The Problem: Lenders and brokers in the Merchant Cash Advance (MCA) space waste thousands of hour...The Problem: Lenders and brokers in the Merchant Cash Advance (MCA) space waste thousands of hour...
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Nicholas Iazzetta
• Aug 15
The Problem: Lenders and brokers in the Merchant Cash Advance (MCA) space waste thousands of hours manually extracting Average Daily Balances (ADB) and gross deposits from unstructured, messy bank statement PDFs.
The Solution: Macram is a high-throughput AI SaaS that automates this entire process. It ingests raw bank documents and runs them through a custom 10-stage LLM pipeline to instantly output a flawless financial underwriting matrix.
Technical Highlights:
Advanced LLM Orchestration: Built a multi-model pipeline using Anthropic's Claude Haiku for fast data chunking/minification and Sonnet for complex synthesis.
Deterministic Output: Engineered a state machine that forces unstructured OCR text into strictly typed JSON fragments and accurate financial calculations.
High-Concurrency Architecture: Designed a custom concurrency "Valve" to process heavy document loads simultaneously without triggering provider rate-limit crashes.
b2bfintechautomation
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Nugraha
• 2d
@Nicholas Iazzetta Using Haiku for chunking and Sonnet for synthesis is a practical split. How does the typed JSON state machine handle low-quality OCR or conflicting transaction totals?
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