Your analytics agents are out in the field. Are they equipped for the mission?
AI is changing how data work gets done. We're already seeing this with Threads and Notebook Agent — delivering answers to end users faster than a queue ever could.
But which answer? Is it useful? Does the agent have the right context, or did it hallucinate a response? Trust has been the fundamental barrier for AI in analytics. It's tricky, and there hasn't been a real solution — until now.
Today, Hex is introducing Context Studio. It helps data teams deploy analytics agents they can trust — with full visibility into what's working, what's not, and how to improve.
Join us today, January 28th @ 1pm PST, for a live launch event and see Context Studio in action.
Observe what questions are being asked
You can't improve what you can't see. AI analytics can deliver answers to all sorts of business users’ questions, but how do you know what’s being asked and step in when needed?
Context Studio gives data teams full visibility into how agents are actually being used across their organization — from Slack and MCP to the Notebook Agent and Threads.
The dashboard shows what matters most:
Understand adoption with conversation volume and trends across all agents
Identify patterns by filtering on agent type, workspace role, and time range
See what users care about through AI-extracted topics showing which business questions drive engagement
Spot problems proactively with AI-generated warnings flagging potential confusion before users lose trust
Admins can drill from high-level trends into specific conversations using the Thread inspector, turning signals into trusted answers.
Diagnose agent confusion
Observability alone isn't enough — you need to understand why something went wrong. The Thread inspector shows you exactly what happened: a summary of the request and response, specific topics extracted from the conversation, which data sources were referenced, and warnings flagging potential confusion.
Inside the inspector, you’ll see specific improvement suggestions: topics that need definition, instructions that need clarification, or data sources that should be endorsed.
This removes the guesswork from diagnosis. We ’ve seen this be the most challenging step for teams newly working with agents. Instead of debating what might help, teams see exactly what needs to change based on real user behavior.
Curate context at every layer
The other challenge, context isn't one thing. It's endorsements that control data access, semantic models that define metrics, and unstructured guides that capture business logic. Data teams need to manage it all in one place — not scattered across wikis, text files, and configuration tools.
Context Studio lets you traverse each layer of context:
Endorsements guardrail which assets the agent can access, ensuring only trusted sources get used.
Semantic models define metrics with deterministic SQL generation, giving agents reliable definitions they can trust. Our modeling agent helps you build these with AI, accelerating the setup process.
Workspace guides are a library of context organized across multiple documents. Instead of overloading the prompt, the agent retrieves only what's relevant for each question, keeping responses sharp.
Each type serves a different purpose and is retrieved when the agent needs it. Giving data teams flexibility across different context tools means they can move fast — applying tight guardrails where accuracy is critical and flexible retrieval where exploration makes sense.
Test context changes and deploy with confidence
Agent behavior is non-deterministic. You need to test context changes before they go live, not hope they work in production. Once Hex provides a recommendation, you can test it with our purpose-built workbench.
The context workbench lets you:
Stage changes to workspace guides and semantic models
Test how Threads will respond using the preview panel
Publish updates with full version control and change history
If you're fixing the agent's response to a specific topic, you make the change, verify the improvement in preview, and deploy, knowing it won't regress existing behavior. Attribution logs track who changed what and when, enabling parallel workflows without collision.
The only end-to-end solution
Data teams are being asked to deploy AI agents everywhere — in Slack, in notebooks, across the business. But deployment without visibility is a recipe for eroded trust.
With agents, context needs the same rigor as your warehouse. It can't live scattered across wikis and config files. It needs to be observed, tested, and managed like any other critical system. That's what Context Studio does. Observe how agents perform. Diagnose where they're confused. Curate better context. Deploy improvements safely. All in one place.
AI analytics is an exciting future that unblocks teams and accelerates how they work with data. With Context Studio, it's a future you can actually trust.