Maven - Building Gen AI Agents for Enterprise: Beyond the Hype [Update 05/2025]
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Genre: eLearning[/center]

Build Production-Ready SaaS Agents that work
You're drowning in AI vendor promises and overlapping tools, wondering: "Which of these actually solves our problems?"

After working with organizations across fintech, supply chain, and manufacturing, we've seen the same pattern: businesses know AI matters but can't identify use cases that deliver measurable ROI.

This course cuts through the noise. You'll build production-ready GenAI SaaS Agents using no-code and low-code approaches-without needing a programming background.

You will build full-scale websites with an AI backend.

Two-Part Approach:

No-code tools for building AI agents
Low-code approaches for complex agent systems
What Makes This Different

We focus on the "what" before the "how"-use case identification, business value assessment, and strategic deployment over technical implementation.

7 Modules: From Concept to Demo

Module 1: GenAI landscape and Industry impact
Module 2: No-code agent building blocks (loveable & n8n)
Module 3: Enterprise RAG with production guardrails
Module 4: Vertical AI Agents and Orchestration
Module 5: Deploying a production-ready website with an AI backend
Module 6: Capstone workshop with peer feedback
Module 7: Demo day-present your working system
What you'll learn
Master the what, why, and how of Generative AI by building Enterprise-Grade Agents that go beyond the basics and actually move the needle

Deploy Your First Production Agent in 7 Weeks (with enterprise grade template)

Get hands-on with use case identification workshops and business value scorecards

Analyze real case studies from fintech, manufacturing, and consulting to recognize patterns of successful vs. failed implementations

Use No-Code tools to build your first AI Agent

Build NoCode AI Agents That Handle Real Business Workflows

Master AgentPro and similar platforms to create multi-step agent workflows with memory, reasoning, and tool integration

Implement guardrails and safety controls that meet enterprise compliance standards

Deploy agents that can handle customer inquiries, data analysis, and document processing at scale

Design Enterprise RAG Systems That Actually Return Relevant Results

Apply advanced chunking strategies and embedding techniques to optimize information retrieval accuracy

Build RAG systems with feedback loops that continuously improve relevance and user satisfaction

Deploy AI Systems with Enterprise-Grade Safety and Scalability

Configure monitoring dashboards that track system performance, costs, and user satisfaction metrics

Implement multi-layered safety controls, including content filtering, output validation, and escalation protocols

Design deployment architectures that scale efficiently while maintaining response quality

Present and Defend Your AI Solution to Stakeholders

Structure presentations using the Problem-Solution-Impact framework to communicate clearly to non-technical executives

Develop implementation roadmaps with timeline, resource requirements, and success metrics for organizational buy-in

Demo live systems during our capstone showcase, receiving feedback from peers and industry mentors

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