Solution · Autonomous Agents
Build agents that remember.
Minds is the substrate for long-running autonomous agents. Episodic memory captures every action with valence and source. HRM plans, neurosymbolic grounds, continual learning improves the agent across sessions — not the model.
Capabilities
What you get.
Production-grade from day one. No flags, no betas — these ship when you adopt Minds.
Long-lived memory
Every action persists with bi-temporal validity. Agents recall what they did, when, and why.
Goal decomposition
HRM's H-module breaks goals into subgoals — your agent plans hierarchically.
Tool integration
Capability-scoped tool calls via Arsenal. Audited end to end.
Self-improvement
Pathway reinforcement strengthens what works. EWC protects what matters.
Multi-agent coordination
Each agent gets a namespace; the KnowledgeRouter routes capability calls.
Auditable
Every belief traced to its source. Every action signed and chained.
API
A few lines is all it takes.
exampletypescript
// One agent, end-to-end.
const agent = minds.agent({
name: "alpha",
scope: "Research",
profile: "full", // full cognitive cycle
tools: ["sql", "web", "recall"],
});
await agent.run({
goal: "Investigate Q3 revenue anomaly and write a memo.",
budget: { tokens: 50_000, seconds: 240 },
});
// Reflect on prior runs.
const reflections = await agent.reflect({ window: "7d" });Specs
What it costs, what it guarantees.
At a glance
- Agents per instance
- 10K+ concurrent
- Memory per agent
- 100M+ episodes / 1TB
- Cycle latency
- ~900ms full profile
- Cross-session continuity
- permanent
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.