The unified, enterprise-grade distributed agent runtime uniting Super-Memory (Bi-Temporal GraphRAG), Cyclical Swarm Orchestration, 24/7 Durable Daemons, Multimodal Streaming, and Critical Systems VLA Safety Governors.
Key Features • Competitive Matrix • Quickstart • Architecture • MCP Server Setup • Benchmarks
Most AI agent frameworks are either:
- Stateless prompt chains that hallucinate when context grows (naive vector RAG).
- Fragile Python loops that crash, drop state, or leak memory during 24/7 background execution.
- Unconstrained probabilistic actors dangerous to deploy to physical actuators, robotics, or critical production infrastructure.
Hyper-Agent OS solves this by unifying a Bi-Temporal Graph Memory (surpassing Cognee), Cyclical State Graphs (LangGraph-style) with Byzantine Quorums, Temporal-grade Durable Execution, Sub-100ms Multimodal Streaming, and Deterministic Control Barrier Functions (CBF).
| Feature | Hyper-Agent OS | Cognee | LangGraph | CrewAI | Naive Vector RAG |
|---|---|---|---|---|---|
| Bi-Temporal Knowledge Graph | ✅ Yes | ❌ No | ❌ No | ❌ No | ❌ No |
| Point-in-Time Rollback (Anti-Hallucination) | ✅ Yes | ❌ No | ❌ No | ❌ No | ❌ No |
| 3D Spatial & Multimodal Embeddings | ✅ Yes | ❌ No | ❌ No | ❌ No | |
| Cyclical State Graphs & Interrupts | ✅ Built-in | ❌ No | ✅ Yes | ❌ Linear | ❌ No |
| Byzantine Fault Tolerant Swarm Quorum | ✅ BFT Quorum | ❌ No | ❌ No | ❌ No | ❌ No |
| 24/7 Durable Replay (Temporal Pattern) | ✅ SQLite Journal | ❌ No | ❌ No | ❌ No | |
| Sub-100ms Voice Stream + Barge-In | ✅ Yes | ❌ No | ❌ No | ❌ No | ❌ No |
| Critical Safety Governors (CBF) | ✅ Deterministic | ❌ No | ❌ No | ❌ No | ❌ No |
| Post-Quantum Attestation Receipts | ✅ Aegis/SHA-256 | ❌ No | ❌ No | ❌ No | ❌ No |
| Built-in SWE-bench & MLE-bench Eval | ✅ Yes | ❌ No | ❌ No | ❌ No | ❌ No |
| Model Context Protocol (MCP) Server | ✅ Native | ❌ No | |||
| Drop-in Cognee Migration Shim | ✅ 1-Line Import | N/A | ❌ No | ❌ No | ❌ No |
┌────────────────────────────────────────┐
│ Hyper-Agent OS / Runtime │
└───────────────────┬────────────────────┘
│
┌──────────────────────┬──────────────────────┼──────────────────────┬──────────────────────┐
▼ ▼ ▼ ▼ ▼
[ 1. Memory Substrate ] [ 2. Swarm Core ] [ 3. 24/7 Daemon ] [ 4. Streaming ] [ 5. Safety & VLA ]
• Bi-Temporal Graph • LangGraph DAG • Durable Loops • WebRTC/Audio Stream • Control Barrier Func
• Vector Index • CrewAI Swarms • Event Bus (PubSub)• Video Keyframe Pipe • Actuation Envelope
• Spatial Scene Graph • Role Consensus • Self-Healing • Real-Time VAD/TTS • Deterministic Reject
│
▼
[ 6. Benchmark Evaluation Suite ]
• SWE-bench Verified & Multimodal Runner
• MLE-bench (Kaggle) Evaluation Adapter
• ARC Reasoning & Tool Execution Harness
git clone https://github.com/AAH20/hyper-agent-os.git
cd hyper-agent-os
pip install -e .# Run live end-to-end demonstrations across all 6 subsystems
hyper-os all
# Or run individual subsystems
hyper-os memory
hyper-os swarm
hyper-os daemon
hyper-os streaming
hyper-os safety
hyper-os benchmarkpython3 -m unittest discover -s tests -p "test_*.py" -vMigrate from Cognee in one line of code:
from hyper_agent_os.adapters import CogneeCompat
cognee = CogneeCompat()
# Ingest unstructured text or code
cognee.add_sync([
"QuantumController coordinates RobotArmAlpha.",
"RobotArmAlpha is governed by ControlBarrierFunction."
])
# Extract and cognify into the bi-temporal graph
cognee.cognify_sync()
# Multi-hop hybrid graph retrieval
results = cognee.search_sync("What governs RobotArmAlpha?", subject="RobotArmAlpha")
print(results)Connect Hyper-Agent OS directly to Cursor, Windsurf, Claude Desktop, or Antigravity:
{
"mcpServers": {
"hyper-agent-os": {
"command": "python3",
"args": ["-m", "hyper_agent_os.mcp_server"],
"env": {}
}
}
}hyper_query_memory: Query the Bi-Temporal Knowledge Graph & Multimodal index.hyper_assert_fact: Commit persistent facts with cryptographic audit attribution.hyper_run_swarm: Launch autonomous collaborative swarm workflows.hyper_evaluate_cbf_safety: Certify and project actuator commands onto safe operational envelopes.
Run Hyper-Agent OS as an autonomous background daemon with persistent SQLite journaling:
docker compose up -dHyper-Agent OS includes built-in harnesses for the industry's most demanding AI benchmarks:
- SWE-bench Verified & Multimodal:
- Tests patch generation against real GitHub repository issues.
- Evaluates whether unit test failures flip to pass (
FAIL_TO_PASS) without regressing existing tests.
- MLE-bench (OpenAI / Kaggle):
- Evaluates end-to-end Machine Learning pipelines on Kaggle competitions.
- Automatically grades models into Bronze, Silver, or Gold Medal tiers.
- ARC Prize (Abstraction and Reasoning Corpus):
- Measures out-of-distribution reasoning and visual grid program synthesis.
Add these exact topics in your GitHub repository settings to maximize search indexing:
ai-agents, graphrag, knowledge-graph, bi-temporal-memory, langgraph,
crewai, swarm-intelligence, mcp, model-context-protocol, swe-bench,
mle-bench, autonomous-agents, durable-execution, voice-agent, vla,
robotics, control-barrier-functions, post-quantum, devin-alternative, rag
Developed by Ahmed Hassan (Founder, A2Z SOC).
Licensed under the Apache-2.0 License.