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Tekan Main Demo untuk lihat bagaimana Penghalaan Pintar jimat 87% token berbanding AI ulang 100 kali.
Demo Lengkap 87% Token Kecekapan Dicapai
01 WhatsApp Arahan
02 Analisis Keperluan
Mode
Token Kecekapan Kajian
Menunggu Sedang aktif Selesai
03 Penjanaan Skrip Python
1
π₯
Load bank penyata100 sets daripada different PKS & bank formats
2
ποΈ
Segment by formatGroup by bank type, detect common corak
3
π
Route intelligentlyRules engine (1.2k) β AI (4-9k) β Manusia (rare)
4
π
Generate penyataHasil 100 kewangan reports dengan 87% fewer tokens
import json, csv
BATCHES = ['maybank.csv','cimb.csv','bni.csv'] # segmented by bank
ROUTES = {'rules': {'tokens': 2000, 'pct': 72},
'ai': {'tokens': 6500, 'pct': 23},
'human': {'tokens': 12000,'pct': 5}}
def route_statement(stmt):
if stmt['format'] in ('standard','known'):
return 'rules' # ~1.2-2.8k tokens
if stmt['anomaly_score'] > 0.7:
return 'human' # ~12k tokens
return 'ai' # ~4-9k tokens
def process_batch(batch):
total = 0
for stmt in batch:
route = route_statement(stmt)
total += ROUTES[route]['tokens']
stmt['route'] = route
return total
all_statements = [s for b in BATCHES for s in csv.DictReader(open(b))]
total = process_batch(all_statements)
print(f"Total tokens: {total} (vs 7.5M baseline)")
print(f"Efficiency: {round((1 - total/7500000)*100)}% saved")
04 Rajah Blok
Menunggu Sedang aktif Selesai
05 Seni Bina Sistem
Penghalaan Pintar architecture: Input β Segment β Route β Process β Hasil. AI hanya untuk kes kompleks.
β‘ Rules Enjin
1.2kβ2.8k tokens
Standard transactions, known bank formats 72% of all PKS
π€ Selective AI
4kβ9k tokens
Kompleks corak, ambiguous entries 23% of PKS
π€ Semakan Manusia
~12k tokens (rare)
High-risk or exceptions 5% of PKS
β οΈ Rules engine mesti dikemaskini secara berkala untuk bank formats baru. AI fallback handle sisanya.
06 Langsung Token Perbandingan
Mula Simulasi
π Ejen AI One-by-One
0 tokens
PKS: 0/100
π§ Detached + Penghalaan Pintar
0 tokens
PKS: 0/100
07 Sistem Report
Itu smartest AI sistem is bukan itu one itu uses itu most tokens.
It is itu one itu knows precisely when dan how to use them.
Log Terminal
[SISTEM] AINNA Token Orchestrator sedia
Seni Bina Sistem
π± Lapisan Arahan
Arahan WhatsApp
100 PKS bank penyata
π€ Lapisan Ejen
Penyata segmentation
Penghalaan Pintar logik
Token optimization
β‘ Pelaksanaan Lapisan
Rules engine (72%)
Selective AI (23%)
Manusia review (5%)
Nota Keselamatan
- Rules engine perlu dikemaskini untuk bank formats baru secara berkala.
- AI fallback handle kes yang rules tak dapat proses jangan skip.
- Manusia review wajib untuk transaction high-risk atau anomaly >0.7.
- Token counts adalah estimate kasar actual bergantung pada model dan prompt.