AI Applications

Build AI products not AI infrastructure.

LLM integration, RAG pipelines, AI agents — any model, one call. Stop building the plumbing and start building the product.

Try the Playground Read the Docs

5 lines to a RAG chatbot

This is all it takes. Seriously.

import { ee } from "@ee/sdk";

const docs  = await ee.vector.ingest("./knowledge-base");
const ctx   = await ee.vector.search(query, { topK: 5 });
const reply = await ee.ai.chat({ model: "gpt-4o", context: ctx });
const saved = await ee.db.insert("conversations", { query, reply });

// RAG chatbot — done. Typed. Logged. Scalable.

AI capabilities

Model-agnostic. Feature-complete.

LLM Integration

Any model — OpenAI, Anthropic, Mistral, Llama, or your own. One API, model-agnostic.

RAG Pipelines

Document ingestion, chunking, embedding, vector storage, and retrieval — five lines of code.

AI Agents

Tool-use framework with memory, planning, and execution. Build agents that actually do things.

Embeddings

Generate, store, and search embeddings at scale. Semantic search with sub-100ms latency.

Streaming Responses

Server-sent events for real-time token streaming. No WebSocket setup required.

Context Management

Automatic context windowing, summarization, and conversation history — no token counting.

Try the AI playground

From prototype to production in one afternoon. Any model, any use case.

Try the Playground Read the Docs

AI Applications

Build AI products not AI infrastructure.

LLM integration, RAG pipelines, AI agents — any model, one call. Stop building the plumbing and start building the product.

Try the Playground Read the Docs

5 lines to a RAG chatbot

This is all it takes. Seriously.

import { ee } from "@ee/sdk";

const docs  = await ee.vector.ingest("./knowledge-base");
const ctx   = await ee.vector.search(query, { topK: 5 });
const reply = await ee.ai.chat({ model: "gpt-4o", context: ctx });
const saved = await ee.db.insert("conversations", { query, reply });

// RAG chatbot — done. Typed. Logged. Scalable.

AI capabilities

Model-agnostic. Feature-complete.

LLM Integration

Any model — OpenAI, Anthropic, Mistral, Llama, or your own. One API, model-agnostic.

RAG Pipelines

Document ingestion, chunking, embedding, vector storage, and retrieval — five lines of code.

AI Agents

Tool-use framework with memory, planning, and execution. Build agents that actually do things.

Embeddings

Generate, store, and search embeddings at scale. Semantic search with sub-100ms latency.

Streaming Responses

Server-sent events for real-time token streaming. No WebSocket setup required.

Context Management

Automatic context windowing, summarization, and conversation history — no token counting.

Try the AI playground

From prototype to production in one afternoon. Any model, any use case.

Try the Playground Read the Docs