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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.

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Architecture Components

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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.

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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

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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

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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

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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.

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Key Features

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Multi-Modal Embeddings

Corvic creates embeddings from various data types:
  • Text documents
  • Tabular data
  • Graph structures
  • Mixed data types

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Distributed Processing

The platform uses distributed high-performance computation:
  • 10x-100x faster than alternative implementations
  • Optimized proprietary algorithms
  • Efficient resource utilization

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Security & Privacy

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

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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

API Integrations

Learn about integrating with the Corvic Platform.

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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

Get Started

Start building with Corvic.