You will get a document extraction pipeline using OCR & AI
Project details
will build a document extraction pipeline using Object Detection (OD) and Optical Character Recognition (OCR). This system converts unstructured files—such as invoices, receipts, ID cards, and forms—into clean, structured, machine-readable data.
The pipeline covers ingestion, preprocessing (de-skew, noise removal), region detection, OCR, post-processing, validation, and export in your preferred format (CSV, JSON, or database). You’ll get a production-ready solution tailored to your documents.
What you get:
OD + OCR pipeline ready for deployment
Support for multiple doc types
High-accuracy extraction with rules/validation
Scalable setup for small or large volumes
Secure handling of sensitive data (KYC, IDs, finance)
Clean outputs for direct integration
Why choose this service?
Accurate & reliable, tuned for precision/recall
Flexible (Python, PHP, or JS stack)
Scalable from POCs to enterprise workloads
Secure with encryption & PII redaction
Affordable pricing without cutting corners
Perfect for: automating data entry, KYC onboarding, table extraction from PDFs, and cleaning documents for analytics.
The pipeline covers ingestion, preprocessing (de-skew, noise removal), region detection, OCR, post-processing, validation, and export in your preferred format (CSV, JSON, or database). You’ll get a production-ready solution tailored to your documents.
What you get:
OD + OCR pipeline ready for deployment
Support for multiple doc types
High-accuracy extraction with rules/validation
Scalable setup for small or large volumes
Secure handling of sensitive data (KYC, IDs, finance)
Clean outputs for direct integration
Why choose this service?
Accurate & reliable, tuned for precision/recall
Flexible (Python, PHP, or JS stack)
Scalable from POCs to enterprise workloads
Secure with encryption & PII redaction
Affordable pricing without cutting corners
Perfect for: automating data entry, KYC onboarding, table extraction from PDFs, and cleaning documents for analytics.
Programming Languages
PHP, JavaScript, PythonCoding Expertise
Cross Browser & Device Compatibility, Performance Optimization, DesignWhat's included
| Service Tiers |
Starter
$150
|
Standard
$200
|
Advanced
$250
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 14 days |
Number of Revisions | 2 | 3 | Unlimited |
Number of Pages | 24 | 100 | 500 |
Design Customization | - | - | - |
Content Upload | |||
Responsive Design | - | - | - |
Source Code | - |
Frequently asked questions
About Fakhar Imam
AI Agent Developer | RAG Systems & LLM Automation | Python
Gilgit, Pakistan - 4:42 am local time
The problems I solve:
Information silos: Your team wastes hours digging through drives and legacy docs. I build RAG chatbots that answer instantly from your PDFs and SOPs, with cited sources.
Repetitive task bottlenecks: I engineer autonomous agents (LangGraph, CrewAI, LangChain) that reason through tasks, trigger backend actions, and plug into your CRM.
Unstructured data traps: Thousands of scanned forms, invoices, or medical records? My OCR and vision pipelines (LayoutLM, YOLOv8) extract and validate data straight into your database.
Recent work: a medical RAG chatbot with document upload and automatic quiz generation; a document extraction pipeline combining object detection and OCR for scanned forms; and custom vision models (YOLOv8, EfficientNet) deployed for KYC and medical imaging at 90%+ accuracy. I bring 2+ years as an ML Engineer at BeeNeural, and I'm certified in Agentic AI with LangChain and LangGraph (Coursera) and RAG application development.
Stack: GPT-4o, Claude, LangChain, LangGraph, CrewAI, LlamaIndex, Pinecone, ChromaDB, Weaviate, FastAPI, Docker, AWS, GCP, Salesforce, HubSpot, Twilio, Slack, n8n
How I work: No jargon. I translate LLM architecture into business logic. Production-first: maintainable code, data privacy compliance, human-in-the-loop safeguards, and HIPAA-aware builds for regulated industries. End-to-end: from architecture to cloud deployment.
Ready to see what's buildable? Message me with the operation eating your team's time and I'll give you a straight, no-sales-pitch engineering answer, free of charge.
Steps for completing your project
After purchasing the project, send requirements so Fakhar Imam can start the project.
Delivery time starts when Fakhar Imam receives requirements from you.
Fakhar Imam works on your project following the steps below.
Revisions may occur after the delivery date.
Kickoff & Sample Collection
Provide 30–50 sample docs per type and target fields. We review your docs, list required fields, and note edge cases (languages, stamps, tables, handwriting) to shape scope and accuracy goals.
OD Setup (Layout Detection)
Detect tables, logos, stamps, signatures, form regions etc. Train/tune detectors on your samples; tag regions for OCR and table reconstruction. Produce layout JSON for downstream steps.