Your AI Investment
Isn't Working.
85% of enterprise AI licenses go unused.
₹17.1 L/year wasted
Three ways your AI investment is losing value
AI Waste
of AI licenses go unused
Unmapped Potential
of projects use AI systematically
Data Risk
Untrained employees paste data into public AI
How we fix it — and prove it
We train your team on AI tools, measure the impact before and after, and give you numbers you can act on.
Train
- Hands-on AI tool training on your team's actual projects
- Prompt engineering + context engineering applied to real workflows
- Tool-specific: Gemini, Copilot, Claude, or hybrid
Measure
- Baseline verification cost before training begins
- Dependency risk mapping per tool and per team
- Identify where AI output costs more to verify than it's worth
Verify
- Post-training verification cost — did the numbers improve?
- Updated risk profile per tool, per team, per workflow
- 30-day check-in to confirm results held
Your team walks away with skills and numbers
Prompt & Context Engineering
How to use AI effectively — applied to their actual projects, not generic demos. The skills layer.
Verification Cost & Risk Profile
Before/after measurement of what AI actually costs to verify. The numbers layer. Take it to your CXO.
One methodology. Two tracks.
Vendor-agnostic training that works with any AI tool your org uses.
For All Teams
AI productivity training for every department — on their actual projects, not generic demos.
- Prompt & context engineering for real workflows
- AI-assisted writing, analysis & decision-making
- Data security awareness & guardrails
For Engineering
AI-assisted development training for your engineering team — coding, testing, version control.
- Agentic coding & codebase-level AI workflows
- AI-powered testing, code review & PR automation
- Security-aware AI usage & data policies
Led by someone who's done it at scale
After Training + Measurement
AI Waste
AI-Mapped Projects
Data Security
30 minutes · No obligation