Custom Knowledge Swarm
Build a custom AI knowledge engine for your ecosystem.
Last updated
Build a custom AI knowledge engine for your ecosystem.
Last updated
Knowledge Swarms are custom AI knowledge engines tailored to your project’s unique data. It aggregates, synthesizes, and updates information from public/private sources (news, on-chain activity, social media, docs) into a unified system accessible via APIs, AI agents, or applications.
Think of it as:
A self-updating, high-context “brain” for your project or topic.
A scalable alternative to static knowledge bases or brittle RAG pipelines.
Built on Fractal, our proprietary knowledge engine that removes redundancy and ensures real-time accuracy.
Define Scope:
Identify your data needs and sources for ingestion
For example: Learn Pudgy Penguins ecosystem updates, US stock news, or BNB Chain developer activity.
Pipeline Setup:
Public Sources: News, social media, blockchain transactions.
Private Sources: Internal docs, proprietary APIs.
Custom Sources: We build scrapers or integrate new APIs.
Fractal Integration
Fractal groups related data into subgraphs, e.g. all Pudgy Penguin trades + related tweets + lore updates.
Updates subgraphs in real-time as data changes.
Model Training
Your custom AI model connects to the knowledge engine, learning from Fractal’s structured subgraphs.
Deployment
Powers your custom AI models and Universal AI Agents
Which in turns, powers any front-end: chatbots, AI agents, games, analytics dashboards, and more.
Typical integration time: 3–7 days.
Contact us or apply here to build your own Knowledge Swarm.
For Crypto Projects: Fractal natively handles overlapping on-chain and off-chain data, e.g. linking a token’s price drop to Reddit speculation + exchange outflows.
Sustainability: Reduces token usage by 30–50% vs. traditional RAG by eliminating redundant data.
Real-Time Context: Automatically update answers when new data arrives, e.g. notify users if a protocol hack impacts their query.
Custom Data Pipelines: We adapt to your sources, whether scraping forums or parsing onchain transactions.
Enterprise-Ready: Deploy outputs as APIs, AI agents, or embed into existing apps via Universal AI Agents.
