G5infotech
G5infotech
  • Home
  • Gen AI
    • How do LLMs work?
    • Prompt Engineering
    • RAG Architectures
    • Model Context Protocol
    • How to Build MCP Agents
    • AI agents - MCP and A2A
    • AI Agents Architectures
    • Tree of Thought Visuals
    • Google IO 2025
  • Business Transformation
    • AI First Thinking
    • Business Value mapping
    • AI Advisory Services
    • Our Core GenAI Services
    • AI Transformation
    • Microsoft Copilot Agents
    • People-Powered AI
    • Executive Coaching GenAI
    • AI Strategy for Mid-sized
    • AI Maturity and Roadmap
    • How to use ChatGPT
    • Future Webinar Series
  • Learning Paths
    • AI Engineering Roadmap
    • ML, AI and GenAI Courses
    • Prompt Engineering
  • Careers
    • GenAI Internships
    • Interview Process
    • Internships FAQ
    • Showcase Skills
    • Mentors Hiring Process
    • Intern Info Sessions
    • AWS Cloud/SRE Internships
  • Contact Us
  • Blogs
  • Recorded GenAI Webinars
  • More
    • Home
    • Gen AI
      • How do LLMs work?
      • Prompt Engineering
      • RAG Architectures
      • Model Context Protocol
      • How to Build MCP Agents
      • AI agents - MCP and A2A
      • AI Agents Architectures
      • Tree of Thought Visuals
      • Google IO 2025
    • Business Transformation
      • AI First Thinking
      • Business Value mapping
      • AI Advisory Services
      • Our Core GenAI Services
      • AI Transformation
      • Microsoft Copilot Agents
      • People-Powered AI
      • Executive Coaching GenAI
      • AI Strategy for Mid-sized
      • AI Maturity and Roadmap
      • How to use ChatGPT
      • Future Webinar Series
    • Learning Paths
      • AI Engineering Roadmap
      • ML, AI and GenAI Courses
      • Prompt Engineering
    • Careers
      • GenAI Internships
      • Interview Process
      • Internships FAQ
      • Showcase Skills
      • Mentors Hiring Process
      • Intern Info Sessions
      • AWS Cloud/SRE Internships
    • Contact Us
    • Blogs
    • Recorded GenAI Webinars
  • Home
  • Gen AI
    • How do LLMs work?
    • Prompt Engineering
    • RAG Architectures
    • Model Context Protocol
    • How to Build MCP Agents
    • AI agents - MCP and A2A
    • AI Agents Architectures
    • Tree of Thought Visuals
    • Google IO 2025
  • Business Transformation
    • AI First Thinking
    • Business Value mapping
    • AI Advisory Services
    • Our Core GenAI Services
    • AI Transformation
    • Microsoft Copilot Agents
    • People-Powered AI
    • Executive Coaching GenAI
    • AI Strategy for Mid-sized
    • AI Maturity and Roadmap
    • How to use ChatGPT
    • Future Webinar Series
  • Learning Paths
    • AI Engineering Roadmap
    • ML, AI and GenAI Courses
    • Prompt Engineering
  • Careers
    • GenAI Internships
    • Interview Process
    • Internships FAQ
    • Showcase Skills
    • Mentors Hiring Process
    • Intern Info Sessions
    • AWS Cloud/SRE Internships
  • Contact Us
  • Blogs
  • Recorded GenAI Webinars

How I Help (Fractional | 8–10 hrs/week)

 I’m Satya Gunampalli, an AI transformation leader with 30+ years in tech leadership across IT infrastructure, SDLC and cloud migrations. I now help organizations adopt and scale Generative AI through strategic advisory and program leadership. I work 8–10 hours a week with select clients to translate AI vision into business impact.


  • Define AI strategy and roadmap aligned with business goals
     
  • Lead pilot programs for GenAI, RAG, and agent-based systems
     
  • Provide fractional program leadership to deliver high-impact use cases
     
  • Design AI-native architecture and tool integration (e.g. LLMs, vector DBs)
     
  • Guide SRE + AIops maturity with automation and incident transformation
     
  • Advise CTOs/CIOs as a thought partner on scaling internal AI capabilities

Copyright © 2025 G5InfoTech - All Rights Reserved.


This website uses cookies.

We use cookies to analyze website traffic and optimize your website experience. By accepting our use of cookies, your data will be aggregated with all other user data.

Accept