01
Agent runtime
Deterministic execution graphs over LLM-native primitives. Pause, fork, replay, and audit every decision an agent makes.
Ontology layer · coming soon
Agentic AI,
grounded in ontology.
Densery builds autonomous agents that don't just predict tokens — they reason over structured knowledge of the world. We're engineering the substrate where language models, tools, and ontologies converge into systems that act with intent.
108
typed relations
<120ms
agent step latency
0
hallucinated entities
// platform A reasoning stack,
A reasoning stack,
not a wrapper.
Most "agents" are loops over a chat model. Densery is a vertically integrated runtime — planner, memory, ontology, and tool fabric — designed from the ground up for long-horizon autonomy.
02
Ontology core Coming soon
A living, versioned model of entities, relations, and constraints. Agents reason against ground truth, not against vibes.
03
Tool fabric
Typed, sandboxed, signable tool calls. Connect to anything — from internal APIs to physical actuators — with provenance baked in.
04
Memory mesh
Episodic, semantic, and procedural memory unified under one query plane. Agents that remember, reflect, and improve.
// ontology
The world is structured.
The world is structured.
Your AI should know that.
Language is a lossy projection of reality. Densery's ontology layer reconstructs the underlying shape — concepts, types, invariants, causal links — and gives agents a stable surface to plan on.
- Bi-directional sync with LLM context windows
- Constraint-checked generation & tool calls
- First-class temporal & provenance edges
- Domain templates: finance, bio, robotics, ops
// research Open questions
Open questions
we're chasing.
Alignment
How do we make agent intent legible to humans at every step?
Symbolic ↔ neural
Translating between latent representations and typed ontologies without loss.
Long-horizon
Stable planning across thousands of steps and hours of wall time.
Verification
Proof-carrying actions: agents that ship evidence with every decision.