SBA
LOANS
HQ
Multi-tenant SBA lending SaaS for U.S. acquisition financing — AI document processing with AWS Textract OCR and Google Gemini, stage-based automation on AWS Lambda, and DocuSeal-powered e-signature flows. Higher revenue, lower ops drag, fully visible pipelines.
"One system for the whole loan lifecycle — brokers, borrowers, and lenders in sync."
SBA Loans HQ is a U.S. consultancy focused on acquisition financing; the business lived in email threads, spreadsheets, and a patchwork of third-party tools with little shared visibility. I led delivery of a production-grade SaaS platform that centralizes deals, documents, and communication in a single workflow. The result is a scalable, multi-role product that replaces manual follow-ups with stage-based automation and gives every stakeholder a live view of progress.
I owned full-stack architecture and delivery as team lead: Next.js front end, Django REST API, PostgreSQL on RDS, and AWS for compute, storage, and document processing. Migrated document storage and automation off brittle connector stacks into first-party services; aligned eng with loan operations so business rules shipped as reliable product behavior. This work was delivered with Arithmiks as the consulting partner to SBA Loans HQ.
hover to explore
SBA LOANS HQ system architecture: Browser (Redux · JWT); Next.js 16 (Pages Router · SSR); Nginx (TLS · Certbot); Django + DRF (JWT · RBAC · v0/); Redis (Broker + Results); Celery (Workers · Beat); PostgreSQL (psycopg2 · MatViews); AWS S3 (boto3 · 3 Buckets); AWS Textract (OCR Engine); Gemini 1.5 (google-genai SDK).
Connections: Browser → Next.js 16 (HTTPS); Next.js 16 → Nginx (HTTP/2); Nginx → Django + DRF (proxy_pass :8000); Django + DRF → Redis (Task.delay()); Django + DRF → PostgreSQL (psycopg2 ORM); Django + DRF → AWS S3 (pre-signed URL); Redis → Celery (BRPOP); Celery → PostgreSQL (save results); Celery → AWS S3 (multipart PUT); Celery → AWS Textract (boto3 client); AWS Textract → Gemini 1.5 (OCR chunks).
Problem Framing & Consolidation
Mapped how brokers actually worked: fragmented email, inconsistent file intake, no single pipeline view, and recurring manual nudges across the loan lifecycle. Defined a product boundary that replaced ad-hoc spreadsheets and generic CRMs with structured deal records, role-based access, and audit-friendly document handling — grounded in how SBA consulting actually closes deals.
AI & Event-Driven Automation
Layered in AI and OCR so the platform does more than CRUD: Gemini for summarization, intelligent file naming, and lead scoring; AWS Textract to pull structured data from complex financial PDFs. Built a custom automation path with stage-based bundles, outbound email via Postmark, and serverless hooks on Lambda so milestones drive the right requests and updates without Zapier-style glue.
Platform Delivery & Observability
Shipped a multi-tenant experience for partners, borrowers, lenders, and external requesters: Kanban and table views for the pipeline, an S3-backed vault that requests the right documents per stage, a memorandum section for underwriting narrative alongside live collaboration, DocuSeal for in-portal e-sign, and threaded per-deal chat to cut email noise. Added a super-admin analytics surface (ApexCharts) plus Mixpanel and GA4/GTM for product telemetry, and a database-backed error logger with full user context for production debugging.