You’re in a meeting and the VP of Sales asks why conversion rates dropped last week. Marketing blames lagging campaigns. Product suspects a broken feature. Data Engineering promises a dashboard update by Friday. Based on the last project, you know you’d be lucky to have the update by the end of the quarter.
But the truth is no one in the room really knows because the data is scattered across systems, delayed by complex ETL pipelines and trapped in yesterday’s reports.
That’s where data intelligence comes in. Not just storing data, — but turning it into instant, usable insight that drives confident decisions.
What is data intelligence?
Data intelligence is the ability to analyze, contextualize and act on the data flowing through your business in real time. It goes beyond storage and reporting. It means understanding what’s happening right now, not just what happened last quarter.
A true data intelligence platform needs to do more than query a warehouse; it must pull together siloed systems, remove latency between ingestion and insight and deliver accurate, real-time answers based on your actual business data.
If generative AI is a storyteller, data intelligence is a truth-teller.
Implementing data intelligence in your gen AI stack
To bring data intelligence into your generative AI stack, you need to bridge the gap between data at rest and data in motion. Here’s how:
1. Connect to more than just the data warehouse
Data warehouses are great for long-term storage and reporting. But data intelligence means going further:
Query operational systems like your order management system (to check if an item has shipped), your payment processor (to see if a transaction has cleared) or your user activity logs (to understand what a customer clicked on before contacting support).
Stream real-time data like location updates from delivery trucks, telemetry from IoT sensors in a factory or application events like “user added to cart” or “login failed.” These streams give your AI context as it happens.
Join structured and unstructured data including customer support tickets (free-text notes and summaries), product manuals (PDFs used to answer support questions), CRM records (names, companies, purchase history) and vector embeddings of past customer conversations. This mix of formats gives your AI richer material to work with and better grounding in the specifics of your business.
Gen AI tools need context. The more connected your platform is to live, real-world signals, the more accurate and helpful your outputs will be.
2. Unify transactions and analytics
Most companies separate transactional systems (used to run the business) from analytical ones (used to understand the business). This split leads to delays, duplication and blind spots.
A modern data intelligence platform like SingleStore eliminates this divide by:
Running transactional and analytical queries in the same engine
Allowing AI agents to read from and write to live data
Supporting high-concurrency, low-latency workloads without moving or transforming data
This means you can power dashboards, trigger business logic, feed machine learning models and support interactive gen AI experiences, all from a single source of truth.
3. Make data available to AI
Once you’ve unified your data, make it available to your AI systems through:
Real-time APIs that serve up relevant context
Semantic search using vector embeddings stored directly in the platform
Secure access controls to protect sensitive business data
Your generative AI tools can now go beyond guessing. They can access live inventory, customer history, pricing models and more — turning generic answers into precise, contextualized actions.
How SingleStore powers real-time data intelligence
SingleStore combines transactions, analytics and AI workflows into a single engine — giving you the performance of a real-time database with the flexibility of a full data intelligence platform.
Unlike systems designed for one job (OLAP or OLTP), SingleStore was built to handle them all, with millisecond response times and cloud-native scalability.
Don’t let your data fall behind your decisions
Generative AI can answer your questions. But only data intelligence can answer them with your data.
If your business wants to move from gut instinct to precision, from static reports to live insights, from generic models to domain-specific automation, then it’s time to rethink your data stack.
SingleStore gives you the foundation to build true data intelligence. So when the next big question comes up in that meeting, you’re not waiting on a dashboard or guessing at a trend. You already know the answer.
