Overview
Hex is a collaborative data workspace built by Hex Technologies, Inc., founded in 2019 by Barry McCardel (CEO), Caitlin Colgrove (CTO), and Glen Takahashi — all former Palantir employees. The platform combines Python, SQL, and R notebooks with a publishing layer for shareable data apps, and has built a comprehensive agentic AI layer on top.
The core product is a browser-based notebook environment where data analysts write code cells and mix in markdown, visualizations, and interactive inputs. What distinguishes Hex is the depth of its AI integration: the Notebook Agent can autonomously generate and edit analysis logic with awareness of warehouse schemas and project history, while Threads provides a natural-language query interface for non-coders. A Fall 2025 launch added several new agent capabilities, including a Generative Apps agent that constructs entire dashboards from a plain-language description.
Hex raised a $70M Series C in May 2025, bringing total funding to over $130M. The platform is used by data teams at companies ranging from Series A startups to large enterprises. AI providers used by Hex operate under zero data retention agreements, so customer data is not fed back into model training — a meaningful differentiator for teams with sensitive data. Pricing is per-editor, with a free Community tier available for individuals and small projects.
Key Benefits
- Contextual AI assistance: Hex Magic and the Notebook Agent have access to live warehouse schemas and existing project code, producing more accurate suggestions than generic code assistants.
- Bridging technical and non-technical users: Threads allows analysts to publish a single project that stakeholders can query conversationally, reducing ad hoc data requests.
- Integrated app publishing: Notebooks convert directly into interactive data apps without a separate tool, shortening the path from analysis to decision-maker.
- Data privacy by default: Zero data retention agreements with AI providers are in place by default, not just as an enterprise add-on.
Use Cases
- Exploratory data analysis — Data analysts use SQL and Python cells alongside the Notebook Agent to investigate datasets, iterate quickly, and document findings in one place.
- Self-serve analytics for business teams — Analysts publish data apps or expose Threads so finance, marketing, or operations staff can answer their own questions without filing tickets.
- Automated reporting — Scheduled notebook runs and alert triggers replace manual report preparation and notify stakeholders when key metrics cross thresholds.
- Semantic model development — The Modeling Agent assists data engineers in building and maintaining governed semantic layers that downstream consumers can query safely.