Introducing LILA: The AI Assistant That Actually Understands Your Business Data
Your sales manager wants to know which customers haven’t ordered in 90 days. Your operations lead needs shipments delayed more than 24 hours. Your CEO asks about revenue by region for last quarter.
The answers exist. They’re sitting in your database right now. But getting them requires SQL knowledge, engineering time, or waiting for someone to build yet another dashboard.
We built LILA to eliminate that wall.
The Problem We Kept Seeing
Every data request in most organizations follows the same painful pattern:
- Business user has a question
- They submit a ticket to engineering or data team
- Someone writes a query (eventually)
- Results come back days later
- Follow-up questions restart the cycle
This isn’t a technology problem. It’s an access problem. The data exists. The questions are valid. But the path between them requires technical skills that most team members don’t have and shouldn’t need.
We watched this pattern repeat across dozens of implementations. Marketing teams waiting for campaign metrics. Sales managers guessing at pipeline health. Operations leads making decisions on outdated information.
The common thread: people who needed answers couldn’t get them without going through a technical gatekeeper.
What LILA Actually Does
LILA is an AI database assistant. You connect it to your database, and your team asks questions in plain language. LILA translates those questions into SQL, executes them safely, and returns formatted results.
No SQL knowledge required. No training courses. No waiting for engineering.
“Show me customers who bought Product A but never bought Product B” becomes a result set in seconds, not a ticket that sits in a backlog.
“What’s our conversion rate for mobile users this week compared to last week?” returns a comparison table, not a request for someone to pull the numbers.
“Which support tickets have been open longer than 48 hours?” surfaces the data immediately, not after someone remembers to check.
The questions your team already asks in meetings and emails become questions they can answer themselves.
Why We Built Our Own AI Infrastructure
Here’s where LILA differs from connecting ChatGPT to your database.
When you use third-party AI services, your data flows through their servers. Your schema, your queries, potentially your results. For many organizations, especially in healthcare, finance, and regulated industries, that’s a non-starter.
LILA runs on our own AI infrastructure. We don’t route your data through OpenAI, Anthropic, or Google. Your database credentials stay encrypted. Your queries process on systems we control. Your data never touches third-party AI services.
This isn’t a philosophical stance. It’s a practical requirement for organizations that take data security seriously. If you can’t send customer records to ChatGPT (and you shouldn’t), you need an alternative that doesn’t require it.
How It Works
Setup takes about 15 minutes:
Step 1 (2 minutes): Upload your database schema or connect with read-only credentials. LILA maps your tables, columns, and relationships.
Step 2 (3 minutes): Define access rules. Who can query which tables? What data should be filtered by user role? Which columns contain sensitive information?
Step 3 (10 seconds): Embed the widget with one line of code. Your team starts asking questions.
The widget embeds anywhere: internal dashboards, admin panels, customer portals. It looks like your application because it can be fully styled to match your brand.
The Self-Healing Engine
AI-generated SQL isn’t always perfect on the first try. Column names get confused. Join conditions need adjustment. Date formats vary.
Most systems would just return an error. “Query failed. Try again.”
LILA’s engine detects failures and attempts to fix them automatically. If a query doesn’t execute, it analyzes the error, adjusts the SQL, and retries. We’re hitting 85% accuracy on first attempts, with self-healing catching most of the remainder.
For complex questions, LILA asks clarifying follow-ups instead of guessing. “When you say ‘recent orders,’ do you mean last 7 days, last 30 days, or something else?”
The goal: users get answers, not error messages.
Beyond Simple Queries
LILA handles more than basic lookups:
- Aggregations: “Total sales by month for 2025”
- Comparisons: “How does this quarter compare to the same period last year?”
- Complex joins: “Show me customers with support tickets who also have pending orders”
- Conditional logic: “Orders over $500 from customers who signed up this year”
- Time-based analysis: “Which products saw the biggest sales increase last week?”
The natural language processing understands intent, not just keywords. Ask the same question three different ways and get the same accurate answer.
Multilingual From Day One
Your team in Dubai asks questions in Arabic. Your Berlin office uses German. Your Tokyo team prefers Japanese.
LILA supports 25+ languages with the same accuracy. No translation layer. No degraded performance. The French sales manager asks in French, gets answers in French, from the same database your English-speaking team queries.
For global organizations, this removes another barrier. Language shouldn’t determine who can access business intelligence.
The Pricing Model That Makes Sense
Traditional BI tools charge per user. Add 10 people to the dashboard? Pay for 10 seats. Scale to 100 users? Your bill scales too.
LILA charges per query, not per user. Your entire organization, from 10 employees to 10,000, accesses the same system at the same price. You only pay when questions get asked.
This changes the math on data access. Instead of limiting who gets BI licenses, you can give everyone the ability to ask questions. The cost stays predictable based on actual usage, not potential headcount.
For Agencies and Consultants
If you build applications for clients, LILA offers white-label capabilities. Remove our branding entirely. Your clients see your brand, your domain, your product.
Deploy “AcmeAnalytics” for one client and “RetailInsights” for another. Each looks custom-built. Each runs on the same proven infrastructure.
This opens a new service line without building AI from scratch. Your clients get database intelligence. You get recurring revenue. We handle the infrastructure.
What’s Coming Next
LILA starts with database queries, but the vision extends further.
We’re building toward an AI assistant that doesn’t just answer questions about your data, but takes action based on it. UI automation that responds to natural language commands. Connections to SaaS platforms like Shopify and Salesforce. Multi-database queries that pull from multiple sources in a single question.
The database assistant is the foundation. What we’re building is an AI that truly understands your business.
Try It Yourself
LILA offers 50 free queries to test with your own database. No credit card required. Connect your schema, ask some questions, see if the answers match what you’d get from manual SQL.
The setup takes 5 minutes. The decision of whether it works for your organization should take less than that.
Start your free trial at getlila.one
LILA is built by AALA AI, the enterprise AI division of AALA IT Solutions. For technical documentation, visit getlila.one/docs. For pricing details, see getlila.one/pricing.