What If Your Security Data Could Just Answer Your Questions? For ACI Protection's Client, Now It Can.

We built Data AI, Magentic AI's proprietary conversational data agent, deployed directly on top of ACI Protection's operational data platform.

The idea was simple: instead of making leadership learn the dashboard, let them just ask. Data AI handles everything else.

Here's how it works and what we built:

• Natural Language to SQL, Instantly. When a user types a question into Data AI, the agent interprets the intent behind the query and writes a precise SQL query to fetch exactly the right data from ACI's database. No filters. No navigation. No analyst in the loop. The user just asks, and the data comes back.
• Dual Output: Raw Data and Beautiful Visuals. Every response from Data AI comes in two forms. The raw data, clean and downloadable, for teams that want to work with it directly. And a generated visual, a chart, graph, or structured table, presented in a format that leadership can screenshot, download, or drop straight into a presentation. Both, every time, without asking.
• An AI That Thinks Like a Data Scientist. What makes Data AI genuinely different is what happens after the answer. The agent doesn't just respond and wait. It actively suggests what to look at next. It surfaces related patterns. It prompts the user with follow-up questions they might not have thought to ask. The experience is less like using a search bar and more like having a sharp data scientist sitting in the room with you, one who's already read everything in the database and is nudging you toward the insights that matter.
• Built for Leadership, Not Analysts. The entire interface was designed with upper management in mind. Clean, fast, conversational. No training required. If you can type a question, you can use Data AI.
• Seamless Integration with Existing Infrastructure. Data AI sits on top of the data platform we already built for ACI, so there was no disruption to existing workflows. Dashboards and scheduled reports still run. Data AI is the layer that makes the data accessible to everyone else.

Because Data AI was built directly on top of ACI's existing data infrastructure, the implementation was faster than a ground-up build. The database was already structured, the data was already clean, and the ingestion pipeline was already running. What we needed to build was the intelligence layer on top of it.

We worked in two focused phases:

• Phase 1: Agent Build and Query Engine. We developed the core Data AI agent, the natural language interpretation layer, the SQL generation engine, and the dual output system for raw data and visuals. This phase ended with a working agent that could accurately answer a wide range of operational questions across ACI's full dataset.
• Phase 2: Proactive Intelligence and UI. We built the follow-up suggestion engine, the layer that makes Data AI feel like a data scientist rather than a search tool. Then we wrapped it in a clean, leadership-ready conversational interface and integrated it into the existing platform experience.

The results shifted how ACI's enterprise client actually interacted with their operational data:

• Leadership started engaging with data directly for the first time, without routing requests through analysts or waiting for scheduled reports.
• Ad hoc data requests dropped significantly because stakeholders could now get answers themselves, instantly, in a format they could immediately use.
• The quality of questions improved because Data AI kept prompting users to go deeper, surfacing angles and follow-ups that wouldn't have come up in a traditional dashboard session.
• Insights that previously lived in the database and never got surfaced started showing up in leadership conversations, because the barrier to accessing them had been removed entirely.
• Report preparation time for meetings dropped because every answer from Data AI came with a ready-to-use visual that could be exported and dropped into a deck without any additional formatting.