> ## Documentation Index
> Fetch the complete documentation index at: https://docs.corvic.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Platform Architecture

> Understand the architecture of the Corvic Platform

## Overview

The Corvic Platform is designed as an end-to-end solution for transforming enterprise data into actionable insights through multi-modal embeddings and AI agents.

## Architecture Components

### Data Ingestion Layer

The platform supports ingestion of multi-structured data:

* **Structured data**: Tables, databases, parquet files
* **Semi-structured data**: JSON, XML
* **Unstructured data**: Text documents, images

All data is processed through ingestion pipelines that clean, transform, and prepare data for embedding generation.

### Embedding Generation Layer

The platform generates and manages multi-space embeddings:

* **Corvic Tables**: Define what entities to embed (distributed processing tables for data transformations)
* **Spaces**: Transform Corvic Tables into embeddings using state-of-the-art algorithms
* **Quality Metrics**: Monitor embedding quality with real-time metrics

### Storage Layer

Embeddings are stored in a distributed, high-performance storage system that supports:

* Vector search and retrieval
* Multi-space query capabilities
* Scalable storage for large datasets

### Agent Layer

The platform supports agent creation and configuration:

* **LLM Integration**: Leverage multiple LLM providers
* **Multi-space Traversal**: Agents can query across multiple embedding spaces
* **Dynamic Policies**: Generate insights from ingested data

## Data Flow (Data Apps & Intelligence Operations)

Here's how these concepts work together in Corvic:

**Ingest Data**
→ Connect and sync data from files, object stores, databases, and live systems into Data Rooms.

**Compose Entities & Logic**
→ Define Corvic Tables to model domain entities, operational units, and business logic across multiple data sources.

**Transform & Enrich**
→ Apply distributed processing to clean, join, enrich, and structure complex data—powering analytics, features, and domain intelligence.

**Build Data Apps & Intelligence**
→ Assemble agents, analytics, and workflows on top of Corvic Tables to explore data, automate reasoning, and drive operational decisions.

## Key Features

### Multi-Modal Embeddings

Corvic creates embeddings from various data types:

* Text documents
* Tabular data
* Graph structures
* Mixed data types

### Distributed Processing

The platform uses distributed high-performance computation:

* 10x-100x faster than alternative implementations
* Optimized proprietary algorithms
* Efficient resource utilization

### Security & Privacy

* Data isolation between organizations and rooms
* State-of-the-art cryptography
* Compliance with privacy standards
* Secure development practices

## Integration Points

The platform provides multiple integration points:

* **REST APIs**: Direct API access to embeddings and agents
* **MCP Integrations**: Model Context Protocol support
* **Python SDK**: Native Python integration
* **Framework Integrations**: OpenAI, Langchain, CrewAI, FastAPI

<Card title="API Integrations" icon="plug" href="/integrations/overview">
  Learn about integrating with the Corvic Platform.
</Card>

## Scalability

The architecture is designed for scale:

* Horizontal scaling of compute resources
* Distributed storage for large datasets
* Efficient embedding generation at scale
* Support for multiple concurrent users and rooms

<Card title="Get Started" icon="rocket" href="/get-started/quickstart">
  Start building with Corvic.
</Card>