AI Calls Hari Ini
🤖
34,247
↑ +12%vs kemarin
Avg Accuracy
🎯
97.4%
↑ +0.3%vs bulan lalu
Avg Response
⚡
0.84 dtk
Target <1 dtk ✅
Total Agents
🤖
12
5 vertikal
Revenue AI (MTD)
💰
Rp 284jt
Savings + value
📈
AI Calls — Volume & Success Rate per Jam📊
Distribusi Calls per AgentOrder (40%)13,699 calls
CS (25%)8,562 calls
Inventory (15%)5,137 calls
Analytics (12%)4,110 calls
Finance (8%)2,740 calls
⚡
AI Decision FeedREALTIME
🤖
Order Agent: 847 order diproses otomatis jam ini — 100% sukses — 0 manual override
💬
CS Agent: Keluhan "paket belum sampai" — auto-track + kompensasi Rp 20rb — 2.1 dtk
📦
Inventory: Stok SKU-2847 kritis — PO auto-generated ke supplier — menunggu konfirmasi
🎯
Performance Gauge97.4%
Accuracy
0%100%
0.84s
Avg Response
03 dtk
📊
Accuracy Trend 7 Hari💰
Cost per Call per AgentActive Agents
🤖
12
5 kategori
Total Calls Today
📊
34,247
↑ +12%
Zero Downtime
⚡
99.97%
SLA 99.9% ✅
🤖
AI Agent Performance Matrix| Agent | Kategori | Calls Today | Accuracy | Avg Response | P95 Response | Error Rate | Cost/Call | Status |
|---|---|---|---|---|---|---|---|---|
| Order Agent | FnB · Retail | 13,699 | 99.8% | 0.42s | 0.89s | 0.2% | Rp 420 | OPTIMAL |
| CS Agent | Multi-vertikal | 8,562 | 98.2% | 0.68s | 1.24s | 1.8% | Rp 680 | OPTIMAL |
| Inventory Agent | Retail · FnB | 5,137 | 94.8% | 0.38s | 0.72s | 5.2% | Rp 380 | GOOD |
| Finance Agent | Multi-vertikal | 2,740 | 97.1% | 0.51s | 0.94s | 2.9% | Rp 510 | OPTIMAL |
| Analytics Agent | All verticals | 2,109 | 91.4% | 0.84s | 1.68s | 8.6% | Rp 840 | REVIEW |
🎯
Accuracy vs Volume — Agent Scatter🤖
Agent Health Monitor📊 Analytics Agent Accuracy Drop
Analytics Agent accuracy 91.4% — di bawah target 95%. Root cause: training data Q4 belum diupdate. Schedule retraining minggu ini.
Drift detected via monitoring
⚡ Order Agent Peak Optimization
Order Agent handle 3,500 calls/jam saat lunch peak — 100% sukses. Auto-scaling berhasil — zero queue.
AI Infra Cost (MTD)
⚡
Rp 8.4jt
Groq API + VPS
Avg Cost/Call
📊
Rp 547
↓ -12% vs bulan lalu
Value Generated
💰
Rp 284jt
Savings + revenue uplift
ROI AI Bulan Ini
🚀
33.8x
Value/Cost ratio
📊
Cost Breakdown AI InfrastructureGroq API (Llama 3.3 70B)Rp 4.8jt/bln (57%)
VPS & ServerRp 1.8jt/bln (21%)
Support & MonitoringRp 1.2jt/bln (14%)
Misc & ToolsRp 600rb/bln (7%)
Total Cost AI/BulanRp 8,400,000
Value Generated/BulanRp 284,000,000
ROI Ratio33.8x 🚀
💡
Cost Optimization AI🧠 Model Routing Opportunity
80% query simple bisa handle Llama 8B ($0.05/M) vs 70B sekarang ($0.59/M). Implementasi router → hemat 68% API cost = Rp 3.3jt/bln.
💾 Prompt Caching
System prompt 500 token di-cache → hemat 90% input token cost untuk repeated context. Estimasi saving: Rp 1.4jt/bln.
📦 Batch Processing
Laporan & rekap bisa async via Batch API (50% cheaper). 20% dari calls bisa di-batch → hemat Rp 840rb/bln.
Model Version
🧠
Llama 3.3 70B
Groq inference
Uptime
⚡
99.97%
SLA guaranteed
Tokens Used (MTD)
📊
142M tokens
Input + Output
🚀 System Status
Semua 12 AI agent berjalan optimal. Peak load 3,500 calls/jam saat lunch — auto-scale berhasil. Zero downtime bulan ini (99.97% uptime).
All systems green
📊 Model Performance Monitor
7-day accuracy trend: 94.2% → 97.4% (↑ +3.2%). Improvement driver: prompt optimization Order Agent dan training data refresh Inventory Agent.
⚠️ Analytics Agent Drift
Accuracy turun ke 91.4% (target 95%). Penyebab: data distribusi Q4 berbeda dari training set Q1-Q3. Action: retraining scheduled Senin.
💡 Next Optimization
Model routing implementation: 80% simple query → Llama 8B, 20% complex → 70B. Expected: cost -68%, latency -30%. Timeline: 2 minggu.
⚙️
Technical SpecsAI ModelLlama 3.3 70B (Groq)
Inference Speed800 tok/sec avg
Input Price$0.59/1M tokens
Output Price$0.79/1M tokens
Avg Tokens/Call650 in + 400 out
Cost/Call~Rp 547
Context Window128K tokens
BackendPHP 8.3 + Supabase
Cache Hit Rate72% (prompt cache)
VPSNevaCloud 20GB RAM