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AI and Automation

Document Q&A System

A document Q&A system that turns long PDFs and reports into instant answers with citations.

Overview

What we deliver

We build document Q&A systems that let teams query contracts, reports, and manuals in plain language and get cited answers in seconds.

We build document Q&A systems that turn dense PDFs, contracts, technical manuals, and research reports into a queryable knowledge layer. Our team handles parsing, chunking, embedding, and retrieval so users can upload or connect a library of documents and ask questions in plain language. Every answer includes citations with page references so reviewers can verify the source before acting. We support tables, scanned documents, and complex layouts through OCR and structured extraction. We also build review workflows for sensitive use cases like legal, compliance, and due diligence where accuracy and traceability matter. The result is faster contract review, quicker research synthesis, and less time spent skimming long documents for the one paragraph that actually answers the question at hand.

Fit Check

Built for teams like yours

Who it's for

  • Legal and compliance teams
  • Investment and due diligence firms
  • Research and analyst teams
  • Regulated industries
  • Internal audit functions

Pain points we solve

  • Hours spent reading long documents
  • Missed clauses or details
  • Slow contract and report review
  • Difficulty finding specific data points
  • Manual extraction of key terms
What's included

Capabilities

Everything we cover in this engagement.

  • PDF and document parsing
  • OCR for scanned files
  • Table and layout extraction
  • Chunking and embeddings
  • Citation with page references
  • Multi-document querying
  • Review workflow
  • Export and reporting
How we work

Our process

A clear, predictable path from kickoff to outcomes.

01

Document audit

We review sample files to understand structure and quality.

02

Parsing pipeline

We build extraction logic for your document types.

03

Q&A interface

We configure the query layer and citation system.

04

Pilot

We test with real users on real documents.

05

Rollout

We hand over with training and ongoing tuning.

What you get

Deliverables & outcomes

What you get

  • Document ingestion pipeline
  • Q&A interface
  • Citation system
  • Review workflow
  • Admin dashboard
  • User documentation

Outcomes you can expect

  • Faster document review
  • Fewer missed details
  • Lower analyst hours per file
  • Higher review consistency
  • Auditable answer trail
Timeline

6 to 10 weeks

Engagement

Monthly retainer, Project, Sprint

Tools we use

LlamaIndex, Unstructured, OpenAI, Azure Document Intelligence, Pinecone

KPIs we track

Time per document, Answer accuracy, Citation precision, Review throughput, User adoption

Client stories

What clients say

"

We were paying three agencies and a lifecycle freelancer to argue over attribution. RevoraOps absorbed all of it in 30 days, killed our worst-performing Meta ad sets, and rebuilt the welcome flow from scratch. CAC dropped 31 percent in the first full month. Honestly the relief of having one weekly call instead of four was worth it alone.

Megan W.
"

Our LCP was 4.8 seconds and Google was punishing us for it. They audited the build, dumped two plugins we did not need, moved hero images to a real CDN, and rewrote the critical CSS. LCP came down to 1.6 seconds within three weeks. Bounce rate on the pricing page dropped by a quarter without us touching the copy.

Sarah K.
FAQ

Frequently asked questions

Quick answers to the questions we hear most.

Can it handle scanned PDFs?
Yes, we run OCR on scanned files and extract text, tables, and layout for retrieval.
How accurate are the citations?
Every answer links back to the page and passage it was drawn from so users can verify before acting.
How many documents can it handle?
From a few hundred to several million pages, depending on the vector store and infrastructure choices.
Can we keep documents private?
Yes, we deploy in your cloud tenant and never train on your data.
Does it work with non-English documents?
Yes, we support most major languages with appropriate embedding and OCR models.

Need answers from a library of long documents?

We will build a document Q&A system that returns cited answers your team can trust.