Case Studies

Discover how we've helped organizations across different sectors transform their operations through innovative technology solutions.

Note: Some information has been redacted due to client confidentiality, and security considerations.
Nuclear Decommissioning Authority logo
Sensitive Project

Nuclear Decommissioning Authority

Knowledge Management Platform

An advanced RAG-LLM based knowledge management system for the UK Nuclear Sector, enabling automated compliance checking, reference validation, and technical query resolution within a highly regulated environment.

Challenge:

The platform needed to streamline document processing, ensure regulatory compliance with UK Nuclear Sector requirements, and enable rapid access to highly technical domain knowledge while maintaining strict security standards and comprehensive audit trails.

Solution:

[REDACTED] A responsive web application with [REDACTED] cloud infrastructure using secure VPC configuration. Features include real-time document processing across [REDACTED] connected data sources, automated reference validation, and compliance checking against regulatory frameworks. The system delivers sub-5-second response times for standard queries and under 30 seconds for complex technical analyses. [REDACTED] architecture ensures high availability and data redundancy. Comprehensive audit trails and role-based access controls ensure compliance with nuclear sector regulations.

Technologies:
Python
OpenAI
Weaviate
Apache
Redis
Key Results:
  • 300% increase in documentation processing efficiency
  • Reduced report completion time by 90%
  • Automated validation of technical references and compliance
  • Enhanced accuracy in domain-specific technical queries
TopDanmark logo

TopDanmark

AI-Powered Claims Processing Engine

An intelligent claims processing system utilizing RAG-LLM technology to automate initial claims assessment, policy verification, and customer communication in the insurance sector.

Challenge:

The existing claims processing workflow required streamlining through automation of the initial assessment phase, reduction of agent workload, and maintenance of consistent decision-making while ensuring compliance with policy terms and conditions.

Solution:

A web-based claims processing platform powered by RAG-LLM technology. The system performs automated analysis of claim submissions, policy coverage verification, and customer eligibility checks, generating preliminary decisions with detailed reasoning. External API integration provides contextual data (weather conditions, location data) to enhance claim validation. The platform features intelligent opportunity detection for coverage gaps and potential policy upgrades. Insurance agents receive comprehensive summaries including assessment logic, contextual insights, and pre-drafted customer communications, enabling rapid review and response.

Technologies:
Python
OpenAI
Redis
Weaviate
Key Results:
  • Reduced claim processing time from 25 minutes to under 2 minutes
  • 85% accuracy in automated policy verification
  • 70% decrease in agent response preparation time
  • Identified coverage opportunities in 30% of claims
BlueNord logo

BlueNord

Enterprise Knowledge Assistant

An advanced RAG-based AI assistant delivering instant access to company-wide technical and business intelligence for offshore operations and executive decision-making. Features mobile-first design for seamless use across all devices.

Challenge:

The solution needed to provide rapid access to critical technical and business information across offshore operations and executive levels, with emphasis on mobile accessibility for field operations. Requirements included support for both real-time querying and document processing capabilities while ensuring accurate information retrieval in time-sensitive situations.

Solution:

A sophisticated AI assistant leveraging RAG architecture with responsive, mobile-first design optimized for phones, tablets, and laptops. The platform features document upload and comprehension capabilities, integrating new information with existing knowledge base in real-time. Role-based access controls, domain-specific knowledge retrieval, and real-time information updates are core components. The interface adapts seamlessly across devices, ensuring consistent user experience for both field operations and executive users.

Technologies:
Python
OpenAI
Redis
Weaviate
Key Results:
  • 90% reduction in query resolution time
  • 24/7 access across all devices
  • 50% reduction in specialist consultation needs
  • Seamless document processing and knowledge integration
Sodexo logo

Sodexo

Enterprise HR Assistant

A scalable GenAI-powered HR assistant designed to provide instant, accurate responses to employee queries across multiple languages and regions. Features advanced document processing capabilities for complex HR documentation and policy management.

Challenge:

The platform needed to handle thousands of concurrent HR-related queries while managing complex document residency requirements for legal compliance. Processing multi-format policy documents and maintaining accurate information retrieval across diverse document types presented significant challenges. Integration with existing HR systems and scalability for global deployment were key requirements.

Solution:

A microservices-based HR assistant leveraging advanced language models and enterprise search capabilities. Powered by our Hive, Comb, and Honey product suite for intelligent document processing and retrieval (see our portfolio for more details). The architecture enables rapid deployment across regions with automated scaling based on demand. The system features real-time policy updates, multi-language support, and seamless integration with existing HR databases. Azure AI Search enables intelligent retrieval across structured and unstructured HR documentation, while Databricks powers advanced analytics and continuous system improvement.

Technologies:
Python
OpenAI
Apache
Azure
Databricks
Key Results:
  • 95% reduction in HR query response time
  • Support for 30+ languages and regions
  • 80% decrease in routine HR ticket volume
  • 99.9% accuracy in complex document processing