Proven results across
critical industries

Context: A regional e-commerce platform with 2M+ SKUs struggled with poor search relevance and low conversion rates.

Challenge: Keyword-based search returned irrelevant results. Users abandoned sessions after 2-3 failed searches, driving conversion below 1.2%.

Solution: Built a semantic search engine using vector embeddings and a RAG pipeline. Implemented visual search and natural language product queries.

AI layer: Fine-tuned embedding model for product catalog. RAG pipeline for conversational product discovery. Real-time personalization layer.

Context: A fleet logistics operator running 500+ vehicles across 3 countries with no real-time visibility or route intelligence.

Challenge: Manual route planning caused 30% excess fuel costs. No real-time tracking meant late deliveries and poor SLA compliance.

Solution: Built a real-time tracking platform with ML-powered route optimization. Streaming telemetry from IoT devices into a unified dashboard.

AI layer: Reinforcement learning model for dynamic route optimization. Anomaly detection for vehicle health. Demand forecasting for capacity planning.

Context: A challenger bank needed to replace legacy batch payment processing to support instant payments across 12 markets.

Challenge: Batch processing created 4-hour settlement delays. System couldn't scale beyond 100K daily transactions without failures.

Solution: Rebuilt payment rails on event-driven microservices with exactly-once processing semantics and multi-region failover.

AI layer: ML-based fraud detection scoring in real-time. Anomaly detection on transaction patterns. Automated compliance checks.

Context: A network of 200+ hospitals needed to reduce diagnostic bottlenecks in radiology departments.

Challenge: Radiologists spent 45+ minutes per scan with inconsistent accuracy. Backlogs grew to 72-hour wait times for results.

Solution: Deployed deep learning models for medical image analysis with HIPAA-compliant infrastructure and clinician-friendly interfaces.

AI layer: Custom CNN models for X-ray and CT analysis. Confidence scoring for triage prioritization. Continuous learning from clinician feedback.

Context: A precision manufacturer with 12 production lines experiencing unplanned downtime costing $2M annually.

Challenge: Reactive maintenance led to 15% unplanned downtime. Quality defects detected too late, causing 8% waste rate.

Solution: Deployed IoT sensors across all lines with streaming analytics and ML models for failure prediction and quality anomaly detection.

AI layer: Time-series anomaly detection for equipment health. Computer vision for real-time quality inspection. Prescriptive maintenance scheduling.

Context: A national government agency serving 8M citizens needed to digitize 40+ paper-based services.

Challenge: In-person processing took 2-3 weeks per application. 60% of submissions had errors requiring re-processing.

Solution: Built an accessible digital portal with intelligent form validation, document upload, and real-time application tracking.

AI layer: NLP for document classification. OCR for automated data extraction. Chatbot for citizen support.