Hex
Agentic data notebooks for analytics teams
- Overview
- Hex combines SQL, Python, and AI agents in collaborative data notebooks connected directly to your warehouse. Its Notebook Agent helps analysts write and debug code, while Threads (Team/Enterprise) gives non-technical users a conversational interface to ask questions in plain English. Hex can also build and publish interactive data apps from the same notebook environment.
- Why it matters
- Hex is one of the clearest examples of the notebook-plus-agent pattern displacing standalone BI tools: analysts get a full code environment, while the Threads interface lets non-technical stakeholders query data without opening a ticket. The $70M Series C (May 2025) and rapid agentic feature releases signal continued investment, but the jump from $36 to $75/editor/mo between tiers is steep, and compute costs accrue separately, so total cost of ownership can surprise teams at scale. Watch for consolidation pressure from Databricks and Snowflake, both of which are pushing native notebook and AI-query experiences.
- In practice
- Analytics engineers typically build and maintain notebooks in Hex, then publish them as interactive apps for finance or ops stakeholders — replacing ad-hoc Looker or Mode dashboards. The Threads agent is being used for self-serve queries where a stakeholder asks a question in plain English and gets a chart back without analyst involvement. The main limitation is compute cost unpredictability: heavier data-science workloads (large-model training, big joins) add meaningful variable charges on top of the per-seat subscription.
- Best for
- Data teams that want AI-assisted, agentic analysis in a collaborative notebook with self-serve access for business stakeholders
- Pricing
- Community free (5 notebooks, limited compute); Professional $36/editor/mo (Notebook Agent, unlimited notebooks, 5 published apps); Team $75/editor/mo (Threads agent, Semantic Model agent, unlimited apps, scheduled runs); Enterprise custom. Pay-as-you-go compute billed separately on Team and above.
Key features
- Notebook Agent for AI-assisted SQL, Python, and visualization
- Threads: conversational analytics for non-technical users
- MCP client and Bring Your Own AI Provider support
- Interactive data apps and dashboards built from notebooks
- Version control, scheduling, and direct warehouse connections
Quick answers
- What is Hex?
- Hex combines SQL, Python, and AI agents in collaborative data notebooks connected directly to your warehouse. Its Notebook Agent helps analysts write and debug code, while Threads (Team/Enterprise) gives non-technical users a conversational interface to ask questions in plain English. Hex can also build and publish interactive data apps from the same notebook environment.
- Why does Hex matter?
- Hex is one of the clearest examples of the notebook-plus-agent pattern displacing standalone BI tools: analysts get a full code environment, while the Threads interface lets non-technical stakeholders query data without opening a ticket. The $70M Series C (May 2025) and rapid agentic feature releases signal continued investment, but the jump from $36 to $75/editor/mo between tiers is steep, and compute costs accrue separately, so total cost of ownership can surprise teams at scale. Watch for consolidation pressure from Databricks and Snowflake, both of which are pushing native notebook and AI-query experiences.
- What is Hex best for?
- Data teams that want AI-assisted, agentic analysis in a collaborative notebook with self-serve access for business stakeholders
- How much does Hex cost?
- Community free (5 notebooks, limited compute); Professional $36/editor/mo (Notebook Agent, unlimited notebooks, 5 published apps); Team $75/editor/mo (Threads agent, Semantic Model agent, unlimited apps, scheduled runs); Enterprise custom. Pay-as-you-go compute billed separately on Team and above.
Seen in recent stories
Where Hex showed up in the last 90 days of KeyNews editions.
Know the terms
Glossary entries that explain what Hex is built on.
Agentic workflow
A multi-step process where an AI agent plans, executes, evaluates, and iterates on tasks with minimal human intervention. Unlike single-turn prompts, agentic workflows involve loops, branching logic, and tool calls that unfold over minutes or hours.
LLM (Large Language Model)
A neural network trained on massive text corpora to predict and generate language. LLMs like GPT-4, Claude, and Gemini are the foundation of the current AI wave, powering chatbots, coding tools, and enterprise automation.
MCP (Model Context Protocol)
An open standard (created by Anthropic) that lets AI models connect to external tools, data sources, and services through a unified interface. MCP is becoming the USB-C of AI integrations.
Agent
An AI system that can autonomously plan, use tools, and execute multi-step tasks on behalf of a user. Agents are the next major product paradigm after chatbots, with every major lab shipping agent frameworks.
Models behind it
The models Hex runs on, offers, or competes with.
More data & analytics tools
New tools drop every week.
ONE BRIEFING · EVERY FRIDAY · FREE
Free. Unsubscribe anytime.