Our Customers

Challenge

Search relevance was declining, leading to a 15% drop in conversion rates across their e-commerce platform.

Solution

Nextbrick re-architected their Elasticsearch cluster, implemented semantic search with vector embeddings, and optimized relevance tuning.

Challenge

Needed to process millions of documents daily for compliance and risk analysis, with manual review causing bottlenecks.

Solution

Deployed a RAG-powered AI system with custom LLM fine-tuning, enabling automated document analysis with human-in-the-loop verification.

Challenge

Legacy data infrastructure couldn't support real-time analytics needed for patient care insights.

Solution

Nextbrick built a modern data lakehouse on Databricks and Kafka, enabling real-time streaming analytics and ML-powered predictions.

Challenge

Needed to rapidly deploy AI agents for their customer support platform without a dedicated ML team.

Solution

Nextbrick designed and implemented an AI agent architecture using RAG, vector search, and LLM orchestration, with a fully managed handoff.