Compare tools
Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
⇄ Comparison dimension — pick the market you're actually shopping in
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Cody
✓ verifiedPaid
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
245K visits/mo
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Gemini Code Assist
✓ verifiedFreemium
Google's AI coding assistant for code completion, generation, chat and review across IDEs and GitHub.
559K visits/mo
✕
Jam
✓ verifiedFreemium
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
730K visits/mo2.9K saves
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Katalon Studio
✓ verifiedFree trial
Test-automation platform for web, API, mobile, and desktop with no-code to full-code authoring and cloud execution.
246K visits/mo2.1K saves
Pricing
Enterprise: starting at $16K (includes AI feature credits, scales with team size)
No public pricing
Free: $0 (30 Jams/mo, 5 recording links)
Team: $14/creator per month billed yearly (unlimited Jams)
Free trial available
No public pricing
Free trial available
Core features
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦AI code completion and suggestions
- ✦Natural-language code generation
- ✦In-IDE chat assistance
- ✦AI code review
- ✦IDE integrations (VS Code, JetBrains, etc.)
- ✦GitHub integration
- ✦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
- ✦No-code, low-code and full-code test authoring
- ✦Web, API, mobile and desktop testing
- ✦Test management and planning
- ✦Cloud-based test execution
- ✦Reporting and analytics
- ✦AI-assisted test generation and monitoring
Use cases
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →Speeding up coding with AI completions
- →Generating code from plain-language prompts
- →Getting in-editor help and explanations
- →Reviewing pull requests with AI
- →Understanding unfamiliar codebases
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
- →Automate regression testing
- →Unify API, web and mobile tests
- →Manage manual and automated tests together
- →Scale test execution in the cloud
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