Powered by the Akasha Cognitive Engine

The cognitive OS for AI.

Multi-modal memory, hierarchical reasoning, neurosymbolic knowledge, spiking neurons, and lifelong learning — in a single substrate.

$curl -fsSL install.minds.sh | sh
The Cognitive Cycle

Six stages. One loop. Endless improvement.

Perceive
Attend
Decompose
Reason
Learn
Act
Stage 01 · Signals in

Perceive.

Raw experiences — queries, tool results, sensor reads — flow in. Deduplicated, scored for novelty, batched.

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Stage 02 · Spotlight

Attend.

The attention filter ranks signals by salience. Only what matters reaches consciousness via the Global Workspace.

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Stage 03 · Structure

Decompose.

Triples persist to the knowledge graph. Episodes flow into episodic memory with source attribution. Embeddings index in HNSW.

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Stage 04 · Plan

Reason.

HRM hierarchical planning — H-module decomposes the goal, L-module executes. Neurosymbolic blends neural similarity with symbolic paths.

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Stage 05 · Reinforce

Learn.

Reward-modulated Hebbian updates strengthen pathways that worked. EWC protects critical weights. Unused connections decay.

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Stage 06 · Output

Act.

The selected action emits. ActionFeedbackAdapter routes the result back into Perceive. The loop closes. The agent improves.

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cycle://run/8f3alive
Active stage
Perceive142ms
→ 14 raw events · novelty Δ +0.41
Global Workspace · broadcast
Attend38ms
→ top-5 selected · drop rate 64%
Global Workspace · broadcast
Decompose186ms
→ 23 triples · 5 episodes · 12 vectors
Global Workspace · broadcast
Reason418ms
→ 6 subgoals · ACT stopped at depth 4
Global Workspace · broadcast
Learn92ms
→ pathway 06 → 03 · Δw +0.182
Global Workspace · broadcast
Act26ms
→ action dispatched · feedback armed
Global Workspace · broadcast
cycle 8f3a · loop 12reward Δ +0.182
Multi-Modal Memory

Every memory an agent needs, in one place.

Most AI memory products give you one shape: a vector blob. Minds gives you the full neuroscience-grounded hierarchy — episodic, procedural, resource, vault, working, and associative — unified under one async API.

Episodic
Temporal events with emotional valence, importance, and source attribution.
Procedural
Executable workflows. Run them like functions.
Resource
Documents, blobs, and models. Full-text search included.
Vault
AES-256-GCM encrypted secrets, credentials, keys.
Working
Miller's 7±2 capacity. Decay. Variable binding.
Associative
Modern Hopfield networks. Finish a thought from a fragment.
Episodic · live

Agents remember what they did.

Every session captured with goal, outcome, valence, source. The StreamSparkline shows event importance over time. Auditable forgetting handles GDPR delete-requests cryptographically.

11 event types4 valencesMVCCBLAKE3 auditSource monitoring
memory/episodiclast 24h
Reasoning

Plans like a strategist.
Grounded like a lawyer.

The Hierarchical Reasoning Module (HRM) plans abstractly, executes concretely, and decides when to stop. Neurosymbolic fusion grounds every embedding in a symbolic path — hallucinations become a hardware problem you can fix.

HRM · Hierarchical Reasoning Module
H-Module · Abstract Planner
Goal decomposition · subgoal ordering · termination via ACT
slow
Decompose query
Order subgoals
Decide stop
L-Module · Concrete Executor
Tool calls · KG lookups · vector recall · chain-of-thought
fast
query KG
embed
ANN
ground
emit
Adaptive Compute
ACT
Backend
Burn / Rust
Model footprint
≈2.5 GB
Neurosymbolic · live reasoning path
1
Neural87.0%
Pattern matching & embedding similarity
2
Symbolic92.0%
Rule-based knowledge graph traversal
3
Fusion94.0%
Combined neural + symbolic reasoning
Query
> Why did revenue dip in Q3?
14 triples touched·3 microtheories
Bi-Temporal Knowledge Graph

Know what was true, when it was true, and when you learned it.

Every node and edge tracks two timelines — valid time and transaction time. Time-travel any query. Causal-path discovery, counterfactual queries, microtheory scoping, Merkle provenance.

AlicePaperModelFactDatasetAgentClaimObs
t_valid · 2026-05-19
Spiking Neurons

Process time the way brains do.

Nengo-inspired, Rust-native SNN engine. LIF, Izhikevich, STDP, BPTT. Ideal for tick streams, sensor data, and log anomaly detection.

Spike raster · neurons × time
live
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
1.4M
spikes/sec
<1ms
step latency
BPTT
training
By the numbers

Sub-millisecond search.
A brain in your binary.

0K
writes / sec
AkashaKV after WAL group commit. 1,673× the original. 30× Redis.
<0µs
P99 latency
Sub-millisecond reads. Sub-10ms vector search at 10K docs.
0M+
rows / sec / node
DataFusion + Arrow Flight analytics throughput.
0
tests in memory crates
Plus thousands more across kv, graph, analytics, reasoning.
What you get

One substrate. Six superpowers.

2024-Q1
n=100
2024-Q3
n=420
2025-Q2
n=1,200
2026-now
n=4,800
Bi-Temporal

Time-travel any query.

Every fact tracks valid time and transaction time. Know what you believed when.

KV
Vector
Graph
SQL
one
Unified

KV + Vector + Graph + SQL. No glue code.

One async API. Cross-modality joins. ANN inside SQL.

EWC protected92%
Replay buffer76%
Quarantined18%
Continual

Train forever. Never forget.

EWC, SI, Generative Replay, and a learning quarantine that rejects poison.

AES-256-GCM · keyed
BLAKE3 audit chain
OIDC + PKCE
Secure

AES-256-GCM. BLAKE3 audit chain. OIDC.

Multi-tenant from the kernel. Differential privacy guardrails. Air-gappable.

write commit1.6ms
vector search · 10K9.4ms
5-hop graph84ms
SQL · 1M rows212ms
Fast

630K writes/sec. Sub-10ms vector.

LSM-tree with WAL group commit, lock-free buffer, TinyLFU cache.

Smart

Self-improves while you sleep.

The cognitive cycle rewards pathways that work. Hebbian + decay.

Governance · Lineage

Every belief, traced to its source.

Knowledge lineage tracks how every fact was derived. Belief-taint tracking ensures untrusted sources cannot launder into Tier-1 recommendations. Auditable forgetting handles GDPR delete requests cryptographically.

governance/lineage · belief #b8f3a4 depths · 7 nodes
Depth 0
memory
interview transcript
5d ago
import
10-Q filing
5d ago
Depth 1
inference
extract entities
5d ago
inference
extract claims
5d ago
Depth 2
merge
deduplicate claims
4d ago
derivation
compute confidence
4d ago
Depth 3
derivation
Q3 revenue ↓ 12%
4d ago
memory
import
inference
merge
derivation
merkle: 0x4a8c…f81e · verified ✓
The Substrate · AkashaKV

The kernel underneath every memory.

Akasha is the cognitive database engine that makes Minds possible. An LSM-tree KV with WAL, MVCC, and lock-free buffers that hits 630K writes/sec — and the substrate every higher-level layer (memory, reasoning, learning) rides on.

akasha · architecture
L5
Interface · HTTP · gRPC · Arrow Flight · MCP
L4
Reasoning · HRM · Neurosymbolic · Cognitive Cycle
L3
Temporal · SNN · SSM/Mamba
L2
Memory · Episodic · Procedural · Working · Vault · Hopfield
L1
Storage · LSM-tree KV · WAL · MVCC · HNSW · Tantivy · DataFusion
L0
Isolation · AES-256-GCM · BLAKE3 audit · 7-action RBAC
Developer surface

One call. Five languages. Same answer.

Native SDKs for TypeScript, Python, Rust, and Go — plus the cogs CLI and the mind TUI control room. All five wrap the same daemon API.

hybrid recall — vector + graph + episodic
import { Minds } from "@minds-sdk/typescript";

const minds = new Minds({ apiKey: process.env.MINDS_KEY });

// Hybrid retrieval: vector + graph + episodic, one call.
const memories = await minds.recall({
  query: "Why did Q3 revenue dip?",
  modes: ["vector", "graph", "episodic"],
  timepoint: "2026-10-01",
  topK: 5,
});

for (const m of memories) {
  console.log(m.confidence, m.source, m.text);
}
TypeScript
13 modules
Python
sync + async
Rust
native client
Go
production-grade
cogs CLI
multi-instance
mind TUI
tiling control
Live · global mesh
14,832 agent actions reviewed today
alpha · recalled 14 episodes for 'q3 revenue'
beta · committed 412 triples to gnosis://eng
gamma · HRM plan · 6 subgoals · ACT stopped at step 4
delta · pathway 02→05 reinforced · Δreward +0.31
epsilon · 1,204 vectors indexed · HNSW ef=200
zeta · quarantine accepted 18 new facts · 2 rejected
eta · SNN ensemble 'tick-anomaly' spiked at t=8.4s
theta · MHN completion · 87% match · cue 'auth-flow'
alpha · recalled 14 episodes for 'q3 revenue'
beta · committed 412 triples to gnosis://eng
gamma · HRM plan · 6 subgoals · ACT stopped at step 4
delta · pathway 02→05 reinforced · Δreward +0.31
epsilon · 1,204 vectors indexed · HNSW ef=200
zeta · quarantine accepted 18 new facts · 2 rejected
eta · SNN ensemble 'tick-anomaly' spiked at t=8.4s
theta · MHN completion · 87% match · cue 'auth-flow'
iota · auditable-forget · 14 episodes · BLAKE3 verified
kappa · neurosymbolic · 92.4% fusion confidence
lambda · KG time-travel · t_valid 2024-Q1
mu · cognitive cycle 8f3a complete · 902ms
nu · working memory consolidation · 7 → 3 slots
xi · cross-tenant federation · 4 nodes agreed
omicron · ANN routing · 'embedding-similarity' selected
pi · DataFusion · 4.2M rows · 198ms
iota · auditable-forget · 14 episodes · BLAKE3 verified
kappa · neurosymbolic · 92.4% fusion confidence
lambda · KG time-travel · t_valid 2024-Q1
mu · cognitive cycle 8f3a complete · 902ms
nu · working memory consolidation · 7 → 3 slots
xi · cross-tenant federation · 4 nodes agreed
omicron · ANN routing · 'embedding-similarity' selected
pi · DataFusion · 4.2M rows · 198ms
Production-grade

Enterprise-ready the day you adopt it.

Multi-tenant from the kernel. Cryptographic provenance on every fact. OIDC + PKCE auth via Hydra. SOC 2 and ISO 27001 paths in flight.

AES-256-GCM at rest
Per-namespace keys via HKDF-SHA256.
TLS 1.3 in transit
rustls, no OpenSSL.
BLAKE3 audit chain
Tamper-evident, Merkle-anchored.
Multi-tenant isolation
tenant → reservoir → agent → dataspace.
Self-hostable
Run on-prem, in K8s, or air-gapped.
Differential privacy
Guardrails on analytics queries.
Manifesto

Don'tfine-tunetheLLM.Traintheagent.

Domain-specific intelligence belongs in the substrate that persists, not the weights that get replaced every six months. Minds gives your agent a brain it carries forward — across sessions, across model upgrades, across the lifetime of your company.

Pricing

Start free. Grow into a brain.

Free
$0/ month
Build your first mind.
  • 1 instance · shared cluster
  • 10K episodic memories
  • 100K vector embeddings
  • 100MB knowledge graph
  • Community Discord
Start free
Recommended
Team
$49/ month
For agents at work.
  • 5 instances · dedicated
  • Unlimited episodic memories
  • 10M vector embeddings
  • Bi-temporal graph · unlimited
  • HRM + Neurosymbolic
  • Continual learning + quarantine
  • Email support · 24h
Start trial
Enterprise
Custom
Brain at your scale.
  • Unlimited instances
  • Self-hosted or VPC-deployed
  • Air-gapped option
  • Federated ANN mesh
  • SOC 2 + ISO 27001
  • Dedicated solutions architect
  • Custom SLA · 99.99%
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