Solution · Multi-Agent
An organization of agents that learns as one.
Each agent gets its own namespace. Shared knowledge flows through the neurosymbolic graph. The KnowledgeRouter dispatches capability requests across the org. Pathway reinforcement means the entire organization learns — not just isolated agents.
Capabilities
What you get.
Production-grade from day one. No flags, no betas — these ship when you adopt Minds.
Namespaced isolation
tenant → reservoir → agent → dataspace — four levels of containment.
Shared knowledge graph
Curated facts visible to the org; private memory stays private.
Capability routing
KnowledgeRouter dispatches across agents with policy enforcement.
Federated learning
Gradients shared via ZK proofs; raw data never leaves the agent.
Pathway reinforcement at the org level
The org learns what works.
Consensus + pattern sharing
Eventually-consistent consensus on canonical facts.
API
A few lines is all it takes.
exampletypescript
// An org with three agents.
const org = await minds.org.create({
name: "research-pod",
agents: [
{ name: "alpha", scope: "literature" },
{ name: "beta", scope: "synthesis" },
{ name: "gamma", scope: "writing" },
],
shared: { graph: true, memory: ["resource"] },
});
await org.run({ goal: "Draft the IF + insulin-sensitivity review by Friday." });Specs
What it costs, what it guarantees.
At a glance
- Agents per org
- unlimited
- Namespace levels
- 4 (tenant · reservoir · agent · dataspace)
- Federated learning
- ZK gradients
- Capability auth
- Arsenal ACTs
Guarantees
- Durability
- fsync per WAL commit
- Isolation
- MVCC · snapshot
- Audit
- BLAKE3 Merkle chain
- Encryption
- AES-256-GCM per-namespace
- Concurrency
- 100K+ ops/sec
Get started in an afternoon.
Run anywhere — Akasha Cloud, on-prem, or air-gapped.