METIS INTELLIGENCE OS

The Intelligence Kernel for
Autonomous Agents

Stop flying blind. Metis Prism provides the governance, memory, and predictive intelligence needed to run mission-critical autonomous workloads in production.

Deploy AgentView Architecture
🔮

Semantic Pre-Flight

Stop Flying Blind.

Traditional barriers to autonomy are operational: You deliver a prompt, and pray it doesn't loop infinitely or hallucinate.

Foresight Intelligence analyzes your agent's plan before execution. It predicts token costs, latency, and success probability, acting as a "System 2" check on your agent's "System 1" generation.

97%
Cost Prediction Accuracy
<10ms
Pre-Flight Latency
# Foresight Pre-Flight Check
> Analyzing Plan...
[✓] Intent: "Database Migration"
[!] Risk Level: HIGH
[!] Cost Estimate: $4.50 (Exceeds budget)

>>> INTERCEPTED: Requesting Council Approval
Live Consensus
Worker_Agent_01
Proposing Action...
⬇️ Veto Check ⬇️
Council_of_Critics
REJECTED (Unsafe)
⚖️

Consensus as a Service

The Consensus Engine.

Don't let a single hallucinating model bring down your production workflow.

Metis Prism A2A (Agent-to-Agent) infrastructure enables a Consensus Engine mode. High-stakes actions are automatically routed to a diverse jury of critics (Safety, Skeptic, Policy) for a weighted vote before execution.

  • ✓ Zero-Touch Governance Injection
  • ✓ Protects Google ADK, AutoGen, & Custom Swarms
  • ✓ Veto-Priority Voting Logic
🧠

Hippocampus Memory

Infinite Context. Zero Latency.

RAG is brittle, and re-computing attention limits agent scale. Metis Prism Memory solves this by combining Vector Similarity (Short-Term) with Knowledge Graph Relations (Long-Term).

Crucially, Foresight predicts what enterprise context your agent needs next and injects it directly into the inference node as Pre-Filled KV Caches, cutting Time-To-First-Token (TTFT) to effectively zero.

Pre-filled KV CachesGraphRAGPII Scrubbing
# Memory Retrieval
> Context Needed: "Project A Timeline"

[+] Vector Match: "timeline_doc_v2.pdf" (0.89)
[+] Graph Relation: (Project A)-[:MANAGED_BY]->(User X)
[+] Pre-fetched: 12ms

>>> Context Configured.
🛡️

Aegis Active Defense

Security that moves faster than your agent. An active shield that neutralizes threats in real-time.

🛑

Prompt Injection Shield

Heuristic and model-based defenses block jailbreak attempts (DAN, Base64) before they reach the LLM.

🕵️

PII Scrubbing

Real-time masking of SSNs, emails, and API keys. Sensitive data never leaves your specialized boundary.

📜

Policy Enforcement

Policy Engine enforces budget caps ($5/day) and tool restrictions (No production DB delete).

Build Faster with the Kernel

The Metis Prism LLM Gateway acts as the universal adapter for your agentic codebase. Zero vendor lock-in. Maximum performance.

Smart Routing

client.chat.completions.create( model="auto", # Routing Magic max_cost=0.02 )

Auto-route to the cheapest capable model for the task, or fallback to ensure 100% uptime.

Advanced Caching

# 5x Faster Responses [HIT] Negative Semantic Cache [HIT] KV-State (Graph)

Negative Semantic Caching & KV-State routing means you never pay for the same mistake twice.

Universal Adapter

current_provider = "anthropic" # Switch instantly current_provider = "metis-hosted"

Deep integration with all frontier labs. Switch from GPT-4 to Claude to Llama with one line of config.