earthy-document

byMaulik Radadiya

📘 SCOPE OF WORK (SOW) UD-AI Platform for Form Updates – Phase 1 Implementation 1️⃣ Project Objective To design and implement a Private, Secure, AI-Powered Document Processing Platform that: Automates document ingestion Performs OCR with primary + fallback engine Extracts structured data Prefills onboarding forms (HOA Invest / FormUpdates) Integrates with DocuSign Provides LLM-based validation & intelligence Ensures full auditability, security, and tenant isolation 2️⃣ Project Phases (Timeline-Ready Structure) 🔹 PHASE 1 – Architecture & Infrastructure Setup Deliverables: Final system architecture design Microservices structure definition LLM Gateway architecture design OCR service architecture (Primary + Fallback) AWS infrastructure setup (VPC, IAM, S3, Aurora) Dev / Staging environments Teams Involved: Solution Architect DevOps Backend Lead LLM Engineer Dependency: Must be completed before core implementation begins. 🔹 PHASE 2 – Document Ingestion Pipeline Scope: File upload APIs (Web + Mobile) Pre-signed S3 upload flow Metadata generation Document ID creation Event-driven ingestion (SQS/SNS) Secure object storage Versioning Deliverables: Document upload service Encrypted storage layer Event trigger mechanism Ingestion audit logging Can Run Parallel With: Infrastructure finalization (late stage) 🔹 PHASE 3 – OCR Engine Implementation Scope: Primary OCR: AWS Textract integration API error handling Response parsing Block/Line/Table extraction Bounding box extraction Page tracking Fallback OCR: PaddleOCR / Donut setup Failover logic Health-based provider selection Enhancements: Image preprocessing (deskew, rotate, contrast) Multi-page PDF handling OCR quality scoring Deliverables: OCR Microservice Provider failover logic Confidence scoring mechanism OCR metrics dashboard Dependency: Requires ingestion pipeline 🔹 PHASE 4 – Structured Data Extraction & Normalization Scope: Driver License extraction module State-specific DL format detection Bank statement classification Account type detection (Individual vs Corporate) Name, Address, DOB extraction Balance & maturity extraction Address normalization (libpostal) Date & currency normalization Confidence scoring per field Field-level source tracking Deliverables: Extraction engine (Regex + NLP) Normalized structured schema Confidence-based tagging Schema enforcement layer Dependency: OCR output 🔹 PHASE 5 – LLM Gateway & AI Intelligence Layer Scope: Multi-provider abstraction layer OpenAI integration AWS Bedrock integration Unified request/response schema Token counting Cost tracking Latency tracking Retry & failover logic Prompt versioning Response normalization AI Functional Scope: Field validation Missing data detection Document summarization Recommendation engine Explainability layer Deliverables: LLM Gateway microservice AI performance monitoring Provider health monitoring Can Run Parallel With: Extraction engine development 🔹 PHASE 6 – Form Prefill & Application Integration Scope: API integration with HOA Invest API integration with FormUpdates Prefill contact/account details Review layer before signing Human-in-the-loop validation logic Auto-apply high confidence rules Deliverables: Prefill API endpoints Confidence threshold logic UI support for field highlighting Source trace display Dependency: Extraction + LLM validation complete 🔹 PHASE 7 – DocuSign Integration Scope: OAuth integration Envelope creation Signer role detection Routing order configuration Executed PDF storage Association linking Deliverables: Automated signing workflow Signed document storage Audit trail for signing Dependency: Prefill + workflow complete 🔹 PHASE 8 – Security, Compliance & Audit Layer Scope: RBAC implementation Tenant isolation Encryption (KMS) Audit logs (user, tenant, model, hash) Prompt/output retention policies Customer-managed keys support Deliverables: Compliance-ready logging Audit dashboard Security validation report Runs Throughout Project 🔹 PHASE 9 – Monitoring, Metrics & Observability Scope: OCR latency monitoring LLM latency & cost tracking Confidence distribution tracking Failover monitoring AI performance dashboard Deliverables: Centralized monitoring dashboard Cost visibility reports AI metrics reporting Final stabilization phase