AhaDoc: AI Document Analysis with Highlighting & Smart Citations

An AI document analysis platform that enables secure uploads, interactive Q&A, OCR, and clickable source-backed citations.

Client

AhaDoc

Industry

AI Document IntelligenceCollaboration

Services

Generative AIOCRSmart CitationsDocument Q&A
AhaDoc App

About AhaDoc

AhaDoc is a collaborative AI document analysis platform that helps users upload, organize, search, and interact with documents through intelligent Q&A. Users can manage files inside public or private workplaces, making the platform useful for teams, researchers, and document-heavy workflows.

The platform provides source-referenced AI answers with clickable citations that take users directly to the exact page and highlighted text inside the original PDF.

About Saddlefit

Project Goals

01
01

Enable Document Q&A

Allow users to ask questions and receive accurate answers from uploaded documents.

02
02

Build Smart Citations

Link AI responses directly to exact source pages and highlighted PDF text.

03
03

Support Secure Workplaces

Organize documents into public and private workspaces for controlled collaboration.

04
04

Process Scanned Files

Use OCR to make scanned PDFs searchable, readable, and citable.

05
05

Improve Research Speed

Help users find answers, verify sources, and analyze documents faster.

Key Challenges

Building AhaDoc required combining document upload, OCR, semantic search, AI Q&A, citation mapping, and secure collaboration into one smooth document analysis experience.

01
CHALLENGE #01

Connecting answers with exact sources

AI responses needed to reference the correct document, page, and highlighted text so users could verify every answer.

02
CHALLENGE #02

Handling scanned documents

Many uploaded PDFs were image-based, so OCR was required to extract readable text and make them searchable.

03
CHALLENGE #03

Managing collaborative workspaces

The platform needed public and private workplace structures to support secure document sharing and team-based access.

04
CHALLENGE #04

Building reliable document retrieval

The AI needed to search large document sets and retrieve the most relevant context before generating answers.

OUR ROLE

Driving AhaDoc’s AI Document Intelligence

GeeksVisor built the AI workflows, OCR processing, citation system, and document intelligence layer behind AhaDoc’s collaborative analysis platform.

Backend Architecture

AI Q&A Workflows

Built document-based conversational analysis.

Smart Citation System

Mapped answers to highlighted sources.

OCR Processing Pipeline

Converted scanned files into searchable text.

Secure Workspace Logic

Structured public and private collaboration.

Marketplace Design

Document Q&A Engine

Used OpenAI to generate answers from retrieved document context with clear and helpful explanations.

Semantic Search Layer

Integrated Pinecone to retrieve relevant document chunks before generating AI responses.

Clickable Citation Mapping

Connected each answer to the exact PDF page and highlighted source text for verification.

OCR Extraction Flow

Used Tesseract OCR to process scanned PDFs and make their content searchable and citable.

Workspace Management

Built public and private workplace logic for secure sharing, organization, and collaboration.

Solution and Architecture

An AI Document Platform Built for Verifiable Answers

We developed AhaDoc using OpenAI, Pinecone, Tesseract OCR, PostgreSQL, and prompt engineering to support document upload, semantic search, AI conversations, OCR processing, and citation-backed responses.

Verifiable AI Responses

Users can validate answers through citations linked to exact PDF pages and highlighted source text.

Searchable Scanned Documents

OCR processing made scanned PDFs readable, searchable, and usable for AI-powered Q&A.

Faster Document Review

Users can ask questions, find answers, and analyze large documents without manual searching.

Secure Collaboration

Public and private workplaces allow teams to organize, share, and analyze documents safely.

Smarter Research Workflow

Combined semantic search, AI Q&A, OCR, and citations into one complete document intelligence experience.

Results and Impact

Faster Document Analysis with Source-Backed Answers

AhaDoc helps users analyze complex documents faster while keeping every AI response verifiable through clickable citations, highlighted PDF text, and OCR-powered search.

OUR TECHSTACK

Key Technologies & Platforms

We work with leading platforms and technologies that empower digital transformation, accelerate delivery, and streamline business results.

Stripe
AWS
AWS Lambda
Claude
Stripe
AWS
AWS Lambda
Claude
Stripe
AWS
AWS Lambda
Claude
Stripe
AWS
AWS Lambda
Claude
Stripe
AWS
AWS Lambda
Claude
Stripe
AWS
AWS Lambda
Claude
Stripe
AWS
AWS Lambda
Claude
Stripe
AWS
AWS Lambda
Claude
Contentful
DevOps
Docker
Figma
Contentful
DevOps
Docker
Figma
Contentful
DevOps
Docker
Figma
Contentful
DevOps
Docker
Figma
Contentful
DevOps
Docker
Figma
Contentful
DevOps
Docker
Figma
Contentful
DevOps
Docker
Figma
Contentful
DevOps
Docker
Figma
Gemini
GraphQL
LangChain
Next.js
Gemini
GraphQL
LangChain
Next.js
Gemini
GraphQL
LangChain
Next.js
Gemini
GraphQL
LangChain
Next.js
Gemini
GraphQL
LangChain
Next.js
Gemini
GraphQL
LangChain
Next.js
Gemini
GraphQL
LangChain
Next.js
Gemini
GraphQL
LangChain
Next.js
Node.js
OpenAI
Pinecone
PostgreSQL
Node.js
OpenAI
Pinecone
PostgreSQL
Node.js
OpenAI
Pinecone
PostgreSQL
Node.js
OpenAI
Pinecone
PostgreSQL
Node.js
OpenAI
Pinecone
PostgreSQL
Node.js
OpenAI
Pinecone
PostgreSQL
Node.js
OpenAI
Pinecone
PostgreSQL
Node.js
OpenAI
Pinecone
PostgreSQL
React
Redux
Shopify
Python
React
Redux
Shopify
Python
React
Redux
Shopify
Python
React
Redux
Shopify
Python
React
Redux
Shopify
Python
React
Redux
Shopify
Python
React
Redux
Shopify
Python
React
Redux
Shopify
Python

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Mail
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Location
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