06 — Live Traction

This Isn't a Pitch Deck.
This Is Running Production Infrastructure.

Every number on this page is real. Every system is live. Every metric is independently verifiable via SSH, API, or Grafana dashboard. This is not a prototype, not a mockup, not a roadmap—this is a sovereign AI platform consuming AWS resources as you read this sentence.

752B

Total parameters running inference

1.15 TB

GPU VRAM allocated

125

Days of continuous development

External API dependency

Live System Metrics — Verified May 2026

Real Numbers. Real Infrastructure. Right Now.

Each metric below represents a live, running system on a single AWS p5en.48xlarge instance. The green pulse indicates active service status monitored via Prometheus.

19.2M

Knowledge Graph Nodes

Neo4j Enterprise 5.26 • 6 node types

78.6M

Graph Relationships

Traversable in <100ms • 14 rel types

622K

Redis Cache Keys

Sub-millisecond response • 2TB RAM

Vector Collections

Qdrant GPU HNSW • 4096-dim embeddings

Docker Containers

All monitored • Auto-restart on failure

Systemd Services

Autonomous 24/7 workers • Watchdog-guarded

72,485

Git Commits

580/day avg • Continuous integration

537K

Lines of Python

Production code • Type-hinted • Tested

4,095

Core Library Modules

api/lib/ • Enterprise patterns

932

API Router Files

FastAPI • Auto-documented • Live

1,233+

Development Sessions

Documented • Searchable • Compounding

AI Consulting Agents

Catalogued • API-accessible • Revenue-ready

Infrastructure Inventory

What's Running on AWS Right Now

A single p5en.48xlarge instance — 8x NVIDIA H200 GPUs, 1.15TB VRAM, 2TB RAM, 192 vCPUs. Everything below is live, monitored, and self-healing.

Component	Specification	Status	AWS Resource
Primary LLM	Qwen3.5-397B-A17B-FP8 • 262K context • Port 8010	Live	GPUs 0-3 (tp=4) • 560 GB VRAM
Critic LLM	GLM-4.7-355B-FP8 • 202K context • Port 8011	Live	GPUs 4-7 (tp=4) • 520 GB VRAM
Embedding Model	Qwen3-Embedding-8B • 4096 dimensions • Port 8014	Live	GPU 7 (shared) • ~16 GB VRAM
Reranker	Qwen3-Reranker-8B • Cross-encoder • Port 8015	Live	GPU 7 (shared) • ~16 GB VRAM
Knowledge Graph	Neo4j Enterprise 5.26 • 19.2M nodes • 78.6M rels	Live	EBS io2 persistent • Bolt 7687
Vector Store	Qdrant • 51 collections • GPU HNSW index	Live	NVMe + EBS • Ports 6333/6334
Relational DB	YugabyteDB • Distributed SQL • Strong consistency	Live	EBS persistent • Port 5433
Cache Layer	Redis • 622K keys • Sub-ms latency	Live	Instance RAM • Port 6379
Event Streaming	RedPanda • Kafka-compatible • Zero-copy	Live	NVMe local storage
API Server	FastAPI • 932 routers • 3,330+ endpoints	Live	Port 8000 • Auto-documented
Monitoring Stack	Grafana + Prometheus • 200+ dashboards	Live	Port 3002 • Real-time alerting
Total Storage	10TB EBS (persistent) + 28TB NVMe (cache)	Active	EBS io2 + 8x NVMe LVM RAID

Everything On This Page Can Be Independently Verified.

We don't ask you to trust us. We ask you to audit us.

🔑

SSH Access

Direct terminal access to the running instance. Inspect processes, query databases, check GPU utilization in real-time.

📊

Grafana Dashboards

200+ real-time monitoring dashboards. GPU utilization, inference throughput, database health, daemon status—all live.

⚡

Live API Endpoints

Hit the API right now. Get real responses from real models running real inference on real hardware. No mocks.

📝

Git History

72,485 commits. Every line of code, every session, every decision—documented and traceable from day one.

# Verify the AI agency is live and operational
$ curl https://genesis-api.myday7.com/api/v1/agency/health
{"status":"operational","catalog_size":71,"models_active":2,"uptime_hours":2988}

# Query the knowledge graph size directly
$ curl https://genesis-api.myday7.com/api/v1/system/metrics
{"neo4j_nodes":19247832,"neo4j_relationships":78612445,"redis_keys":622147,"qdrant_collections":51}

# List available AI consulting agents
$ curl https://genesis-api.myday7.com/api/v1/agency/agents | jq '.[0:3]'
[
  {"name":"Corporate Strategy Agent","status":"ready","specialization":"M&A, market entry, competitive positioning"},
  {"name":"Growth Strategy Agent","status":"ready","specialization":"Revenue optimization, market expansion, scaling"},
  {"name":"Financial Analysis Agent","status":"ready","specialization":"Modeling, forecasting, capital allocation"}
]

# Verify GPU utilization (live inference happening right now)
$ curl https://genesis-api.myday7.com/api/v1/system/gpu-status
{"gpus":[
  {"id":0,"model":"H200","vram_used_gb":138.2,"utilization_pct":67,"process":"qwen3.5-397b"},
  {"id":1,"model":"H200","vram_used_gb":138.2,"utilization_pct":64,"process":"qwen3.5-397b"},
  {"id":2,"model":"H200","vram_used_gb":138.2,"utilization_pct":71,"process":"qwen3.5-397b"},
  {"id":3,"model":"H200","vram_used_gb":138.2,"utilization_pct":69,"process":"qwen3.5-397b"},
  {"id":4,"model":"H200","vram_used_gb":128.7,"utilization_pct":45,"process":"glm-4.7-355b"},
  {"id":5,"model":"H200","vram_used_gb":128.7,"utilization_pct":42,"process":"glm-4.7-355b"},
  {"id":6,"model":"H200","vram_used_gb":128.7,"utilization_pct":48,"process":"glm-4.7-355b"},
  {"id":7,"model":"H200","vram_used_gb":144.9,"utilization_pct":53,"process":"glm-4.7+embed+rerank"}
]}

Development Velocity

The Output of 186 Autonomous AI Workers

Genesis doesn't sleep. 186+ autonomous agents operate 24/7, writing code, running tests, fixing bugs, and improving the system—all without human intervention. The velocity numbers below represent actual git commit history, independently verifiable.

580

Commits Per Day

72,485 total commits across 125 days of development. Every commit is atomic, tested, and meaningful.

36–182

Developer Equivalents

Industry average: 3.2 commits/dev/day. Our output equals a team of 36 to 182 professional engineers.

186+

Autonomous Workers

AI agents operating 24/7. Daemons, miners, guardians, healers—each with a specific mission, all coordinated.

24/7

Continuous Operation

The system improves while the founder sleeps. Every daemon, every agent, every process—running on AWS.

4,296

Lines Written Per Day

537,000 lines of production Python, growing every hour. Type-hinted, docstring'd, enterprise-grade.

Human Founder

One person. One vision. Orchestrating an army of AI that outproduces entire engineering departments.

Resilience Under Fire

Involuntary Chaos Engineering — And Genesis Passed Every Test

AWS spot instances are designed to be interrupted. Most startups would lose everything. Genesis treats every interruption as a resilience drill—and has never lost a single byte of data.

Spot Instance Terminations Survived

AWS pulled the hardware out from under us thirteen times. Thirteen times, Genesis recovered automatically. Full state restoration, zero human intervention required.

233

Failed Launch Attempts Overcome

233 times AWS couldn't fulfill our instance request. 233 times the system queued, waited, retried, and eventually launched—without losing a single job or context.

Bytes of Data Lost

Zero. Across all 13 terminations, all 233 failed launches, across months of continuous operation. EBS persistence, systematic backups, and self-healing architecture make data loss architecturally impossible.

<12

Minutes to Full Recovery

From cold start to full production: all models loaded, all databases online, all daemons running, all services healthy. Under twelve minutes. Every time.

100%

Recovery Success Rate

Not 99.9%. Not "five nines." One hundred percent. Every termination recovered. Every launch eventually succeeded. The system has never been permanently down.

This Isn't Vaporware. This Isn't a Roadmap.
This Is Live.

752 billion parameters running inference right now. 19.2 million knowledge nodes being traversed right now. 78.6 million relationships powering intelligence right now. 91 autonomous services working right now. On H200 GPUs. On AWS. As you read this.

The question isn't whether this technology works.
The question is what happens when it's properly capitalized.