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Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Connects Git repos to answer plain-English questions about your code with file references and dependency context.
Full-stack observability platform with an AI SRE agent that detects, debugs, and auto-fixes issues across infra, apps, and users.
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
Open-source asset-based data orchestrator, with Dagster+ cloud, for building, observing and delivering reliable data and AI pipelines.
No public pricing
No public pricing
Free trial available
Free trial available
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦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
- ✦Infrastructure and application performance monitoring
- ✦Log monitoring with AI insights
- ✦Real user monitoring
- ✦OpsAI SRE agent for detection and auto-fix
- ✦Synthetic and browser testing
- ✦LLM observability
- ✦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
- ✦Asset-based pipeline orchestration
- ✦Built-in lineage and data-quality checks
- ✦Data catalog with asset metadata
- ✦Native dbt, Snowflake and Fivetran integrations
- ✦Branch deployments and hybrid deployment
- ✦Open-source core plus managed Dagster+ cloud
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Monitor full-stack app and infra health
- →Debug incidents faster with AI
- →Correlate frontend and backend issues
- →Observe Kubernetes and cloud environments
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
- →Orchestrate ETL/ELT and dbt pipelines
- →Monitor data health and lineage
- →Build AI/ML data pipelines
- →Run reliable, observable data platforms