Prodgain.
Architecting enterprise-scale AI research platforms and intelligent data processing systems, delivering market insights, sales intelligence, and automated document analysis solutions that drive measurable business impact through advanced Gen AI based agentic orchestration and real-time optimization.
Details
Responsibilities
Architected high-performance deep research infrastructure processing 100+ concurrent research queries with an enterprise-grade RBAC system, reducing secondary research report generation time by 75% and achieving a 40% AI cost reduction through proper data modeling, file system simulation and agent orchestration.
Developed an AI-powered market research assistant analyzing 1.8M data points using multi-query retrieval and vector search, engineered a high-precision RAG system with CoT reasoning and custom re-ranking, achieving 90% accurate responses.
Built a real-time streaming parser for custom tag extraction and dynamic chart generation with an enterprise-grade RBAC interface, optimized with memoisation, contributing to a 15% increase in customer retention and a 10% boost in deal conversion.
Developed an internal NPM package integrating the top 5 LLMs with standardized TypeScript APIs and abstracted real-time streaming for tool calling, reducing integration time by 40% and helping developers write 900+ fewer lines of code per project.
Engineered an automated revenue intelligence system by integrating the Freshcaller API, processing 4,800+ sales calls per month. Designed intelligent cron jobs for multi-stage analysis, cutting manual review time by 80% and boosting team efficiency by 30%.
Developed a real-time chat interface with Socket integration enabling 6K global clients to receive AI-powered insights and implemented credit-based usage tracking and dynamic response streaming, processing 10K+ user interactions with sophisticated tag processors.
Architected a scalable, fault-tolerant RMS backend to process 8,500+ market research reports, using parallelized cron jobs handling 100+ reports per batch. Integrated LLMs with batching optimizations, reducing API costs by 50-70% while ensuring system resilience and high availability.
Developed an enterprise-level RMS frontend featuring bulk upload support and live processing status updates, reaching 95% accuracy in extracting insights from market research reports, driving over 10% of annual company revenue.
And, continuing to build more impactful solutions...