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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.
Interactive online platform for learning data science and AI skills.
AI coding platform and IDE that orchestrates multiple agent sessions and lets teams plug in their own AI subscriptions.
No-code AI platform that builds full-stack apps, websites and agents from plain-language prompts with hosting built in.
No public pricing
Free trial available
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
- ✦Interactive courses and coding challenges
- ✦Skill and career tracks
- ✦DataCamp Workspace for data analysis
- ✦Skill assessments
- ✦Certifications
- ✦AI coding IDE with agent orchestration
- ✦Run and manage multiple agent sessions
- ✦Task, artifact and collaboration tools
- ✦Bring-your-own AI subscription or API keys
- ✦Cloud-scale agent execution
- ✦Prompt-to-app full-stack generation
- ✦Built-in backend, database and auth
- ✦One-click integrations (Slack, Notion, HubSpot, etc.)
- ✦Instant hosting and custom domains
- ✦Superagents for automated workflows
- ✦GitHub sync and code export
- →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
- →Learning Python, R, SQL, Power BI, and Tableau
- →Upskilling in data analysis, data engineering, and machine learning
- →Preparing for data science and analytics careers
- →Team training for data literacy and AI skills
- →Shipping code faster with AI agents
- →Coordinating agent work across a team
- →Managing tasks and artifacts in one place
- →Running many parallel agent sessions
- →Building internal tools and dashboards
- →Launching websites and landing pages
- →Creating customer portals and CRMs
- →Deploying AI agents that automate tasks