture explanations and dependency graphs
- ✦Bug hunter that traces issues across files
- ✦AI code review before opening a PR
- ✦Automatic documentation generation
- ✦Multi-repo support via OAuth
- ✦One-click bug capture via browser extension
- ✦Automatic repro steps
- ✦Console, network and device logs
- ✦Instant replay of recent activity
- ✦Backend tracing and an AI debugger
- ✦Integrations with Jira, Linear, GitHub and Slack
- ✦Liquid Foundation Models (LFMs) for on-device use
- ✦Variants sized to run on phones, laptops and cars
- ✦Broad runtime support (llama.cpp, MLX, ONNX, CoreML, vLLM)
- ✦On-device reasoning, vision and retrieval models
- ✦Enterprise and embedded deployment partnerships
- ✦DAST for Web Apps and APIs
- ✦Automated Penetration Testing
- ✦AI-Driven Remediation Reports
- ✦Compliance-Ready Security
- ✦Sensitive Data Exposure Detection
- ✦Real-Time Vulnerability Detection
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
- →Run private AI locally on consumer hardware
- →Embed intelligence in cars and edge devices
- →Deploy tool-calling agents without the cloud
- →Identifying vulnerabilities in web applications and APIs
- →Automating penetration testing processes
- →Generating AI-powered remediation reports
- →Ensuring compliance with security standards
- →Detecting sensitive data exposure
- →Securing SaaS growth
- →Simplifying client security for MSSPs
- →Meeting compliance standards for regulated industries