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AI Powered Search Assistant for Business
WislaSearch is an AI powered search assistant that centralises fragmented data, indexes and retrieves relevant information instantly, and ensures everything stays within your secure infrastructure.
- AI Models: LlamaIndex, HuggingFace for smart retrieval
- Industry: Fintech, Leasing
- Deployment Time: 6 weeks
01.
Clients Request and Our Solution
Companies face challenges with scattered knowledge and inefficient search. Employees waste time retrieving critical data, while most AI search solutions rely on third-party services, raising security concerns.
Our client needed a fully on-premise AI-driven search tool that integrates seamlessly with internal systems while ensuring complete data privacy.
We delivered an AI-powered assistant that provides instant answers by integrating seamlessly with internal data sources. The system is fully deployed on-premise, ensuring that no data is transferred externally. It supports both open-source and private AI models, giving businesses full control over their search infrastructure.
Final Results
- 70% faster data retrieval.
- Full security compliance with all sensitive data kept internally.
- Scalable architecture for expansion.
- AI continuously improves search accuracy.
Our client now has a secure, autonomous search assistant that delivers precise, real-time insights while maintaining full data control.
Defining the Core System Architecture
Many enterprises struggle with inefficient knowledge management. Traditional search tools fail to provide context-aware, precise answers.
· We developed a scalable AI-driven search architecture leveraging LlamaIndex and HuggingFace for smart retrieval, integrating the Retrieval-Augmented Generation (RAG) pattern.
· The system utilises vector-based search with ElasticSearch and Qdrant for high-speed indexing, ensuring fast, context-aware responses while maintaining full on-premise security.
· A modular API-driven design enables seamless connectivity with enterprise knowledge bases, structured databases, and unstructured document repositories.
Suggested Key Architectural Solutions
· On-premise deployment for complete data privacy.
· Vector-based search indexing for high accuracy in information retrieval.
· API-first design for seamless integration with internal enterprise tools.
· AI-powered document parsing for understanding unstructured data.
· Self-learning models that adapt to company-specific terminology.
Business Impact
We developed a structured rollout plan ensuring seamless integration across departments. A phased deployment strategy minimised disruptions and maximised adoption.
Key outcomes:
· 70% reduction in search-related workload.
· Faster decision-making with instant access to key data.
· Scalable on-premise infrastructure for long-term AI enhancements.
WislaSearch has transformed internal knowledge management, making data retrieval faster, more accurate, and entirely secure.
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We are equipped with an Agile mindset — flexible, transparent, and results-driven at every stage.
Viacheslav Kostin, CEO
20+ years of experience in managerial positions in IT and bankingViacheslav Kostin, CEO
Previous roles: CEO in IT, Director of Strategy and Marketing in Banking, Curator of Holding Banks, Head of Products and Project Office.
Education: MBA for Executives at IMD (Switzerland), Leading Digital Business Transformation (IMD). Provides consulting in strategy and digital transformation.
Vasil Pahomov, CTO
20+ years of experience as a developer, analyst, and solutions architectVasil Pahomov, CTO
Designs resilient, high-load systems with multiple integrations for banks and financial institutions. Expertise in distributed storage and microservices architecture.