Executive Workshop
Building Data Products Using AI
A practical, leadership-friendly workshop led by Prashant Dhingra—covering GenAI, RAG, and Agentic AI patterns to move from experiments to production-scale AI data products.
Who this is for
Senior leaders and technical stakeholders responsible for driving AI transformation—especially where data, governance, and real ROI matter.
- Chief AI Officers (CAIO), Chief Data Officers (CDO), CTOs
- Product, Innovation, and Platform leaders
- Enterprise architects & data platform owners
- Teams modernizing analytics, automation, and decision support
Workshop outcomes
You’ll leave with tangible artifacts and decision-ready clarity to move faster with less risk.
- A blueprint for building enterprise AI data products
- A reference architecture for GenAI + Agentic AI platforms
- Frameworks to identify and prioritize AI use cases with measurable ROI
- A roadmap for operationalizing AI across the organization (governance, security, LLMOps)
What you’ll learn
A structured journey from strategy to architecture to execution—focused on building scalable AI-powered data products.
1) Identify high-value AI data products
- Convert enterprise data into monetizable and decision-support products
- Spot use cases with measurable ROI and fast paths to value
- Align AI initiatives with business strategy
2) Architect modern AI platforms
- Design with LLMs, RAG, vector databases, and agent frameworks
- Integrate enterprise data sources, documents, and APIs
- Build scalable and secure platforms in the cloud
3) Build Agentic AI workflows
- Design autonomous agents that reason, plan, and execute tasks
- Orchestrate tools, APIs, and enterprise data sources
- Implement human-in-the-loop governance for enterprise AI
4) Develop AI-powered data products
- Turn data into copilots, knowledge assistants, and decision systems
- Design reusable product frameworks and patterns
- Accelerate delivery with a modern AI stack
5) Operationalize AI in the enterprise
Governance & security
Responsible AI, risk management, policy, and controls that scale.
MLOps & LLMOps
Production operations, evaluation, monitoring, and change management.
Value measurement
KPIs, adoption, cost controls, and scaling AI across the org.
About Prashant
Technology leader specializing in AI, GenAI, and emerging Agentic AI systems for intelligent data-driven products.
Prashant has hands-on experience building production-grade AI systems that combine LLMs, RAG, vector databases, enterprise data platforms, and document processing pipelines (including OCR and structured data extraction) for complex enterprise use cases such as financial analysis, compliance workflows, and intelligent research assistants.
Core strengths
- LLM integration, prompt engineering, and RAG architectures
- Agentic workflows: tool use, planning, and orchestration
Platform expertise
- Cloud architecture, data lakes, vector search, enterprise AI services
- End-to-end productization: evaluation, security, and ops
Ready to build AI data products that scale?
Book the workshop and align your leaders and teams on a practical path from AI ideas to production-grade outcomes.