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AI-first customer-service helpdesk built around the Fin AI agent, for support teams handling omnichannel conversations.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
Vibe-coding builder creating full-stack apps by chatting with AI.
AI Text2SQL database client that generates and fixes SQL from natural language across 30+ databases, with dashboards.
No public pricing
Free trial available
No public pricing
No public pricing
No public pricing
Free trial available
- ✦Fin AI agent for customer service
- ✦Omnichannel agent inbox
- ✦AI-assisted ticketing
- ✦Copilot agent assistant
- ✦AI conversation insights and scoring
- ✦No-code automations
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Cross-session project memory recalling prior decisions and state
- ✦Autonomous execution of long, multi-step notebook tasks
- ✦Reads cell outputs (plots, tables, metrics), not just code
- ✦In-notebook cell-level assistance and error fixing
- ✦Installs directly into existing JupyterLab via pip, no new editor
- ✦Concept explanations with runnable example cells
- ✦CodeFlying enables full-stack app creation via chat in minutes
- ✦AI Text2SQL query generation
- ✦One-click SQL error fixing
- ✦GUI database management and ER diagrams
- ✦AI data analysis and dashboards
- ✦Support for 30+ databases
- ✦Local data processing for privacy
- →Automating customer support with AI
- →Assisting human agents in real time
- →Routing and resolving tickets
- →Analyzing support quality and trends
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Data scientists running multi-week model iteration projects
- →Domain experts (e.g. risk/fintech) who know the problem but not deep Python
- →Researchers wanting an agent that remembers project context across days
- →Analysts needing help understanding unfamiliar algorithms or libraries
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- →Write SQL from plain language
- →Manage multiple databases in one client
- →Generate BI dashboards from data
- →Migrate and sync schemas/data