case Study:

AI Document
management

Letting AI do what it does best to speed workflow
& increase accuracy.

Facing high volumes of client records, legal documents, and compliance materials, New Dawn Title Agency needed an automated document system they could trust.

Overview

TAD (Totally Automated Documents) is a custom-built document intelligence platform designed to streamline the ingestion, summarization, tagging, and retrieval of high-volume client and compliance documents. Built on Azure OpenAI, React, Blob Storage, and Dataverse, it automates manual workflows while embedding trust features like confidence scoring, source traceability, and audit-ready metadata. Users can drag and drop files, instantly receive AI-generated summaries and suggested tags, review trust reports, and search or bundle documents for audits—all within a scalable, transparent, and user-friendly interface. TAD empowers organizations to manage documents with speed, accuracy, and ethical AI oversight.

-85%

Document Processing Time

92%

Human Match Rate

4.8/5

average rating

-30%

Audit Collection Time

The Challenge

In an era of increasing regulatory scrutiny, data complexity, and operational scale, organizations face mounting pressure to manage documents with precision, transparency, and speed. TAD (Totally Automated Documents) is a custom-built document intelligence platform that leverages Azure OpenAI, React, and Microsoft 365 infrastructure to automate document ingestion, summarization, tagging, and retrieval—while embedding trust features that ensure auditability and compliance.

The Approach

Organizations, especially compliance-driven enterprises in a highly regulated industries, routinely manage thousands of documents across disparate systems. These documents often contain sensitive, time-critical information that must be:

Reviewed for relevance and accuracy
Tagged for classification and retrieval
Summarized for decision-making
Auditable for compliance and legal defense

Challenges include:

Manual review is slow, inconsistent, and error-prone
Tagging lacks transparency and often depends on subjective human judgment
Search and retrieval are fragmented across platforms
AI-generated content lacks traceability and trust signals

These inefficiencies lead to operational bottlenecks, missed deadlines, and elevated risk—especially in high-stakes environments like audits, legal proceedings, and grant reporting.

The Solution

TAD (Totally Automated Documents) is a custom-built document intelligence platform designed to:

Automate document ingestion, summarization, and tagging
Provide transparent trust scores and source traceability
Enable fast, filtered retrieval for audits and client reporting

Built using React, Azure OpenAI, Azure Blob Storage, and Dataverse, TAD delivers a seamless user experience with enterprise-grade reliability.

Implementation Steps

Discovery & Design

Conducted stakeholder interviews and workflow mapping

Identified three primary user flows: Upload, Review, Collect

Defined metadata schema and trust requirements

Test & Refine

Ran pilot with real-world documents across multiple clients

Validated AI summaries and tags against human reviewers

Refined UI for clarity and accessibility

Embedded trust signals and override workflows

Build & Integrate

Developed React components for drag-and-drop upload, preview, and tag review

Configured Azure Blob containers w/structured folders

BuildAzure Functions to extract text, generate summaries, and apply tags

Stored metadata in with relational clients and tag links

Enable search and export features for audit preparation

Deploy & Train

Deployed to small set of document handlers
Developed training video and documentation
Launched to all users with initiation training

Conclusion

TAD demonstrates how thoughtful architecture, ethical AI, and user-centered design can transform document workflows from a liability into a strategic asset. It empowers organizations to scale intelligently, respond confidently, and build trust—one document at a time.