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EvolutionaryBrain

An AI That Learns from Every Outcome

39 agents with genuine OODA loops. Bayesian confidence from outcomes. Vector-embedded memory. Cross-tenant intelligence via k-anonymous skill federation.

39
AI Agents
1024d
Vector Memory
6
Agency Criteria
k=3
Anonymous Federation

Six Agency Criteria

Every agent must satisfy all six criteria to be considered genuinely agentic

Perception

Observes the environment through 42+ connectors, edge agents, and SIEM event lake

Reasoning

Embeds signals as 1024d vectors, retrieves similar past decisions, applies Bayesian confidence

Decision-Making

Risk-tiered autonomy: auto-execute LOW, confidence-gate MEDIUM, approve HIGH/CRITICAL

Action

Scoped ChangeSets with blast-radius assessment, DRY_RUN preview, tested rollback

Learning

Bayesian confidence updated from every outcome. Behavioral change tracked over time.

Communication

Evidence chain, PSA tickets, Observatory feed, cross-tenant skill federation

The Learning Loop

Every decision outcome makes the brain smarter

Step 1

Signal Arrives

HIBP breach, Defender alert, edge anomaly — any of 65+ signal types

  • Brain recalls: pgvector similarity search returns 5 most similar past decisions
  • Confidence computed: Bayesian update from prior outcome: P(action | signal) with historical success rate
Step 2

Action Executed

ChangeSet runs with DRY_RUN preview. Evidence sealed at each phase.

  • Outcome recorded: success/failure/partial + metrics (time-to-remediate, user impact, blast radius)
  • Pattern extracted: High-confidence patterns (95%+, 50+ successes) published via k-anonymous federation
Skill Federation

Cross-Tenant Intelligence with k-Anonymity

When a pattern is proven in 3+ tenants, it becomes fleet intelligence. No tenant data is ever exposed — only the anonymized pattern and its confidence score.

  • Local learning: Pattern discovered in Tenant A at 95%+ confidence
  • Anonymization: Tenant-specific data stripped, k-anonymity check
  • Publication: Pattern published to federation, 3+ tenants required
  • Import: Tenant B imports at 70% confidence in SIMULATION mode
  • Validation: Local data confirms pattern, confidence adjusts
  • Production: Pattern promoted to production at full confidence

The Glass Wall

Full transparency into every decision. The Observatory shows what the brain is thinking, why, and what it learned.

Decision Stream

Real-time feed of every brain decision with confidence, risk level, and reasoning chain

Confidence Trends

Track how confidence evolves over time for each signal type and action combination

Memory Explorer

Browse the vector memory: search by similarity, see clusters, understand what the brain remembers

Brain FAQ

AI That Gets Smarter Every Day

39 agents learning from every outcome. Bayesian confidence. Vector memory. Cross-tenant federation. The brain that never stops improving.