Manufacturing & IndustrialAI & GenAIData & Analytics

AI-Powered Knowledge Base for Enterprise Documents

Instant answers from thousands of enterprise documents

Client

Enterprise Client

Region

North America

Key Outcomes

10x faster document retrieval100% data privacyEnterprise-wide deployment

Business Challenge

Technical knowledge was distributed across large collections of manuals, policies, specifications, and operational documents. Employees had to know which repository to search, try several keywords, open multiple files, and interpret long passages before answering routine questions. Conventional search returned documents rather than answers, while a general-purpose chatbot could not be trusted to respect document permissions or ground responses in approved enterprise content.

Solution Overview

DIATOZ built a retrieval-augmented knowledge platform that ingests approved documents, extracts and segments their content, creates searchable embeddings, and stores them in a secured vector index. When a user asks a question, the service retrieves the most relevant authorized passages and supplies that context to the language model before it generates an answer. Responses are tied back to source material so users can verify the underlying document instead of treating generated text as an unsupported conclusion. Administrative workflows govern document ingestion, re-indexing, access, and removal.

Architecture & Engineering

Document ingestion pipeline for extraction, normalization, chunking, metadata enrichment, and indexing

Vector search that retrieves semantically relevant passages instead of relying only on exact keywords

RAG orchestration that limits model context to approved source material

Role-based filtering so retrieval respects the user's document and department permissions

Source references returned with answers to support review and reduce hallucination risk

React experience backed by Python and Node.js services on AWS for upload, search, and administration

Technology Stack

ReactPythonNode.jsVector DBAWS

Business Impact

Reported document-retrieval time improved by up to 10x for supported knowledge workflows

Employees can ask questions in natural language without learning repository-specific search syntax

Answers remain grounded in enterprise documents and can be checked against their sources

Access controls preserve document-level privacy across teams and roles

A reusable ingestion and retrieval layer supports expansion to additional document collections

Why DIATOZ

DIATOZ treated enterprise search as a data-governance and trust problem as well as an AI problem, combining retrieval quality, source traceability, access control, and production-ready application engineering.