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VS Code extension letting developers chat with their own custom OpenAI assistants without leaving the editor.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
Satellite data analytics provider turning imagery into AI-driven insights for agriculture, forestry and infrastructure.
Research participant marketplace that gives AI teams and academics fast access to verified, screened human data and feedback.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦in-editor chat with OpenAI assistants
- ✦workspace source-code context sharing
- ✦support for custom, user-defined assistants
- ✦secure management of the user's OpenAI account
- ✦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
- ✦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
- ✦LandViewer imagery search and analysis
- ✦Crop Monitoring for precision agriculture
- ✦EOS RayVision analytical reports
- ✦Crop classification and yield prediction
- ✦Infrastructure and change monitoring
- ✦Deforestation and damage mapping
- ✦EOSDA API and 20+ satellite data sources
- ✦300,000+ verified, screened participants
- ✦300+ audience targeting filters
- ✦Representative and quota-based sampling
- ✦API and no-code survey tool integrations
- ✦AI-powered participant quality monitoring (Protocol)
- ✦Managed services with dedicated project teams
- ✦Access to vetted domain experts
- →getting coding help without switching out of VS Code
- →using a personalized OpenAI assistant tuned to a project
- →quick in-editor Q&A while writing code
- →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
- →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
- →Monitoring crop health and predicting yields
- →Tracking infrastructure and construction
- →Disaster damage and deforestation mapping
- →Maritime and border surveillance
- →Collecting human preference data for RLHF or model evaluation
- →Running academic behavioral or market research studies
- →Sourcing domain-expert data for specialized AI benchmarks