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Clients Don’t Pay for Just an AI Agent

Pradip Nichite17 June 2026Watch on YouTube

Part of series

Ep. 11 · Agent Futuresmart Actually

View the series

Description

When a client hires us, they don’t pay us just for building an AI agent or RAG system. They want someone who can understand their business, their workflows, and suggest what can actually be built. Whether it is feasible or not. Whether they have the right data and infrastructure or not. And if we build something, how it is going to integrate with their existing system. Sometimes it is not straightforward. We spend a really good amount of time understanding their data, workflows, and proprietary systems. And the most important part is to be available when they have a problem, fix things, and help their team. #AI #RAG #AIAgents #AISolutions #ProductionAI #FutureSmartAI

What you'll learn

  • Clients pay for business understanding and advice, not just for building an AI agent
  • Data assessment and infrastructure evaluation are critical before starting development
  • System integration with existing business processes requires time and deep understanding of workflows
  • Ongoing support and problem-solving are essential parts of the client relationship
  • Determining technical feasibility requires knowledge of the business, available data, and existing systems

Frequently asked questions

Where do companies spend the most time on AI agent projects?
Most time is spent understanding the client's business data, workflows, and proprietary systems, rather than coding itself.
What should you assess before building an AI agent for a client?
You need to evaluate technical feasibility, whether they have the right data, if their infrastructure is suitable, and how it will integrate with existing systems.
Why is long-term support important in AI agent projects?
Clients need support when issues arise and their teams require help to effectively implement and use the systems.
What role does business understanding play in building AI solutions?
Business understanding enables you to make useful suggestions, set realistic expectations, and tailor solutions to the client's actual needs.

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