How Sigma’s AI Apps Are Changing Modern BI

…and how we leverage them at Maverick Data

AI Apps are one of the biggest reasons that Maverick Data is all in on the Sigma platform. Not because AI is trendy, or because “AI-powered” sounds good in a sales pitch, but because Sigma is one of the first analytics platforms where AI actually fits naturally into how organizations already work with data.

Most companies don’t need more dashboards – in fact, we’d argue that most companies need fewer dashboards. What they need instead is a platform that is capable of integrating governed & curated CDW data with business processes and LLMs with minimal effort.

This blog post will talk about the nature of AI Apps in Sigma, real-life use cases for AI Apps, and how we use AI Apps internally at Maverick Data.

What are AI Apps in Sigma?

From a practical perspective, AI Apps allow organizations to combine visualizations from traditional BI, data inputs from users written back to a well curated and governed CDW, and modern LLMs. Philosophically, AI Apps fundamentally change the way that users interact with data from static consumption of data to dynamic consumption of data.

No longer is BI a one way street – instead, users are now able to not just control what data is being shown on the screen, they are able to control what data is being stored via Sigma’s write-back capability.

Sigma’s AI integrations allow for this data – both CDW + user input – to be analyzed with the underlying CDW’s LLMs. This is the essence of a modern BI platform – one built with a company’s AI roadmap in mind.

Traditional BI Methodology

Traditional – or “legacy” – BI follows a fairly rigid, one-directional flow. Business processes generate data, that data gets extracted and modeled in a data warehouse, and dashboards are then built on top for users to consume. The role of the end user stops at viewing, filtering, and exporting. The end products are being consumed via a cloud platform, while decisions and actions live somewhere else—usually in emails, spreadsheets, or downstream tools that sit completely outside the analytics platform.

This model works well for answering questions about what happened, but it does not allow users to tell the BI tool what is happening now. As a result, critical information lives outside the warehouse, disconnected from the data that informed it. Over time, BI turns into a read-only system of record—useful, but removed from the day-to-day flow of how work actually gets done.

The New AI App Methodology

AI Apps shift the traditional BI model by turning analytics into a two-way consumption methodology instead of a one-way output.

Rather than just creating dashboards, Sigma allows business users to create a platform to leverage their data. Sigma’s write-back allows the warehouse to no longer just store historical data; it also captures human context and decision-making as it happens.

Once both system-generated data and user-provided inputs live together in the CDW, they become available for AI analysis. Sigma’s AI integrations—whether through the underlying warehouse (like Snowflake Cortex) or Sigma’s own AI features—can then analyze the full picture: structured data, operational inputs, and real-time context. The output isn’t stuck in a chat window or a disconnected third-party tool. It’s written back to that same governed, auditable, and reusable CDW.

This is the core of the AI App methodology: analytics that operate as part of your data platform and not just another data tool.

AI App Possibilities

When talking about AI Apps, the conversation should not start with AI models or automation—it should start with friction.

Most organizations already know where things feel slow, manual, or disconnected. AI Apps resonate when they are positioned as a way to remove that friction by bringing data, decisions, and action into a single, governed platform—rather than adding yet another tool to the stack.

Below are the most common use cases where AI Apps tend to land with our clients.

Excel & Spreadsheet Processes

Many operational processes still live in Excel: planning, approvals, commentary, tracking, and ad hoc analysis. These spreadsheets are often emailed around, copied, renamed, and manually reconciled—creating version control issues and data quality risk.

AI Apps replace these spreadsheets with shared, warehouse-backed workflows. Users still get a familiar, spreadsheet-like interface, but inputs are written directly to governed tables in the CDW, making the data immediately available for reporting, auditing, and downstream analysis.

Third-Party Tools & Apps

A lot of companies run critical business processes in third-party applications—time entry, invoicing, expense reporting, approvals, and other “operational admin” workflows. The problem isn’t that these tools don’t work. It’s that they often become yet another system to manage, and they almost always create another gap between where work happens and where data lives.

AI Apps (and Data Apps more broadly) give you a different path: Sigma can replicate much of this functionality directly in the analytics layer using write-back and actions. The biggest unlock is what happens next—once those workflows live in Sigma, the data they generate is captured directly in your CDW, which can eliminate the need to ETL operational data back into the warehouse later.

Workflow Use Cases

Insight without action means you’re not realizing all of your data’s value. Any business process that involves workflow—approvals, handoffs, commentary, updates, or follow-ups—can be replicated using AI Apps in Sigma.

Because of Sigma’s web-native design, embedding Sigma into internal portals or operational tools is straightforward. When combined with write-back and actions, Sigma moves beyond analytics and becomes a lightweight workflow management layer. Users can review data, add context, take action, and trigger downstream steps without leaving the platform.

Maverick Data’s Internal Use Cases

At Maverick Data, we practice what we preach! We operate almost all aspects of our business using AI Apps in Sigma. Here are several use cases that we’ve implemented to help our business be more streamlined and leverage AI more practically.

Internal Time Entry App

Maverick Data employees track all of their time by inputting their client name, project, hours billed, and notes directly into Sigma. This data is written back to the CDW and serves as the single source of truth for both internal reporting and invoicing.

Invoices are generated directly in Sigma using this data, eliminating duplicate systems and manual reconciliation between tools.

Financial Forecasting & Planning

Transactional data from our online banking system is combined with time entry data in our CDW to support financial reporting and forecasting in Sigma.

This allows us to view historical performance alongside forward-looking forecasts in a single environment. Assumptions, adjustments, and planning inputs are captured through Sigma input tables, keeping forecasting logic transparent, auditable, and easy to update.

Weekly Client Status Reports

Data from project input tables and invoicing data from our time entry app are combined with LLM-generated summaries of time entry notes. These summaries are created directly in Sigma and included in our weekly client-facing status reports.

The result is a repeatable, structured status reporting process that reduces manual effort while improving consistency and clarity for our clients.

Sales Pipeline Management

Maverick Data sales opportunities are entered and updated directly in Sigma, where we can also view pipeline reporting, deal summaries, and recent engagement notes. These notes are captured from our AI meeting note taker and surfaced alongside deal data to provide context without leaving the platform.

This gives us a real-time, consolidated view of our sales pipeline without relying on disconnected tools.

Wrap-Up

AI Apps aren’t about turning BI into an AI experiment. They’re about fixing the long-standing gap between data, decisions, and action. At Maverick Data, AI Apps aren’t a future concept—we use them every day to run our business more efficiently, reduce tool sprawl, and make real-time decisions. The same patterns apply to our clients, regardless of size or industry.

Modern BI isn’t about building better dashboards. It’s about leveraging platforms that help people do their jobs better. AI Apps in Sigma are one of the clearest steps in that direction.

Contact Us

If you would like to talk to someone at Maverick Data about maximizing your usage of the Sigma platform, please email us at spencer@maverickdata.io for more information!