🤖 AI Development & Digital Transformation

Case Study 1: AI-Powered Document Intelligence Solution

Ozone developed a Proof of Concept (POC) for an AI-Powered Document Intelligence Solution, designed to demonstrate how artificial intelligence can transform document-heavy workflows into intelligent, automated, and searchable systems.

The 4-6 week prototype showcases how organizations can automate document ingestion, extraction, semantic search, and proactive alerting — helping business users find key contract information in seconds instead of hours.

Project Goal

The goal of the POC was to validate a scalable, secure, and cloud-ready foundation for enterprise document intelligence. It demonstrates how AI can automatically read, interpret, and alert on key contract terms such as parties, dates, clauses, and risks, reducing manual review and compliance overhead.

Architecture Overview

The AI-Powered Document Intelligence POC is built using a modular, cloud-ready architecture designed for scalability, rapid iteration, and secure enterprise deployment.

Data Flow

• Ingest documents from SharePoint
• Preprocess via OCR/text extraction
• Extract metadata & generate embeddings
• Store vectors in Weaviate & metadata in MongoDB
• Query or alert via natural-language interface

Key Features

• Document Ingestion – Automated retrieval from Microsoft SharePoint, handling PDF, DOCX, and scanned documents with OCR. Batch upload of up to 100 files.
• AI-Based Extraction & Analysis – NLP-powered entity recognition with 90%+ accuracy on parties, clauses, and risk terms. Semantic embeddings for similarity search.
• Semantic Search & Queries – Natural-language search like "What is the expiration date for Contract X?" Returns relevant snippets with filters by date, party, and risk.
• Proactive Alerts & Notifications – Scheduled monitoring for key events, contract expirations, and compliance risks. Configurable delivery via email or dashboard.
• User Interface & Reporting – Intuitive web dashboard for non-technical users with visualization of metadata and alerts. Export options to CSV or PDF.
• Workflow Integration – Real-time sync with SharePoint updates. RESTful API endpoints for integration. Optional Microsoft Teams notifications.

Technology Stack

Built with Azure OpenAI, Hugging Face (LayoutLM, SentenceTransformer), LangGraph for agent orchestration, Weaviate (vector database), MongoDB, and Microsoft Graph API for SharePoint integration.

Conclusion

This POC successfully validated the feasibility and business value of an AI-driven document intelligence platform. The next phase involves extending the system to production scale — introducing advanced workflow automation, risk scoring, and full integration into enterprise ecosystems (e.g., SAP, Dynamics, Salesforce).

By combining Ozone's AI expertise with enterprise-grade architecture, this solution demonstrates how organizations can unlock insights from unstructured documents — instantly and securely.

Case Study 2: Contract Lifecycle Intelligence Dashboard

The Contract Lifecycle Intelligence Dashboard is an AI-driven analytics platform that transforms how organizations manage contracts — from initiation and negotiation to renewal and expiration. By combining advanced analytics, predictive AI models, and intuitive visualization, it delivers real-time visibility into contract performance, risks, and workload distribution.

This dashboard empowers legal, procurement, and sales teams to make proactive decisions — reducing missed renewals, avoiding compliance penalties, and optimizing operational efficiency.

In essence: it turns raw contract data into actionable intelligence for smarter, faster, and risk-aware business operations.

Purpose & Goals

The primary goal of the dashboard is to give organizations a dynamic, predictive view of their entire contract portfolio. It combines two complementary capabilities:

Impact: By merging visualization with prediction, the dashboard shifts organizations from reactive to proactive contract management — improving cash flow, vendor relationships, and strategic planning.

Three-Layer Architecture

Who Benefits

• Legal Operations – Track obligations and compliance status. Identify non-standard clauses and disputes early. Reduce manual review effort and regulatory risk.
• Vendor Management – Monitor supplier performance against KPIs. Predict renewals and renegotiation opportunities. Optimize audit scheduling and workload balance.
• Sales Operations – Visualize renewal pipelines and quota impacts. Prioritize high-probability renewals for targeted outreach. Prevent revenue leakage from missed expirations.

Data Workflow

• Contract data is pulled from internal and third-party systems
• AI models process historical and contextual data to predict outcomes
• Forecasted insights populate dashboards and trigger alerts
• Users explore analytics through interactive charts and reports
• Feedback loops enhance prediction accuracy over time

Technical Stack

• AI Models: Logistic regression, random forests, neural networks trained on contract datasets
• Data Sources: APIs to CLM, ERP, CRM tools (Salesforce, Dynamics, SAP)
• Frontend: React.js or Streamlit with D3.js/Plotly for visualizations
• Backend: Python (FastAPI) or Node.js microservices; containerized with Docker
• Storage: PostgreSQL for structured data; Weaviate or Elasticsearch for semantic indexing
• Alerting: Event-driven notifications via email, Slack, or Teams
• Security: JWT/OAuth authentication, encryption, role-based access control

Measurable Impact

The Contract Lifecycle Intelligence Dashboard goes beyond monitoring — it's a strategic decision-support system for contract-heavy organizations. By combining visualization, AI prediction, and intelligent alerts, it helps teams act faster, smarter, and more efficiently.

Empower your organization to anticipate, not just react — with AI-driven contract intelligence.