FOR DATA LEADERS
Unlock the speed of AI analytics, without losing sight of a single question, answer, or cost
You shouldn't have to choose between giving people AI on your data and knowing the answers are right. Every answer in Hex draws on context your team controls, and that context improves each time someone asks a question.
Say goodbye to your queue of tickets
Self-serve analytics that actually sticks
Your stakeholders want an answer in whatever window they already have open. They can ask in Slack, inside a published app, or through Claude, ChatGPT, and any MCP-connected system. Calibrate the agent to your business teams need based on preference of cost and depth.
10.6x
growth in data exploration. Every employee gets answers via @Hex in Slack under their own permissions.
Stop answering the same question for the fourth time
The easiest place to build complex analytical flows
When SQL lives in one tool, Python in another, and metric definitions in a doc that's always slightly out of date, consistency is a myth. In Hex, all of it lives in the same notebook so work is reproducible, definitions don't drift, and complex analyses don't disappear onto someone's laptop.
$60K
Looker contract eliminated
$170K
Omni migration avoided
"Product managers and data scientists now co-create inside the same Hex notebook – sketching ideas, refining metrics, and seeing results in real time.”
Blank G. Data Team at Ramp
Skip the upfront modeling project
Start with the context you already have
Hex reads what you've already written: table descriptions in your warehouse, dbt models, docs in Notion, rules in your repos. Endorse the tables your team trusts and monitor the answers the agents produce, that way you know where to build more guardrails and models.
"Context Studio changed how we manage agent performance. It surfaces gaps, proposes fixes, and suggests exactly where to add context. The agent improves without me auditing every conversation.”
Emily Hawkins Head of Analytics Engineering at Ramp
Context is not a constant
Make sure your context keeps pace with the business
Hex monitors it's own answers and provides Suggestions for fixes that would help improve answers the most. Then check the agents work by running Evals to test context and configuration changes.
"We constantly ship new products and features so our context is never stagnant. Even when we launch a new data domain for the first time, it's already stale the next day. Hex’s Context Studio and Evals give us the visibility needed to manage our context at scale.”
Jordan Farrer Director of Data Science at Ramp
What is AI already telling your stakeholders about your data?
Govern every question, answer, and dollar spent
In Hex you can see the question, the answer, which model it used, which tables it used and which metric definitions. When an answer comes back wrong or out of budget, you can trace it back to the root cause and make sure the same mistake doesn’t happen twice.
"Hex is where we go to understand the deep nuances of what's happening — and then act on them before anyone else sees it coming.”
Joshua Hanson Data Team Manager at Ramp
Give every team answers on your terms
FAQ
No. Business users typically ask questions in Threads, Slack, or published apps without opening a notebook. Notebooks are where your data team builds and governs the analyses those experiences draw on.
Yes. Threads and published apps let stakeholders explore in plain language while permissions and semantic context stay enforced.
Many teams replace legacy BI for self-serve and operational reporting while keeping the warehouse and dbt models they already trust. Hex consolidates exploration, apps, and AI on top of that stack.
Teams often connect a warehouse and publish a first app in days, then migrate high-traffic dashboards incrementally. There is no separate server to provision.
No. Hex starts from warehouse metadata, dbt, docs, and curated context you already have, then improves as you endorse tables and refine guardrails in Context Studio.
No. Answers respect the same warehouse and workspace permissions as the person asking. AI cannot bypass row- or object-level access controls.
Published apps, Threads, and agents inherit permissions, endorsed datasets, and audit trails so self-serve stays within policies you define.
Answers combine live queries with endorsed context, metric definitions, and feedback loops from Context Studio and Evals.
Give stakeholders governed self-serve in Slack and apps, while analysts build reusable logic once in notebooks instead of re-answering the same ticket.
Can't find your answer here? Get in touch.