About Voltus AI Academy
Voltus AI Academy is an initiative by VoltusWave, a software product company with nine years of building software and more than five years building AI products.
9 YRS
Building Software
VoltusWave is a software product company.
5+ YRS
Building AI Products
The experience the Academy is built on.
12 WKS
One Practical Programme
AI Engineering & Agentic AI.
Charles Sasi Paul
Founder & CEO, VoltusWave Technologies
Founder & CEO
Built by engineers. Backed by real AI experience.
Charles Sasi Paul
Founder & CEO, VoltusWave Technologies
Most AI academies are built by trainers and academicians. Voltus AI Academy was built by Sasi — a seasoned engineer and technology leader who has spent decades building and leading engineering teams.
With over 30 years of experience in software engineering and technology leadership, Sasi has worked alongside CIO and CTO teams and has himself served in senior technology leadership roles, including VP of Engineering and CTO.
His career spans technology leadership roles at Virtusa, Thomson Financial, Thomson Reuters, Cura Software Solutions and innRoad. Since 2008, he has also been Managing Partner at Sycontec, an AI engineering services firm.
Today, as Founder & CEO of VoltusWave Technologies, Sasi leads the development of AI-native enterprise platforms, Agentic AI and AI agent workforces, focused on solving real-world business problems across freight, logistics and enterprise technology.
30+ years Software engineering and technology leadership
VP Engineering · CTO Senior technology leadership roles
Since 2008 Managing Partner at Sycontec, an AI engineering services firm
Technology leadership roles at
Virtusa
Thomson Financial
Thomson Reuters
Cura Software Solutions
innRoad
Training team
The Academy’s training team.
Lead Trainer
Thribhuvan Reddy
Lead Trainer, Voltus AI Academy
Thribhuvan holds a dual degree from BITS Pilani — a B.E. in Computer Science and an M.Sc. in Economics — and began his career as a Software Developer at LTI Mindtree, working with Python, Flask, SQL and PySpark. He brings that same engineering discipline into the classroom.
As an AI/ML Instructor and now Subject Matter Expert at Edunet Foundation, he has trained students across Machine Learning, Deep Learning, NLP and Computer Vision, along with Generative AI, Transformers and Hugging Face tools — with a strong focus on hands-on, practical learning. He teaches in English, Telugu and Hindi.
Machine Learning
Deep Learning
NLP
Computer Vision
Generative AI
Transformers
Assistant Trainer
G. Akshita
Assistant Trainer, Voltus AI Academy
Akshita is a Computer Science graduate who brings hands-on AI training experience into the classroom. As an AI Trainer with Magic Bus India Foundation’s IBM SkillsBuild initiative, she helped students and young learners build practical skills in AI tools, chatbot development and web applications through project-based activities.
She pairs this with technical knowledge across Python, SQL, Machine Learning, NLP and LLM API integration, along with experience in Knowledge Transfer and technical project coordination — giving her a structured, practical approach to teaching rather than simply walking through theory.
At Voltus AI Academy, she works closely with students as they build their projects, providing step-by-step guidance that helps turn concepts into working applications.
Python
SQL
Machine Learning
NLP
LLM API integration
Our approach
A product company’s standard, applied to teaching.
01
Built by a product company, not a training institute
The programme is built around working engineers and product-company experience.
02
Live and cohort-based
Live sessions with a working engineer, a cohort, and a fixed weekly rhythm with deadlines that hold.
03
Portfolio-ready projects, evaluated and reviewed
Six portfolio-ready projects, each evaluated and reviewed line by line by a working engineer.
How students work
Build it. Ship it. Prove it.
Students work through practical, evaluated software-building work.
Build
Six portfolio-ready projects in twelve weeks
A weekly assignment, released on Monday with a Friday deadline.
Ship
Portfolio-ready work
Portfolio-ready, evaluated and engineer reviewed.
Prove
Reviewed by a working engineer
Every assignment is reviewed line by line by a working engineer within 48 hours — not automated grading.
Apply
Twelve weeks, six portfolio-ready projects, and a working engineer reviewing every assignment within 48 hours. New cohorts start monthly.