Organizations across all sectors struggle to manage vast volumes of documents stored across complex digital ecosystems like SharePoint, OneDrive, and other Microsoft 365 services. Employees often waste valuable time searching through nested folders or reading lengthy files to find key insights. We developed an AI-Powered Document Search & Chat Platform—an enterprise-ready solution that combines intelligent search with conversational AI. Users can now locate, explore, and extract insights from documents instantly using natural language queries, transforming the way businesses interact with their digital content.
Agentic AI
GPT
Langchain
Pinecone
Python
Finding the right document meant navigating through deeply nested folder structures and thousands of SharePoint sites.
Existing Microsoft 365 search lacked contextual relevance and often returned incomplete or irrelevant results.
Even after locating a document, users had to manually read through long files to extract specific information.
Documents were distributed across departmental SharePoint sites and OneDrive folders, making centralized search impossible.
The client needed a secure solution that aligned with HIPAA and PHIPA compliance for handling sensitive medical documents.
We developed an AI-based search tool capable of crawling millions of documents across SharePoint and OneDrive using semantic understanding.
Integrated a Generative AI layer that allowed users to ask natural-language questions using Large Language Model and receive document-specific answers instantly.
Optimized the platform to support large-scale repositories with low-latency and high-performance document retrieval.
Enabled secure Microsoft 365 authentication with role-based permissions and audit trails, ensuring data security and access control.
Enabled multi-site querying, so users could search across departments and locations without needing to know where documents were stored.
We conducted stakeholder interviews, mapped document repositories, and documented workflows across departments to capture user needs.
Our designers then prepared design to showcase future-ready, modular system architecture using Azure Cognitive Search, FastAPI, OpenAI APIs, and Microsoft Graph APIs for seamless M365 integration.
Post designing, we built custom connectors for SharePoint and OneDrive. Also, we undertook development search engine logic using vector similarity and metadata indexing. Lastly, our software developers integrated the conversational AI layer.
We even ensured compliance with data security regulations and implemented multi-factor authentication, role-based access control, and data encryption.
During the development, we even enabled features like search filters (site, file type, last modified), metadata display, inline chat with documents, and download/view in M365.
Post development, we conducted UAT with actual resources across departments. And performed load testing for up to 10 million documents.
Once everything was tested, we then rolled out the solution in phases. And provided onboarding training, 24/7 support, and quarterly updates based on evolving needs.
Users could now locate the right files in seconds, not hours.
Staff spent less time navigating folders and more time on resources.
The intuitive interface and built-in guidance ensured smooth onboarding across departments.
Secure access and traceable actions ensured readiness for internal and external audits.
The solution proved robust, capable of supporting future growth without compromising performance.
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