TRINOVION AGI View Live Demo →
SYSTEM ONLINE · ALL 41 AGENTS ACTIVE

Arıx1
The World's First
Self-Learning DevOps Intelligence

41 autonomous agents. Zero human intervention. Getting smarter with every deploy.

61
Deployments
94.3%
Success Rate
89
Patterns Learned
33s
Pipeline Speed
SCROLL
── Live from Production API

The Numbers Don't Lie

Real-time data pulled directly from the ARIX1 production system. No demos, no screenshots — live.

🚀
Total Deployments
0
Across all monitored repos
Success Rate
Pipeline completions
🧠
Patterns Learned
0
Knowledge base entries
Risk Score Trend
Calculated from all deploys
── Real Incidents · Live from API

AGI in Action

These are real incidents detected, diagnosed, and resolved by ARIX1 — without a single human paged.

Loading incidents from API...
── Knowledge Base · Live

What AGI Learned

Every deployment, incident, and near-miss is encoded into ARIX1's knowledge graph. These are the top patterns guiding future decisions.

Loading knowledge base...
── 41 Autonomous Specialists

Meet the Agent Squad

Six key specialists from a team of 41. Each has a personality, a purpose, and a track record.

🧠
The Orchestrator
GENERAL · orchestration
Coordinates all 41 agents in parallel. Assigns tasks, resolves conflicts, and signs off on every deployment decision.
🛡️
The Guardian
SECURITY · vulnerability scanner
Caught 3 dependency vulnerabilities before they reached production. Blocked 2 deploys with exposed secrets.
🔮
The Oracle
RISK ASSESSMENT · ML model
Predicts deployment risk using 47 signals. Accuracy improved from 73% to 91% over 15 days of self-training.
🔍
The Detective
INCIDENT RCA · root cause
Diagnosed a memory leak in 4 minutes that a senior engineer spent 2 days investigating. Zero false positives.
📚
The Professor
LEARNING · knowledge engine
Built 89 patterns from 61 deployments. Feeds learnings back into The Oracle every 6 hours to sharpen risk predictions.
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The Launcher
DEPLOYMENT · canary manager
Executes canary rollouts, monitors error rate thresholds, and triggers auto-rollback in under 3 seconds if needed.
── The Numbers That Matter

Why ARIX1
Changes Everything

AI agents vs competitors
0 vs 0
ARIX1 ships with 41 pre-trained autonomous agents. Every competitor ships with zero. You don't configure them — they just work.
DevOps AI market size
$10.4B → $25.5B
The DevOps AI market is growing at 19.8% CAGR. ARIX1 is positioned to lead the self-healing infrastructure category by 2028.
Time to deploy safely
23 min → 33s
Traditional deployment reviews take 23 minutes on average. ARIX1 completes a full 41-agent analysis in 33 seconds.
Engineering hours saved
0h
342 engineering hours saved this month. At $150/hr, that's $51,300 in recovered developer time — from a single team.
Deployments protected
0
324 deployments analyzed and protected from silent failure, security vulnerabilities, and compliance violations since launch.
── AI Brain Roadmap

The Path to Full AGI Autonomy

Three stages from advisory intelligence to narrow autonomous action — each unlocked only once the prior stage proves reliable in production.

LIVE NOW
🧠
AI Brain — Advisory Intelligence
Reads live deployment, risk, security, and incident data and answers questions in plain language. Learns from every deployment via a growing knowledge base. Humans approve every real decision.
Talk to Brain →
COMING NEXT
💡
AI Brain — Recommended Decisions
The Brain will surface a specific recommendation alongside every PRR and deployment decision — approve, block, or escalate — with full reasoning shown. The human still makes the final call.
Coming Next
LONG-TERM VISION
AI Brain — Narrow Autonomous Action
Starting with low-stakes, reversible actions — like auto-dismissing known-safe, previously-seen test patterns in incident triage. Higher-stakes actions like deployment approval, security response, and credential rotation remain human-gated. Autonomy expands only as each prior stage proves reliable in production.
Long-Term Vision
── Ready to see it live?

The Future of DevOps
is Already Running

Live system. Real data. 41 agents standing by.