MP

Work

Evidence over adjectives.

Every engagement below follows the same shape: a real problem, a defined role, something built, and an outcome that can be pointed at.

Discuss a similar engagement
Case study 01Education

AI & entrepreneurship program

Engineering institution · innovation cell

Students understood AI tools in isolation but could not connect them to a venture, a workflow or a customer.

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Case study 02Startups

AI-native company / founder workshop

Incubator & early-stage founder cohort

Founders were hiring for functions that agents and automation could already cover, slowing burn-to-output ratio.

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Case study 03Institutions

Faculty AI enablement

University faculty & academic leadership

Faculty adoption was uneven, with policy uncertainty around teaching and assessment.

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Case study 04Workshops

Student AI builder program

Multi-campus student cohorts

Students consumed AI content but shipped nothing.

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Case study 05AI systems

Startup MVP / AI system

Early-stage startup teams

Teams needed a working product surface before they could test demand.

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Case study 06Institutions

AI knowledge partner / campus transformation

Institution-wide engagement

One-off workshops created awareness but no durable capability.

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02 / Selected impact

Proof, not positioning.

25,000+
Students engaged
20+
Startups worked with
Nationwide
Sessions & programs across India
Multiple
Institutions & innovation ecosystems
AI systems
Agents · Automation · MVPs · Platforms

Institutions & ecosystems engaged

  • IIT Hyderabad
  • IIT Bombay
  • IIT Delhi
  • Engineering institutions
  • MBA institutions
  • Universities & schools
  • Startup ecosystems

13 / Open channel

Let's build what's next.

Building AI-ready people, institutions and organizations for the AI-native economy. Tell me the audience, the timeline and the outcome you need — I'll reply with a concrete shape for the engagement.

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Email
maazaivalytics@gmail.com
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Connect with Maaz
Based in
Bengaluru, India