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Spice AI
Spice.ai is a data and AI platform that combines federated SQL query, hybrid search, and LLM inference in a portable, open-source runtime
For agents: Data and AI platform with federated SQL, hybrid search, LLM inference and data acceleration in an open-source runtime; docs cover Spice Cloud and Enterprise.
federated sqlhybrid searchllm inferencedata accelerationopen-source runtimecdc replication
Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-21T03:53:35.125Z. Cached copy · Source on spice.ai
# Spice AI
> Spice.ai is a data and AI platform that combines federated SQL query, hybrid search, and LLM inference in a portable, open-source runtime
Spice AI provides a unified data and AI infrastructure platform. Our open-source runtime enables federated SQL query across multiple data sources, hybrid vector and full-text search, and seamless LLM inference integration.
## Documentation
- [Spice.ai Platform Documentation](https://spice.ai/docs): Documentation for Spice Cloud, Spice Enterprise, and the Spice.ai platform API
- [Spice.ai OSS Documentation](https://spiceai.org/docs): Documentation for the open-source Spice runtime
- [GitHub Repository](https://github.com/spiceai/spiceai): Open-source codebase and examples
## Platform
- [Analytics Replica](https://spice.ai/platform/analytics): Add a real-time analytics replica to PostgreSQL, MySQL, and MongoDB in minutes. Spice replicates operational data with high-throughput CDC for sub-second analytics, without ETL and without load on production.
- [LLM Inference](https://spice.ai/platform/llm-inference): Call LLMs from SQL with the ai() function, or ask a question in plain language and get SQL back. Spice runs both in the runtime that holds your data.
- [RAG & Agentic Retrieval](https://spice.ai/platform/retrieval-augmented-generation): Ground RAG pipelines and AI agents in enterprise data. Spice combines hybrid vector and full-text search, SQL federation, and model inference in one runtime.
- [SQL Federation & Acceleration](https://spice.ai/platform/sql-federation-acceleration): Spice joins data from many sources in one SQL query, and keeps hot tables in a local engine for fast reads. No ETL pipeline is necessary.
## Use Cases
- [Analytics](https://spice.ai/use-case/analytics): Add a real-time analytics replica to PostgreSQL, MySQL, and MongoDB in minutes. Run sub-second analytics on operational data with high-throughput CDC replication, without ETL and without load on production.
- [Datalake Accelerator](https://spice.ai/use-case/datalake-accelerator): Accelerate query performance in your data lake with Spice. Run SQL locally on federated datasets for up to 100x faster performance.
- [Operational Data Lakehouse](https://spice.ai/use-case/operational-data-lakehouse): Federate, accelerate, and serve data-intensive apps and AI agents directly from object storage with millisecond performance.
- [Secure AI Agents](https://spice.ai/use-case/secure-ai-agents): Build and deploy AI agents that are secure by design. Federate-governed context, enforce policy inline, and route to any model with full auditability.
## Features
- [AI Model Serving](https://spice.ai/feature/ai-model-serving): Serve hosted and local LLMs from the Spice runtime. Call them through an OpenAI-compatible API or the ai() SQL function, grounded in your data.
- [Distributed Query](https://spice.ai/feature/distributed-query): Distributed query in Spice runs one SQL query across a cluster of executor nodes, coordinated by a sche
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