Every data team knows the feeling. You build the dashboard, the semantic layer, the governance model. Then a business user downloads the data to Excel anyway, or pastes it into a chatbot, because the platform can't get them to the last step: taking action.
That gap between insight and action was the focus of our recent launch webinar for Incorta Builder and Incorta Intelligence. Mark, our Head of Product Marketing, hosted the session with Ashwin, VP of Product, and Anurag, VP of Product Management, walking through the new capabilities and running live demos of what business users can build without writing a line of SQL. The full session is available on demand if you want to watch it end to end. Here's a recap of what shipped and why it matters.
The problem: three friction points slowing every team down
Mark opened with three patterns that show up at nearly every company:
Insight doesn't lead to action. Dashboards and BI tools surface what's happening, but taking action still means jumping to another system. Now that gap includes chatbots. Teams pull data out of governed platforms and drop it into AI tools with little to no oversight, and adoption stalls.
Innovation sits in a queue. Either IT can't build custom apps fast enough, or the business ends up with a sprawl of small SaaS tools, each doing one thing, none of them talking to each other.
The cost adds up. Mark cited research showing over 60% of workers' time goes to work about the work: prepping data, hunting for access, merging systems. 74% of companies can't scale AI because of governance gaps. Six in ten IT teams have app backlogs they can't clear, and large enterprises are sitting on an average of $18 million in excess SaaS spend a year.
The fix isn't another point solution. It's giving business users a way to build what they need on top of data that's already governed, so nothing new has to be reinvented or re-secured.
What's new: Incorta Intelligence and the Builder toolkit
Ashwin introduced the next layer of the platform. What used to be called Nexus is now Incorta Intelligence, and it's built on the same data foundation Incorta customers already have: the pipelines, the semantic layer, the direct data mapping that turns a 40-table star schema into one clean business view an AI model can actually query.
On top of that foundation sit three pillars:
- AI Applications, built with a chat interface and low-code tooling so business users can describe an app and get a working one.
- Data Studio 2.0, a set of low-code analytical flows (covered in more depth in a future webinar).
- Business notebooks and workflow orchestration, including deterministic and agentic workflows for write-backs and reverse ETL.
All of it runs on the Smart Agent, which is where the actual query generation and reasoning happen.
Why the Smart Agent beats downloading to Claude or Gemini
A fair question came up during the session: why not just export data and hand it to a frontier model? Ashwin walked through what he called the hidden AI tax.
Frontier models are powerful, but they don't know your data. Every complex question means re-explaining the schema, re-joining tables, and re-running the same expensive query someone already ran last week. Incorta's Smart Agent works differently because it sits on top of a data foundation that's already curated: pre-built business views, established relationships across tables, dashboards and queries you've already written that can be reused instead of rebuilt from scratch.
Add response caching, query caching, and business context you can enrich directly in Incorta's data catalog, and the cost difference compared to raw frontier-model usage is significant, without giving up governance or row-level security.
From chat to dashboard to live app
The bulk of the webinar was live demos, and they followed a clear progression: ask a question, get a report, turn that report into something interactive.
HTML dashboards, built from a prompt. Anurag showed four examples: a monthly financial close summary, a quarterly business review, an annual board and investor report, and a product launch analysis (using Incorta's synthetic Apple dataset to track how iPhone 17 performed against iPhone 16). Each one started as a plain-language prompt and came back as a polished, interactive HTML report in a few minutes, no dashboard design or SQL required.
Static reports turned into live apps. A monthly report is only useful for that month. Anurag showed how the same dashboard can be redeployed as a live Incorta app, with filters that run real queries against live data instead of a snapshot.
A gallery for managing every dashboard you've created. If you're generating dozens of these reports a month, you need somewhere to find them again. Anurag built a simple app, in under half an hour, that lets users upload, tag, search, and organize every HTML dashboard by category, all inside Incorta's existing governance model.
A forecast and planning app with real write-back. This was the demo that showed what "action" actually looks like. Users could review a 12-month revenue trend, generate a forecast, then plan by product and region directly in an Excel-like grid, adjusting units and revenue by month. Saving the plan writes to a Postgres database that syncs back to Incorta immediately, and the same write-back pattern extends to ERPs or systems like Workday Adaptive Planning through REST API or JDBC.
An internal resourcing app, built entirely on a custom schema inside Incorta, to track consultant utilization and flag overallocation in real time.
Claude generating an app through Incorta's MCP server. The last demo tied it together: Anurag prompted Claude to build a sales comparison dashboard using an Incorta business view, then asked Claude to convert it into a full AI app with product and country dropdowns. The Smart Agent, running inside Claude through Incorta's MCP server, generated the SQL. Anurag deployed the new version, tested it, and published it, all without leaving the Incorta environment.
Governance doesn't get left behind
A question from the audience got at something worth calling out directly: does row-level security carry over to these new AI apps, or is it a separate mechanism?
Ashwin's answer was straightforward. It's the same underlying security model used for dashboards today, the same user predicates, the same session variables. Anything built with the Smart Agent or Incorta Builder inherits that governance from the start. Nothing new to configure, nothing new to audit.
What's next and when you can get it
Smart Agent capabilities are live in Incorta's current release. AI Apps are on track for general availability by the end of July, with early access open now for customers who want in ahead of GA.
Also on the roadmap: tighter native support for layout.dev alongside the existing Streamlit and Python options, giving developers another path to build richer last-mile visualizations inside Incorta apps.
Watch the full session
This recap covers the highlights, but the demos are worth watching in full, especially the live app-building sequence with Claude and the forecast and planning walkthrough.
The webinar recording is available on demand, and if you want early access to AI Apps or a personalized demo, reach out to the Incorta team directly.
