Ask Your Database Anything: AI-Powered Business Intelligence

Intuitive SQL building and effortless information extraction with large language models.

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Webinar

Unlock the power of your Snowflake data with LLMs

In this webinar, you'll learn how to leverage LLMs to build an AI system to query your database.

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Intuitive database access powered by LLMs

Perform analytical QA on any tabular dataset.

Streamline business intelligence

Gain actionable insight into your business processes in no time.

Democratize data access

Gain actionable insight into your business processes in no time.

Gain insights across databases

Encode your database schemas once and let LLM do the rest, even across databases.

Transform data into customer value

Empower your customers with instant, data-driven insights - turning your database into a revenue-generating asset.

Customer Testimonial

"Working with deepset Cloud has positioned us as a leading edge provider in our space. It has improved our relationship with clients as they see us rapidly responding to their needs. Finally, it has resulted in a new product to sell as well as incremental revenues."

Dan Coates
President

Generate data-driven insights in seconds – even across database schemas

Build robust LLM-powered BI solutions on top of your tabular data.
01

World-class text-to-SQL templates

Get started right away with proven Compound AI templates, including LLMs tailored for text-to-SQL tasks. The templates work right out of the box, or you can use them as a starting point for your own custom AI architecture–whatever works best for your use case.

02

Database insights through natural dialogue

Run queries across multiple tables in your database, join them, and reorder them according to complex criteria–all using only natural language. Pass your database schema to LLM to generate precise SQL statements to extract the desired information from the database and return the resulting table along with a detailed summary of the findings.

03

Built-in AI engineering best practices

Follow AI engineering best practices for product development, using our guided workflows for building, testing, deploying, and monitoring to create a customized text-to-SQL solution for your data. Cultivate team-wide expertise in mastering the intricacies of AI product development, even among those with limited experience.

04

Seamless database connectivity

Take advantage of deepset's superior text-to-SQL capabilities without moving your data out of your database.

SCALABLE, SAFE AND SECURE

Open Source Foundation
Built on Haystack, the trusted open-source framework for production-ready LLM applications.
Data Privacy Assurance
Your data remains private and isn’t utilized for training your choice AI models.
Flexible Identity Management
Seamlessly integrate with your Identity Provider and configure Single Sign-On (SSO) with SAML support for tailored role access.
Custom Data Retention Policies
You define how long we keep your data, giving you full control over data retention timelines.
Enterprise Support
Dedicated support from our security and infrastructure experts, with guaranteed response times for critical issues.

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FAQ

What is Text-to-SQL?

Text-to-SQL (or Text2SQL) uses LLMs to convert natural language queries into structured SQL statements that can query a database. This simplifies complex data analysis, making database insights accessible to non-technical users and faster and more intuitive for analysts. Text-to-SQL solutions can deliver accurate quantitative data and qualitative insights, enhanced by AI analytics and interactive chat capabilities.

How does Text-to-SQL improve business intelligence?

Text-to-SQL bridges the gap between user intent and database queries, providing seamless access to insights without requiring SQL expertise or in-depth knowledge of your data and its structure. It improves efficiency, reduces manual effort, and democratizes access to data for broader business use, enabling data-driven decision making across the enterprise.

What are the use cases for Text-to-SQL?

Text-to-SQL is ideal for self-service analytics, business intelligence, financial reporting, market research, and customer support dashboards. Its ability to generate SQL queries from natural language makes it valuable for government and industries such as market research, finance, healthcare, and retail, enabling non-technical users to access data insights.

How can I implement Text-to-SQL in my organization?

Implementing Text-to-SQL involves integrating AI models capable of natural language understanding with your existing databases, such as Snowflake and Amazon Redshift. deepset allows you to build custom pipelines for accurate query processing, SQL generation, and insight summarization. Text-to-SQL in deepset can also be integrated with other AI approaches such as agents, RAG, search, and intelligent document processing (IDP) for even more powerful solutions.

How can I customize Text-to-SQL for my business?

Customizing Text-to-SQL involves refining components like retrievers, query processors, and model prompts to match your database schema and business-specific language. With deepset's modular framework, you can optimize the system for accuracy, scalability, and ease of use, ensuring that it fits your unique requirements.