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Vibe Coding Platform for Multi-modal Data

Berry AI brings conversational velocity to organize and manage multi-modal data and knowledge (docs, PDF, images, audio and video)

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"UI and application logic development is transformed by vibe coding, but the data layer has not evolved"

Building and managing data remains highly manual including defining data models, stitching together structured and unstructured data, and data enrichment pipelines

Claude AI + Berry AI Completes the Vibe Coding Solution

Code generation tools like Claude AI, Lovable or Base44 vibe your UI and application logic and Berry AI vibes your data, completing the solution, enabling true end-to-end creation. It also provides the following:

Connects different data types (Structured tables, docs, images, audio, video) into a semantically connected layer

Automatically creates the knowledge graph connecting different data types

Intelligent data enrichment and control

Berry AI natively understands docs, images, audio, video and enriches the data in place. It provides fine-grained governance and provides a memory layer for AI agents

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Own Your Knowledge. Own Your Future.

As AI agents start writing code and make decisions, a governable data and knowledge layer is not optional.
Its the foundation for control, intellectual property and long-term competitive advantage

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Why Berry AI ?

It is the first system purpose-built for managing data and knowledge on structured and unstructured data. The missing layer between raw data lake and AI agents & vector DB

Rapidly build governable knowledge graphs

Building knowledge graphs using traditional DBs is hard. Developers need to integrate multiple backends including RDBMS for metadata, text search engine, an annotation system and a graph store. You cannot govern multiple backend systems easily. Berry AI consolidates it into a single system.

Built-in semantic studio

Berry transforms raw documents, media and other data into richly annotated, multi-layered knowledge graphs, without manual data modeling

Natively manage PDF, text, images, audio, video, and JSON data types

Natively supports unstructured data types, including PDFs, images, audio, video, and JSON

Infinite flexibility to handle changing data

Berry can understand, integrate and index JSON data produced by AI workflows. JSON is the standard output format for AI models and it offers unparalleled flexibility to adapt to changes

PDF/Docs
Text
Image
Audio/Video
JSON

Multi-dimensional scaling and super fast performance

Horizontally scale knowledge graphs

Horizontally and separately scale knowledge data and knowledge index nodes

High performance query on knowledge graphs

Berry is designed to be used in application serving layer. It creates multiple indexes right on JSON knowledge graphs and is 5x or more faster on reads and writes compared to other DBs (MongoDB, MySQL etc)

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Berry API

Powerful API to ingest, enrich and search through knowledge graphs: See https://docs.berrydb.io/python-sdk/

User friendly APIs for AI applications

Powerful APIs to process unstructured data, multi modal search APIs for queries, annotation APIs and others provides a comprehensive APIs to build AI applications

Notebook access and SDKs

Notebook UI for accessing/processing unstructured data and building knowledge layers using Python or Java SDKs

Explainer video

A 90 second overview of Berry AI

Demo video

Getting started video

Ready to get started?

Contact us or sign up for 30 day free trial access

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