White Label AI Tool for Agencies: Resell Text-to-SQL to Clients

Looking for a white label AI tool to resell? Your clients sit on databases full of answers they can't access without developers.
A white label data assistant solves this problem while building recurring revenue for your agency.

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The Data Access Problem Every Agency Sees

If you've built websites or applications for clients, you've seen this pattern: the client has a database with years of valuable data, but they can't answer basic questions without asking a developer.

An e-commerce store owner wants to know their best-selling products last month. A SaaS founder needs to see which features users actually use. A service business wants to find invoices overdue by 30 days.

The data exists. The questions are simple. But the path from question to answer requires SQL knowledge, database access, and developer time.

The Traditional Workflow

  1. Client has a question about their data
  2. They email you or their developer
  3. Someone writes a SQL query
  4. Results get formatted and sent back
  5. Follow-up question? Repeat the cycle

This cycle can take hours or days for what should be a 30-second answer.

Dashboard tools like Metabase or Google Data Studio solve part of this. They create fixed reports and visualizations. But they can't handle ad-hoc questions. "Show me customers who bought X but not Y" isn't a pre-built report. It's a question that requires SQL.

What Text-to-SQL for Agencies Actually Does

Text-to-SQL tools are the core of any white label AI tool for data access. They use AI to convert natural language questions into database queries. The user types "What were my top 10 products last month?" and the system generates the SQL, runs it against the database, and returns the results.

This isn't new technology. The challenge has been making it accurate enough for production use and simple enough for non-technical users. Recent advances in language models have made both possible.

How It Compares to Other Tools

Tool Type What It Does Data Source Question Types
Chatbots Customer support, lead capture Knowledge base, FAQs "What are your hours?"
Dashboards Pre-built reports and charts Connected data sources Fixed report views only
Text-to-SQL Ad-hoc database queries Client's actual database Any question the data can answer

The key difference: chatbots answer from a knowledge base of pre-written content. Dashboards show pre-configured views. Text-to-SQL generates queries on demand from any question the user asks.

The Agency AI Resell Business Model

For agencies, the interesting part isn't the technology. It's the agency AI resell opportunity.

Most text-to-SQL tools offer white label AI tool options. You pay a flat monthly fee, customize the branding, and resell to your clients at whatever price makes sense for your market. This white label data assistant model creates predictable recurring revenue.

LILA Pricing Structure

White-label add-on $250/mo Flat fee, unlimited clients
Your client pricing $200-500/mo You set the price
Query costs ~$0.02/query Pass through or bundle

The economics improve with scale. Your second client doubles your revenue without increasing your platform cost. By your fifth client, you're looking at meaningful recurring revenue.

More importantly, it's a service that's hard for clients to cancel. Once a team gets used to asking questions and getting answers, going back to waiting for developer reports feels slow.

Where This Works Best

Not every client needs this. The best candidates have two things: a database with useful data, and team members who need answers but can't write SQL.

E-Commerce Operations

WooCommerce stores, Shopify (with database sync), custom platforms

Store managers asking questions like:

  • "Which products have low inventory but high sales velocity?"
  • "Show me customers who ordered in December but not January"
  • "What's my average order value by traffic source?"

Works best when the operations team is separate from the development team.

SaaS Product Teams

Custom applications, subscription businesses with product databases

Product managers and founders asking:

  • "How many users activated feature X this week?"
  • "What's the correlation between onboarding completion and retention?"
  • "Which pricing tier has the highest expansion revenue?"

Especially valuable when engineering is a bottleneck for data requests.

Service Business Operations

Booking systems, CRMs, custom internal tools

Operations managers asking:

  • "Which services have the highest profit margin?"
  • "Show me all appointments scheduled but not confirmed"
  • "What's our average time from inquiry to booking?"

Common in businesses that outgrew spreadsheets but can't justify a data team.

Setting Up LILA for Your Clients

Here's what a typical LILA setup looks like:

1. Database Schema Upload

Export the client's database structure (tables, columns, relationships) and upload to LILA. No actual data needed during setup. LILA learns the structure, not the contents.

For security-conscious clients: the AI only sees schema definitions. Actual queries run through encrypted connections to their database.

2. Connection Configuration

Create a read-only database user with SELECT permissions only. Enter credentials in LILA's admin panel. Credentials are encrypted at rest.

LILA supports standard ports and SSH tunnels for databases behind firewalls.

3. Branding Customization

With white-label enabled: replace LILA branding with your own. Company name, logo, colors. The client sees your brand, never "LILA".

4. Deployment

Copy the embed code. One line of JavaScript on the client's admin panel, internal tool, or website. Done.

Total setup time: under an hour per client once you've done it once.

How to Position and Price It

The positioning that works best: "Data access as a service." You're not selling software. You're selling the ability for their team to get answers without waiting.

For E-Commerce Clients

"Right now, when your operations team needs sales data, they wait for someone to pull a report. What if they could just ask? Type a question, get the answer. No spreadsheets, no waiting, no developer involvement."

For SaaS Clients

"Your product team makes decisions based on data. But every data request goes through engineering, which means they wait in a queue. This gives them direct access to answers without pulling engineering off product work."

Pricing Conversation

"We set this up once, maintain it for you, and your team gets unlimited questions. $X per month, no per-user fees. Compare that to the developer time you're currently spending on ad-hoc data requests."

Pricing Strategies That Work

  • Flat monthly fee: Simplest to sell. "$300/month for unlimited data access." Works well for clients with predictable usage.
  • Tiered by query volume: "$200/month for 500 queries, $350 for 2000." Better margins on heavy users.
  • Bundled with retainer: Add it to existing maintenance packages. "Your hosting and support package now includes AI data access."

Getting Started with Your White Label AI Tool

If you want to test the agency AI resell model, LILA offers a white label data assistant platform with text-to-SQL for agencies built in.

What LILA Provides

  • Flat-rate white-label: $250/month for unlimited clients and projects
  • Full branding control: Your name, logo, colors. Clients never see "LILA"
  • Database support: MySQL, PostgreSQL, MariaDB, SQL Server
  • Privacy-first: LILA runs its own AI models on dedicated infrastructure. Data never touches OpenAI or other third parties
  • Embeddable widget: Couple of line of code deployment to any website or app

Free tier available to test before committing to white-label. 50 queries included.

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Common Questions

How is LILA different from chatbots?

Chatbots answer from scripted knowledge bases. LILA connects to your client's actual database and returns real data. "What sold most last week?" gives actual sales numbers, not a canned response.

What if LILA generates wrong SQL?

LILA shows the generated SQL alongside results so users can verify. Read-only access means wrong queries return wrong data, not data loss. Accuracy improves with clear column names and specific questions.

Is client data safe with LILA?

Yes. LILA runs its own AI models on dedicated infrastructure. No OpenAI, no third-party AI providers. Queries execute through encrypted connections. Database credentials are encrypted at rest. Read-only access prevents data modification.

What databases does LILA support?

MySQL, PostgreSQL, MariaDB, and SQL Server. This covers WooCommerce, Laravel, Django, Rails, and most SaaS products. MSSQL support coming soon for enterprise clients.

How much technical knowledge do I need?

Basic database concepts: tables, columns, relationships. You upload the schema, LILA handles the SQL. If you've built WordPress sites or worked with any database-backed app, you have enough background.

Can I try LILA before committing to white-label?

Yes. Free tier includes 50 queries to test with your own database. White-label is a $250/month add-on when you're ready to resell.

Ready to Add a White Label AI Tool to Your Services?

Start free with text-to-SQL for agencies. White-label at $250/month when you're ready to resell your white label data assistant.

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