AI-powered Document Interaction System

Upload documents, ask questions in natural language, and get accurate, contextual answers instantly. Find information faster and turn complex documents into actionable insights.

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PDFDOCXPPTXCSV / XLSXJPG / PNG + OCR

vendor-agreement-2026.pdf 12 pages · 48 chunksIndexed

Master Services Agreement, Northbridge Logistics

Extract · OCR · Chunk · Embed

4.1 Fees. The Client shall pay all undisputed invoices within thirty (30) days of receipt. Invoices are issued monthly in arrears against the rate card in Schedule B.
4.4 Late payment.Amounts unpaid after the due date accrue interest at 1.5% per month, and the Supplier may suspend services after fifteen (15) days if the invoice stays unpaid.
7.2 Confidentiality. Each party shall protect the other's confidential information using no less than reasonable care, for a period of three (3) years following termination.
8.2 Termination for convenience.Either party may terminate this Agreement for convenience by providing sixty (60) days' prior written notice to the other party. Fees for work completed up to the effective date remain payable.
9.1 Limitation of liability.Aggregate liability of either party is capped at the total fees paid in the twelve (12) months preceding the claim, excluding breaches of confidentiality and indemnified IP claims.
11.3 Governing law. This Agreement is governed by the laws of the State of Delaware, without regard to conflict of law principles.
48 chunks indexed and ready. Pick a question to watch retrieval run.

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The document assistant is live. Upload a file and get an answer that points back to the exact passage it came from.

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  3. Upload a file and ask your first question
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AI Innovation overview

What if your documents could answer your questions?

The Chat with Documents AI Innovation is an AI-powered document interaction system that enables users to upload their files and query them through natural language instead of manual reading and searching.

Users can upload documents in multiple formats, including PDF, Word, PowerPoint, CSV, Excel, and images. The platform extracts and processes the content, including OCR for scanned documents, indexes it for semantic search, and uses AI to generate contextual responses. This extracted content is stored in a cloud object store with CDN delivery and indexed in a vector database, enabling fast and accurate semantic search across large document sets.

Your files
  • PDF vendor-agreement-2026
  • DOC supplier-terms-v4
  • XLS rate-card-schedule-b
  • SCAN signed-addendum.jpg
Extracting · OCR · chunking
Indexed
chunk_031
chunk_015
chunk_022
chunk_036

From files to answers

01

Upload

Add your business documents, spreadsheets, presentations, or images.

02

Understand

Content is extracted, parsed, OCR-processed, chunked, and converted into searchable representations.

03

Search

Semantic search identifies the most relevant information across your indexed documents.

04

Ask

Interact with your documents using natural language.

05

Get insights

Receive contextual answers, summaries, and suggested follow-up questions.

More than document search

The AI Innovation was designed to demonstrate what a production-ready document intelligence platform could look like, not just validate basic question-answering.

Secure access

Google-based single sign-on, token refresh, authentication, logging, and error handling help protect and monitor user requests.

Persistent conversations

Users can revisit previous conversations, rename or remove chats, and manage their uploaded documents whenever needed.

Built for monetization

Tiered subscriptions, card-based checkout, automated renewals, cancellation and reactivation flows, billing history, and real-time usage limits support a complete commercial model.

Engineered for scale

The AI Innovation validates the feasibility of an AI-powered document intelligence platform while establishing the foundation for scalable search, secure access, commercial deployment, and future production optimization.

Storage

Documents are stored in cloud object storage with CDN delivery.

Retrieval

Vector indexing enables fast semantic retrieval across growing document collections.

Embeddings

Batched and parallel embedding generation, with configurable chunk sizes.

Throughput

Connection pooling and defined file and row limits keep processing and response times predictable.

Key features

What the AI Innovation already does

Structured CSV and Excel data is processed for analysis and statistical insights, not just read as text.

RegionQ3Q4DeltaAPAC1,2401,610+29.8%EMEA2,0502,318+13.1%AMER1,8702,455+31.3%
Table detected · 4 × 3

Retrieval

Intelligent document search

Go beyond keyword matching with semantic search across indexed document content.

"can we walk away early?"
chunk_0310.94
chunk_0150.71
chunk_0220.48

Top match shares no keywords with the question

Ingest

OCR for scanned documents

Extract meaningful information from scanned and image-based documents using OCR-powered processing.

Answer

AI-powered answers

Ask questions in natural language and receive contextual, user-friendly responses.

Ingest

Multi-format document support

Work with PDFs, Word documents, PowerPoint presentations, CSV and Excel files, JPGs, and PNGs.

Analyse

Data analysis

Process structured CSV and Excel data for analysis and statistical insights.

Operate

Persistent conversations

Users can revisit, open, rename, or delete previous conversations.

Operate

Document management

Upload, view, manage, and delete documents from a centralized experience.

Foundations

Enterprise-ready foundations

The AI Innovation includes authentication, usage controls, subscriptions, cloud storage, logging, and scalable processing considerations.

  • Google OAuth 2.0
  • Live usage limits
  • Tiered subscriptions
  • S3 + CloudFront storage
  • Request logging
  • Error handling

Technologies used

Modern AI and cloud architecture

Chat with Documents combines AI, RAG, document processing, cloud infrastructure, and production-oriented backend technologies.

query.py
from llama_index.core import VectorStoreIndexfrom qdrant_client import QdrantClientindex = VectorStoreIndex.from_vector_store(QdrantVectorStore(client=QdrantClient(QDRANT_URL)))answer = index.as_query_engine(llm=gemini).query("Which clauses cap our liability?")# 2 sources, top match 0.94, section 9.1

AI & LLM

Google Gemini 2.5 FlashGemini EmbeddingsLlamaIndexLlamaParse / LlamaCloudLangChainLangGraph

Backend

PythonFastAPIUvicornPydantic

Data

Qdrant Vector DBPostgreSQLSQLAlchemyAsyncPG

Document processing

pypdfpython-docxpython-pptxpandasopenpyxlTesseract OCRPillow

Cloud & infrastructure

AWS S3AWS CloudFrontboto3

Auth & payments

Google OAuth 2.0Stripe CheckoutStripe Webhooks

Build with us

50+ AI specialists, ready when you are

Strategy, development, deployment and tuning. Our team takes an idea from first sketch to a production ready AI system.

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ML engineers, data engineers and product designers, picked per project.

48 chunks indexedOCR ready

Live POC Form

Get live access to the document assistant

Submit your details and we will open a working environment loaded with sample documents, so you can index files and ask questions against them yourself.

Why it matters

How it helps your business

Your teams already have the information they need. The challenge is finding it quickly. Chat with Documents creates a conversational layer over your business knowledge so employees can spend less time searching and more time acting on information.

One grounded answer 3 sources

Reduce manual searching

Find relevant information across large document collections without manually scanning files.

Accelerate decision-making

Get contextual answers and summaries faster, helping teams move from information to action.

Unlock existing knowledge

Make information buried inside documents easier for teams to discover and use.

Improve productivity

Reduce repetitive document-reading and information-retrieval tasks.

Build smarter internal tools

This foundation can be adapted for internal knowledge bases, document assistants, customer-facing portals, research tools, and other AI-powered workflows.

FAQ

Frequently asked questions

The same semantic search that powers the product also finds the right answer here. Your wording does not have to match.

can it read a photo of a page
Can it understand scanned documents? 0.94
What types of documents can the platform process? 0.61
Does it support Excel and CSV data? 0.42
Chat with Documents supports PDF, Word, PowerPoint, CSV, Excel, JPG, and PNG files.
Yes. OCR-based processing is included for scanned documents and image-based content.
The underlying semantic-search architecture is designed to retrieve relevant information from indexed document content, making cross-document querying a core capability.
Yes. Chat with Documents includes structured parsing and statistical analysis capabilities for CSV and Excel data.
Yes. Conversation history is persisted, with functionality to list, open, rename, and delete chats.
Yes. Chat with Documents includes Google OAuth 2.0 single sign-on with refresh-token support.