AI-Driven Document Parsing and Analysis System
Budget: ₹75,000 – ₹150,000 INR
AI-Based Batch Document Processing System (with Manual Review Dashboard)
Overview
We are looking for an experienced AI / Backend Engineering team or freelancer to build a production-grade AI document processing system.
The system will process multiple vendor document types in batch mode, extract structured data using AI, and expose APIs for downstream consumption. A web-based operations dashboard with manual review capability is required.
This is not a PoC — we expect clean architecture, maintainable code, and enterprise-ready delivery.
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Scope of Work
1. Document Ingestion
• Batch ingestion of documents from Amazon S3
• Support for multiple document types (Invoices, POs, GRNs, Delivery Notes)
• Scheduled batch execution (hourly/daily)
• Error handling & retries
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2. AI-Based Processing
• Document classification (vendor + type)
• OCR and layout-aware field extraction
• Vendor-specific field mapping
• Confidence scoring per field
• Routing low-confidence documents to manual review queue
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3. Data Storage
• SQL database (PostgreSQL / MySQL)
• PO-centric normalized schema
• Audit logs and batch metadata
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4. APIs
• REST APIs to fetch consolidated data by PO number
• JSON response format
• Pagination and basic filters
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5. Web Dashboard (Mandatory)
• Processed documents queue
• Manual review queue
• Document viewer
• Field-level editing & approval
• Role-based access (Admin / Reviewer / Viewer)
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Technical Preferences
• Backend: Python / Node.js
• Frontend: React / Next.js
• Cloud: AWS
• AI: OCR + LLM-based extraction
• Processing: Batch only (no real-time)
⸻
Deliverables
• Deployed solution
• Source code & documentation
• Database schema
• API documentation
• Deployment instructions
Pricing Model
Please propose your estimate under one or both of the following:
1. Client-hosted deployment (client pays cloud & AI usage)
2. Vendor-managed SaaS model (monthly pricing)
Clearly mention:
• One-time implementation cost
• Estimated monthly operating cost
• Assumptions (volume, vendors, fields)
Proposal Requirements (Important)
To be considered, please include:
1. Relevant experience with AI document processing
2. Sample projects or GitHub links
3. Proposed architecture (high-level)
4. Commercial estimate
5. Post-delivery support / AMC details
Overview
We are looking for an experienced AI / Backend Engineering team or freelancer to build a production-grade AI document processing system.
The system will process multiple vendor document types in batch mode, extract structured data using AI, and expose APIs for downstream consumption. A web-based operations dashboard with manual review capability is required.
This is not a PoC — we expect clean architecture, maintainable code, and enterprise-ready delivery.
⸻
Scope of Work
1. Document Ingestion
• Batch ingestion of documents from Amazon S3
• Support for multiple document types (Invoices, POs, GRNs, Delivery Notes)
• Scheduled batch execution (hourly/daily)
• Error handling & retries
⸻
2. AI-Based Processing
• Document classification (vendor + type)
• OCR and layout-aware field extraction
• Vendor-specific field mapping
• Confidence scoring per field
• Routing low-confidence documents to manual review queue
⸻
3. Data Storage
• SQL database (PostgreSQL / MySQL)
• PO-centric normalized schema
• Audit logs and batch metadata
⸻
4. APIs
• REST APIs to fetch consolidated data by PO number
• JSON response format
• Pagination and basic filters
⸻
5. Web Dashboard (Mandatory)
• Processed documents queue
• Manual review queue
• Document viewer
• Field-level editing & approval
• Role-based access (Admin / Reviewer / Viewer)
⸻
Technical Preferences
• Backend: Python / Node.js
• Frontend: React / Next.js
• Cloud: AWS
• AI: OCR + LLM-based extraction
• Processing: Batch only (no real-time)
⸻
Deliverables
• Deployed solution
• Source code & documentation
• Database schema
• API documentation
• Deployment instructions
Pricing Model
Please propose your estimate under one or both of the following:
1. Client-hosted deployment (client pays cloud & AI usage)
2. Vendor-managed SaaS model (monthly pricing)
Clearly mention:
• One-time implementation cost
• Estimated monthly operating cost
• Assumptions (volume, vendors, fields)
Proposal Requirements (Important)
To be considered, please include:
1. Relevant experience with AI document processing
2. Sample projects or GitHub links
3. Proposed architecture (high-level)
4. Commercial estimate
5. Post-delivery support / AMC details