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About
Defog.ai is a natural language data query tool designed to be embedded in applications.
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1.43M
1.43M
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(Computers_Elect…) 15.9K
(Computers_Elect…) 15.9K
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(US) 1.13M
(US) 1.13M
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23.3K
23.3K
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Summary
Deploy fine-tuned LLMs for enterprise analytics
Features
- Speed up data analyses in SQL, Python and R with AI assistants and agents tailored for your business - without sharing your data.
- Privacy-centric integration with any SQL database or data warehouse
- Answer questions that can require pages of SQL
- Automatically visualise data as tables and charts
- Fine-tuned on your metadata to give results you can trust
- Handle complex and repetitive workflows in SQL, Python and R with human-in-the-loop agents.
- Automates trial and error in statistical analyses
- Decomposes complex, multi-part questions into executable tasks
- Orchestrates handing off each task to an appropriate AI model
- Generates reports for editing and collaboration
- Go beyond generic models. Defog uses AI that is customized for your database schema and aligned to your business logic. Deploy fine-tuned models, monitor their performance and stay aligned with human feedback.
- Defog only uses metadata to fine-tune LLMs for you – it's never given access to your actual database. You can use our cloud offering or deploy models on-prem.
- Defog is powered by SQLCoder – the best performing open-source model for text-to-SQL generation.
- SQLCoder outperforms OpenAI’s gpt-3.5-turbo, and significantly outperforms all major open-source models for generic SQL schemas in Postgres. When fine-tuned on an individual DB schema, it outperforms gpt-4.
- SQL-Eval is our open source framework to evaluate the correctness of LLM-generated SQL. Our goal is to produce a reproducible framework that measures both the complexity and semantic diversity of queries.
- SQLCoder is compatible with all major SQL databases and data warehouses.
Use Cases
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Free
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Self-hosted
