readme.md
Welcome to Spice.ai
The Spice.ai Cloud Platform is an AI application and agent cloud — an AI-backend-as-a-service with composable, ready-to-use building blocks including high-speed SQL query, LLM inference, vector search, and RAG, built on cloud-scale, managed Spice.ai OSS.
This documentation covers the Spice.ai Cloud Platform.
Table of Contents
| Feature | Description | Link |
|---|---|---|
| 🚀 Get Started | Sign up and run your first query in minutes | Get Started |
| ⚡ Federated SQL Query | Query across any data source with one SQL interface | /pages/JSLAgkGEzRdATtrY2WbZ |
| 🤖 AI Gateway | OpenAI-compatible API for LLM inference | /pages/xPzXLnuTVGxNphNmkCqK |
| 🔍 Search & Retrieval | Vector and hybrid search for RAG workflows | /pages/fTHrnT4bxBvNnzdKaEO7 |
| 🔌 Data Connectors | Connect to 30+ databases, warehouses, and lakes | /pages/N3bRKIkaBpwkNfccYrXd |
| 📊 Monitoring | Observe performance with Grafana, Datadog, and more | Monitoring |
What You Can Do
With the Spice.ai Cloud Platform you can:
- Query and accelerate data — Run high-performance SQL queries across multiple data sources with results optimized for AI applications and agents.
- Use AI models — Perform LLM inference with OpenAI, Anthropic, xAI, and more for chat, completion, and generative AI workflows.
- Build agentic AI apps — Combine data, models, search, and tools into production-grade AI agent backends.
- Collaborate on Spicepods — Share, fork, and manage datasets, models, embeddings, evals, and tools in a collaborative hub indexed by spicerack.org.
Use Cases
| Use Case | Description |
|---|---|
| Agentic AI Apps | Build AI agent backends with unified data and model access |
| Database CDN | Cache and accelerate hot data for low-latency applications |
| Data Lakehouse | Federated queries across warehouses, lakes, and databases |
| Enterprise Search | Semantic search across enterprise data sources |
| Enterprise RAG | Retrieval-augmented generation with your own data |
Quick Start
Get up and running in minutes:
Sample Code
from spicepy import Client
client = Client("YOUR_API_KEY")
reader = client.query(
"SELECT * FROM my_table LIMIT 10"
)
df = reader.read_pandas()
print(df)
Community & Support
- Slack — Ask questions and get help from the team at spice.ai/slack.
- GitHub — File issues and contribute at github.com/spiceai/spiceai.
- Enterprise support — Paid plans include priority support with an SLA.
- Help Center — Browse the Help Center for troubleshooting, guides, and FAQs.
Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the ask query parameter, and the optional goal query parameter:
GET https://docs.spice.ai/getting-started/readme.md?ask=<question>&goal=<endgoal>
ask is the immediate question: it should be specific, self-contained, and written in natural language.
goal is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.