Product updates

We've reorganized the left nav to surface what matters most. Metrics and Entities now sit at the top level, above Teams, so you can quickly access your most-used data. Collapse these sections to keep your nav compact, or expand them to see all your metrics and entities at a glance. A new Favorites section at the bottom lets you pin any metric, report, or entity for one-click access.

Customize your visualizations

Rolling calendar periods: Set visualizations and report filters to track current periods, which will update automatically as each new period begins. We've also added the last completed periods (last week, month, quarter, year) for snapshots of finished periods.

To date comparisons: A single click now lets you align comparisons to matching points in time. In the options from any visualization(charts, tables, big numbers and widgets), you can choose whether the comparison period should be the full period or to date. This is availiable for metrics with a daily time grain.

Table period-over period comparisons Period-over-period comparisons are now also available in report tables.

Steep lets your whole organization work from the same trusted metrics and semantic model defined by your data team. The Steep MCP extends that power beyond Steep, into the AI tools and agents you already use every day.

Your data, where you work

Connect any MCP-compatible client to your Steep workspace and query your metrics directly from Claude, Cursor, Codex, VS Code, and more. Browse the metric catalog, query metric and target data, and explore your workspace without switching context.

Governed by default

Every query runs through the same semantic layer and permissions model that powers Steep. Members connect with their own Steep credentials via OAuth, so the AI sees exactly what the member is allowed to see, nothing more. Your data team stays in control. Also works with row-level security.

Getting started

The Steep MCP server is hosted at https://mcp.steep.app/mcp. Authentication is handled through OAuth, and your agent will only see data you have access to in Steep.

Learn more →

Row-level security (RLS) lets workspace admins control which rows of data each member can see.

Define who sees what

Admins can now set access policies directly on any module in Steep's semantic model. A policy filters the data a member sees based on their identity, so an account manager only sees data for their own accounts, or a regional lead only sees data for their market. The policy applies automatically across every metric, entity, and report built on that module.

User-level and custom attribute access

Policies can be set based on individual user email or custom attributes. Define a table mapping each member's email to their attributes, then set policies to filter by those attributes. Policies work with any dimension in your data, whether that's market, region, manager email, or any custom attribute.

Always consistent, always filtered

Once a policy is in place, members always see filtered data, whether they're exploring a metric, viewing a report, or using Steep AI. Members are informed when they're seeing a filtered view. Admins always see everything.

Availability

Row-level security is available on Enterprise plans.

Learn how to get started →

The shift to AI analytics

For years, getting data into the hands of the business has been a challenge for data teams. But in the AI era, access alone isn’t enough. Teams need the speed, flexibility, and depth of AI, but in an environment that stays trusted and grounded in the right business context.

Steep AI solves that problem.

Real analysis, not just answers

Built on top of your semantic model, the Steep agent gives teams a fast, powerful way to do analysis in natural language. It can connect metrics and dimensions, compare segments and time periods, and return clear answers grounded in the business logic your data team has defined.

• Ask complex questions in plain language and refine the answers in the same conversation.

• Explore your catalog using all metadata and descriptions available.

• Get deep analysis using the full context of your semantic model, with the Steep agent combining multiple metrics and breakdowns for real insights.

Read the full blog post →

Start using Steep AI →

With the Steep API, teams can access the metrics and semantic model defined in Steep and use them anywhere, while governance remains centralized. Complete consistency without the lock-in.

Unlock a whole new set of automation and integration use cases for analytics teams, whether you’re driving internal workflows, notebooks, or powering AI experiences with your metrics.

API for metadata and queries

This release focuses on the semantic model metadata and metric queries, providing the core building blocks for secure, read-only access to Steep’s semantic layer from other systems.

What’s included:

• Metadata endpoints to list metrics, entities, modules, members, and teams.
• Metric query endpoint that uses Steep’s query engine to compute and deliver aggregated metric data.

What this unlocks

Steep’s API opens up new possibilities for your analytics, without re-implementing definitions or logic.

• Build anywhere: Bring Steep’s metrics into your internal tools, notebooks or other systems.
• Introduce metrics to AI: Power LLMs, agents, and custom AI use cases with your trusted, governed metrics.
• Get creative: Build custom use cases built on top of Steep’s semantic model.

Explore the API documentation and references to get started:

https://help.steep.app/api