95%
कवरेज
कनेक्टेड मॉड्यूल / कुल
एजेंट दक्षता
Read-only aggregate: how AI OS routes agents (exam permissions + ledger success). No per-task detail.
0%
ताज़ा करें
टिकर ताजगी (0–15 मिनट की विंडो)
ऑफ़लाइन
AI उपयोग
मॉडल रनटाइम मीट्रिक (ऑफ़लाइन)
ऑफ़लाइन
कैश हिट
एज कैश अनुपात (ऑफ़लाइन)
Self-improving loop
AI OS continuously adjusts agent routing based on exam scores and real-world outcomes.
1
Exam
Agent takes offline exam → gets score per category
→
2
Score → Routing
Score determines which tasks the agent can handle
→
3
LLM राउटर
Router picks cheaper or better backend based on cost/quality
→
4
Effectiveness Ledger
Real outcomes tracked: success rate, blocker rate, cost
→
5
Learning → RAG
Next session starts with context from previous results
Effectiveness ledger offline — aggregates shown only where available.
Generated 2026-06-27T09:05:06.533252+00:00
- Agents tracked
- 0
- Tasks recorded
- 0
- Overall success
- —
- Tests pass rate
- —
- Avg est. cost
- —
| Agent | Exam total | Success rate | Blocker rate | Recommended lane |
|---|