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Our Case Studies

Check out our portfolio to view the featured projects!
  • Case study

    AI-Powered Healthcare MVP for Patient Imaging Insights

    AI/MLMobile AppHIPAARAGHealthcare

    A New York-based healthcare MVP that helps patients better understand their medical imaging results through AI-assisted explanations in plain, human-readable language.

    Key objectives:
    • Build HIPAA-aware AI architecture
    • Implement RAG architecture for verified medical sources
    • Create MVP to validate user demand
    • Prepare for clinician-in-the-loop workflows
  • Case study

    AI-Fashion Social Mobile App

    Mobile AppSocial MediaAI/LLMiOSBetaFashion/Social Media

    A Berlin-based fashion social mobile app for enthusiasts to share outfits, discover styles, and interact through core social features with AI-powered tagging.

    Key objectives:
    • Complete and stabilize inherited codebase
    • Implement AI-assisted tagging via LLM API
    • Ship production-ready mobile experience
    • Build scalable infrastructure with cost trade-offs
  • Case study

    Cloud-Based AI & ETL Platform for Agricultural Machine Learning

    AI/MLCloud InfrastructureAWSETLData PipelineAgriTech

    A cloud-native system capable of orchestrating AI workloads, managing data pipelines, and storing results for an AgriTech company specializing in machine learning for field crop analysis.

    Key objectives:
    • Create robust execution layer for AI and data pipelines
    • Design modular system architecture on AWS
    • Support full lifecycle of AI workloads
    • Introduce strong observability and control mechanisms
  • Case study

    RAG-Powered Natural Language to SQL for Accounts Payable Automation

    RAGAI/MLFinTechSQLAzure OpenAIAccounts Payable Automation

    A proof of concept using RAG architecture to enable non-technical users to interact with accounting data through natural language queries translated into secure SQL.

    Key objectives:
    • Design secure AI interface for financial SQL database
    • Implement RAG to ground AI output in database schema
    • Prioritize accuracy, safety, and auditability
    • Deliver fast PoC with production readiness path
  • Case study

    RAG-Powered Process Automation for a Fintech Platform

    RAGFinTechProcess AutomationAI/MLUK ComplianceFinTech

    A RAG-powered automation layer that enables teams to retrieve accurate information, automate internal workflows, and reduce manual processing across finance and operations.

    Key objectives:
    • Design RAG architecture to ground AI in verified data
    • Automate repetitive operational workflows
    • Ensure UK financial compliance alignment
    • Deliver incremental value through automation
  • Case study

    AI-powered SaaS Dashboard

    SaaSMarTechNode.jsReactPostgreSQLMarTech

    A high-performance analytics platform that automates marketing reporting by aggregating data from major ad networks into a unified AI-driven intelligence hub.

    Key objectives:
    • Automate cross-platform data collection and normalization
    • Develop a unified attribution model for blended ROAS tracking
    • Build a scalable reporting engine for marketing agencies
    • Implement AI-driven anomaly detection for ad spend optimization
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Hi, I'm Danylo Melnychuk

CEO at Xedrum

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