Keyur Gondaliya

RAG (Retrieval-Augmented Generation) combines AI with your business data to provide accurate, contextual responses. It can improve customer service, automate documentation, and enhance decision-making by 30-50%. I build RAG systems that work with your existing data sources and scale to enterprise requirements.

I implement production-ready AI with proper error handling, monitoring, scaling strategies, and performance optimization. My systems handle enterprise-level traffic with 99.9% uptime. I use containerization, load balancing, and comprehensive testing to ensure reliability.

I've delivered AI solutions for real estate, fintech, e-commerce, restaurant management, healthcare, and industrial sectors. Each solution is tailored to specific industry needs and compliance requirements. My cross-industry experience helps identify unique opportunities for AI implementation.

Yes, I specialize in AI integration that works with your current tech stack. Whether it's CRM systems, databases, APIs, or legacy applications, I build bridges that let AI enhance your existing workflows without disruption.

Data security is paramount in all my AI implementations. I use encryption, secure data pipelines, privacy-compliant processing, and enterprise-grade security practices. All systems are designed to meet GDPR, CCPA, and industry-specific compliance requirements.

LangChain is excellent for linear AI workflows and rapid prototyping, while LangGraph handles complex, multi-step business processes with conditional logic and parallel execution. I choose the right framework based on your specific use case and scalability requirements.

AI can optimize Meta ads through automated bid management, audience targeting, creative testing, and conversion prediction. I build systems that integrate with Meta's Conversions API for privacy-compliant tracking and typically achieve 20-35% improvement in ROAS.

I focus on business outcomes first, technology second. Every AI solution I build is designed to solve specific problems and deliver measurable results. I combine deep technical expertise with business understanding to create systems that actually work in the real world.

A production-ready RAG system typically takes 4-8 weeks to implement, depending on data complexity and integration requirements. This includes document processing setup, vector database optimization, testing, and deployment with monitoring.

Companies that need enterprise-grade AI solutions with proven ROI. Best fit: Fortune 500 companies, fast-growing startups, and businesses with complex data processing needs who want reliable, scalable AI systems that integrate seamlessly with existing workflows.

My AI implementations typically deliver 30-50% performance improvements with ROI within 6-12 months. This includes reduced manual work, faster decision-making, improved customer satisfaction, and operational cost savings averaging $100K-$500K annually per system.