Superprism. Infrastructure for Collaborative AI
Superprism is an R&D lab for human-agent coordination. We research and build systems where humans and AI agents generate shared context together — without sacrificing privacy or sovereignty.
AI tools are built for individuals.
But the most complex work happens in teams:
- • distributed organizations
- • research groups
- • open source communities
- • global companies
These teams struggle to maintain shared context across conversations, documents, repositories, and AI agents.
Superprism explores how humans and AI systems coordinate knowledge together.
Areas of Inquiry
Research Areas
We explore the systems required for collaborative AI.
● Active Experiment
Collaborative AI Environments
Shared environments where teams and AI agents operate on the same evolving context. Designed so agents assist without displacing human judgment.
● Active Experiment
Context Engineering
Techniques for creating, maintaining, and isolating context so AI systems stay useful at scale.
● Active Experiment
Local-First AI Infrastructure
Architectures that preserve privacy and sovereignty over knowledge.
Agentic Economies
Exploring how AI agents interact with decentralized economic systems.
Multi-Agent Coordination
How networks of specialized agents communicate, divide work, and maintain coherence with shared context.
Knowledge Interfaces
New ways for humans to navigate and shape complex shared context.
Reference Implementation
Superprism
The Superprism app is our primary research artifact, a collaborative AI workspace for distributed teams.
We also work closely with organizations to build bespoke systems tailored to their needs and workflows.
Current Experiments
- •multi-source knowledge ingestion
- •automated daily and weekly digests
- •shared context workspaces
- •project-specific context isolation
- •knowledge graph exploration
Field Work
Applied Research
Our systems are tested with organizations exploring collaborative AI.
Case Study
Raid Guild
Collaborative AI systems for decentralized teams.
- •Shared knowledge base for contributors
- •Automated ingestion of chats and governance discussions
- •AI-assisted sensemaking across distributed contributors
Case Study
Open Machine
AI-native knowledge infrastructure for cultural search initiatives.
- •Git-centric knowledge base
- •Inner Mind built for knowledge production
- •Outer Mind meant for public interaction
The next generation of AI will not be individual.
It will be collaborative.
As AI agents become ubiquitous, the challenge is no longer individual productivity.
The challenge is shared intelligence.
There's also a compounding problem. The most capable AI tools are built for technical users, and collaboration doesn't work when only half the room can participate.
How teams create, maintain, and govern context will determine whether AI empowers organizations — or fragments them.
Superprism explores the infrastructure required for collaborative intelligence.
Work With Us
Superprism works closely with organizations exploring new ways of enhancing collaboration with AI.
Research Partnerships
Teams experimenting with collaborative AI systems.
Applied Implementations
Organizations integrating AI into complex coordination workflows.
Funding & Grants
Support our research into privacy-preserving and decentralized AI infrastructure.