AI Workspace
Semantic context engine & agentic canvas for high-leverage teams
A next-generation spatial computing and canvas environment that unifies unstructured project documentation, code repositories, and autonomous multi-model AI agents into a continuous reasoning workspace.
Repository Ingest
Indexed 42,100 symbols across AST. HNSW vector index synced.
Multi-Model Router
> Synthesizing architectural tradeoffs...PR #108 Generated
All typed contracts satisfied. 100% test coverage verified.
The cognitive fragmentation of contemporary knowledge work
Knowledge workers lose up to 40% of productive hours switching context between chat-based LLMs, documentation wikis, Figma boards, and IDEs. Traditional chat boxes restrict complex synthesis to a linear conversation history without persistent memory or spatial relationships.
A unified spatial canvas powered by persistent semantic memory
AI Workspace replaces linear prompts with an infinite, latency-critical interactive board. Nodes represent data sources, reasoning threads, and autonomous tasks that communicate via typed message streams with zero cognitive overhead.
Engineered for deterministic execution and low-latency interaction
The architecture decouples the high-frequency rendering pipeline from asynchronous model inference pipelines through a distributed pub/sub event mesh.
Spatial Rendering Engine
GPU-accelerated WebGL / Canvas2D rendering core maintaining 60 frames per second under load with thousands of active nodes.
Semantic Vector Router
Hierarchical HNSW indexing and semantic caching layer cutting inference token consumption by 62%.
Event-Driven Agent Mesh
Sub-millisecond WebSocket multiplexer coordinating concurrent agent swarms and human intervention checkpoints.