Four-stage funnel cuts daily AI API cost from $60,000 to $393
A market analysis pipeline uses code filters, lightweight classifiers, Kimi K3's long context, and finally Astra bull-versus-bear agent debates to cut analytical compute spend.
SPENDING 60 000 DOLLARS A DAY ON AI API CALLS IS A FAST TRACK TO BANKRUPTCY Feeding raw market data straight into heavy reasoning models sounds great until you calculate the daily infrastructure cost for 10 000 tickers. The Sieve terminal uses a multi-tiered funnel that slashes analytical compute spend from 60 000 dollars to 393 dollars per day: Stage 1: Deterministic code filters 10 000 assets down to 800 anomalies using Z-scores and volume ratios. Stage 2: Lightweight classifiers compress the candidates down to 150 items. Stage 3: Kimi K3 uses its 1 million token context to cross-reference 8 quarters of filings for 40 companies. Stage 4: GPT-6 Astra pitting bullish versus bearish agents against each other on the top 8 assets before human review. Eight hours of manual analyst extraction compressed into fifteen minutes of high-density reading. Full funnel economics, token math, and pipeline architecture inside the article.
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