Founder & Chief AI/Data Architect
Pramath Parashar is a nationally and internationally recognized AI and Data Engineering specialist leading the development of enterprise-scale AI-powered intelligence systems, intelligent automation platforms, and cloud-native enterprise analytics infrastructure through Krivex Intelligence.
Pioneering enterprise data intelligence and cognitive workflow automation at scale.
Architecting advanced Retrieval-Augmented Generation (RAG) and Agentic AI reasoning layers that transform siloed company documents into secure, production-grade intelligence hubs.
Orchestrating stateful autonomous agents that model complex enterprise workflows, automate multi-step operational tasks, and integrate with external APIs dynamically.
Building high-throughput, cloud-native analytics backends utilizing Snowflake, AWS, Databricks, and modern data warehouses to store and query multi-terabyte datasets.
Designing strict data governance access controls, SOC2-ready security guardrails, token rate-limiting, and privacy layers to protect corporate intellectual property.
Pramath's direct operational leadership and technical management at Krivex Intelligence.
"AI must be reliable, secure, and deeply integrated into core databases. We build reasoning systems that respect data governance while delivering autonomous, real-time insights."
Pramath Parashar
Founder & Chief AI Architect
End-to-end design of modular AI frameworks, LLM integrations (OpenAI, Anthropic, open-source), semantic search, and reasoning engines built on LangChain and LlamaIndex.
Developing scalable real-time analytics platforms, transactional data pipelines, semantic models, and interactive BI dashboards for executive-level operational insights.
Architecting secure AWS cloud architectures, dockerized deployments, API gateways, database replication strategies, and high-performance caching infrastructure.
Pioneering proprietary technologies that address LLM hallucinations, optimize metadata-driven extraction, and introduce autonomous self-correcting logic in AI agent systems.
Establishing secure ETL/ELT pipelines, data governance structures, and seamless storage system connectors with compliance at the core.
Pioneering proprietary technologies that address LLM limitations and ensure database security.
Engineered custom semantic chunking algorithms and hybrid search scoring (sparse & dense embeddings) that dramatically drop generative hallucinations, offering trustworthy enterprise information retrieval.
Created execution graphs that enable LLMs to self-correct code execution, cross-examine retrieved knowledge, and run multi-step planning tasks without human intervention.
Built natural language interfaces mapping directly to SQL, allowing executives to query structured databases (Snowflake, PostgreSQL) safely and get immediate visualizations.
Implemented strict security filters, PII sanitization layers, and role-based data isolation so enterprise documents never leak into unauthorized model training runs.
Schedule a technical strategy consultation with Pramath Parashar or explore Krivex's platforms.