RELICA
Semantic modeling for next-generation
cognitive applications
The emergent future demands a shared data substrate....
Next-generation cognitive systems represent the long-awaited fulfillment of personal computing's promised vision. They combine genuine machine intelligence with integrated world modeling — unified data dioramas in place of scattered silos. They present adaptive multimodal interfaces, letting you engage the same substrate across every mode of interaction — chat, voice, symbolic manipulation, extended reality, etc., all expressions of the same underlying coherence. Most of all, they sustain a continuous relationship with your computing environment — an ongoing dialogue that fluidly shifts between capturing and leveraging information and shaping the system itself. If it reads as science fiction it's only because the enabling data foundation has been missing.
RELICA is that foundation. A self-describing knowledge graph in which relationship semantics are defined within the graph itself, RELICA provides the integrated ontological substrate these cognitive systems require. It ships with foundational modeling capabilities — native temporal, spatial, and physical object semantics among them — so developers no longer need to construct core ontologies from scratch. You begin directly in your domain, mapping your problem space with RELICA's shared vocabulary and extending it as needed, benefiting from the accumulation of knowledge over time.
Because semantics live within the model itself, AI agents can read, reason about, and modify the graph's meaning structures. This is what enables sustained collaboration between human and machine intelligence — the defining characteristic of the next computing paradigm.
_ THE BIG IDEA
[ Continuous cognitive loop: human ↔ interface ↔ AI ↔ semantic model ↔ world ]
Self-Referential Semantics
The model knows what it means, not just what it contains. Relationship semantics defined within the graph itself.
AI-Native Architecture
Agents read, reason about, and modify meaning structures directly. True human-machine knowledge collaboration.
Foundation Ontology Included
Native temporal, spatial, and physical object modeling. Start in your domain, not building primitives.
Expression begets experience.
_ APPLICATIONS
Personal Cognitive Computing
Not enterprise middleware. Not another productivity hack. A genuine extension of your cognitive capabilities.
Personal Assistant
Cognitive Computing Environment
Personal AI maintains persistent world model of your projects, preferences, and routines. Understands context across email, calendar, documents, and external systems. Proactively manages tasks, suggests connections, and adapts to changing priorities—all grounded in semantic understanding. It doesn't just execute commands; it understands your world.
Relevant Capabilities:
Knowledge Work
Research & Writing Companion
Build a living knowledge base where notes, sources, ideas, and insights exist as interconnected semantic entities. AI helps discover connections between concepts, surfaces relevant research, and assists in synthesizing arguments. Your second brain that actually understands what things mean, not just keyword matches.
Relevant Capabilities:
Creative & Professional
Project Memory & Context
Every project—software, creative, professional—exists as a rich semantic model capturing requirements, decisions, relationships, and evolution over time. AI agents help maintain context across months or years, surface relevant precedents, and prevent knowledge loss during transitions. Institutional memory for teams of one.
Relevant Capabilities:
Development status and planned features
Project Roadmap→