AI UpskillingFor enterprises
Your teams learn AI on their own work.
Ship working AI workflows in 2-3 days. See measurable improvement in 6 weeks.
Hands-on programmes for business and technology teams. Every group works on its own workflows, builds something usable, and sees what changed before and after.
- professionals trained on live workflows
- 180+
- professionals trained on live workflows
- students trained on real deployed use cases
- 300+
- students trained on real deployed use cases
- consistent CSAT across cohorts
- 4.5 / 5
- consistent CSAT across cohorts
- time to first working AI workflow
- 2–6 week
- time to first working AI workflow
- NDA first
- Runs on your approved tools
- Your data stays inside your environment
Delivered for
- India's Largest Health Insurer
IIT Bombay
So in general, enterprise AI is much harder and will take a long time.
Carnegie Global Tech Summit, April 2025
Harder because the work sits inside real systems, real data rules and real approval chains. That is where our programmes start: your teams, in your environment, on your own work, measured before and after.
The real demand is not for AI, but for people who can build production-grade software using AI.
Who it is for
Business teams and technology teams, each on their own work.
Business, Product & Support functions
BusinessProductOperationsSupply chainHRAdministrationFinanceCustomer service
Your teams work on their own reports, emails, documents, and repeat patterns. Every session is hands-on, building outputs on use cases that move their day-to-day work.
Technology teams
Full delivery teams or role-based cohortsBackendFrontendDataQADevOpsProductProduction support
Teams build in their own codebases, across greenfield and brownfield systems. Every session produces working code, tests, and changes on real use cases, as full teams or role-based cohorts.
Choose your starting point
Every team starts where it needs to. Build something new or improve an existing system. Most teams do both.
A typical technology-team journey
From first conversation to AI champions in nine weeks.
A focused, hands-on journey built around your team’s real work.
Weeks 0 – 2
Prepare
Pick one real use case. Align on goals, scope, and how your team works today.
Week 3
First workshop
Two days, hands-on. Your team builds a real solution, end to end, in your own environment.
Weeks 4 – 5
Apply it
Teams start using what they learned, with weekly support when they get stuck.
Week 6
Second workshop
Back to hands-on. This time, improve something that already runs in production.
Weeks 7 – 8
Build momentum
Teams apply the patterns to their own backlog, with support as needed.
Week 9
Hackathon
One day, real problems, judged with your leadership. Clear winners and next steps.
Outcome
AI Champions
Each team leaves with 1–2 champions who know what works, and help others adopt it.
Weeks 0 – 2
Prepare
Pick one real use case. Align on goals, scope, and how your team works today.
Week 3
First workshop
Two days, hands-on. Your team builds a real solution, end to end, in your own environment.
Weeks 4 – 5
Apply it
Teams start using what they learned, with weekly support when they get stuck.
Week 6
Second workshop
Back to hands-on. This time, improve something that already runs in production.
Weeks 7 – 8
Build momentum
Teams apply the patterns to their own backlog, with support as needed.
Week 9
Hackathon
One day, real problems, judged with your leadership. Clear winners and next steps.
Outcome
AI Champions
Each team leaves with 1–2 champions who know what works, and help others adopt it.
- Business teams can run a shorter two to four week version.
- We adapt this based on your teams and priorities.
What each team leaves with
Production-ready work, not demos.
Workflow
A real workflow, running with AI.
One piece of your team’s actual work, now faster, clearer, and partially automated.
A prompt pack, with a working harness
Reusable prompts for your team’s real tasks, with structure, tools, and data rules built in.
Way of working
A way of working your team can repeat.
Documented, so others can pick it up and run it without starting over.
Champions
Clear results, and people who can carry it forward.
Measured outcomes, and one or two people per team who can lead adoption from here.
Code
Working code in your repositories.
For technology teams, every exercise produces code and artefacts you can deploy.
Support
We stay with you after the workshops.
Office hours for up to 24 weeks, and an AI assistant based on what your teams built, adapted to your workflows, environment, and guardrails, available for up to one year.
Measured before and after
We look at how your work runs today, and again at the end.
Business teams
How long work takes, where it slows down, and how often it needs rework. We measure it before and after, using the same idea as engineering metrics, but applied to your day-to-day workflows.
DORA’s 2026 guidance expects an early productivity dip when AI tools arrive, the tuition cost of adoption. Our programmes are built to shorten it. DORA, The ROI of AI-assisted Software Development, 2026
Built-in safeguards
Built to operate within your environment, your controls, and your approval process.
Built inside your environment.
We work within the tools your teams already use. Nothing new to introduce or approve.
No sensitive data in prompts.
We use sample or sanitised data. No confidential or personal information is used during the programme.
Teams learn what to trust.
Teams review outputs before using them, so they build the habit of working with AI responsibly.
Works within your policies from day one.
The way of working fits your internal controls and data rules from the start.
We run the programme on whatever you have approved, or help you choose if you have not. What we teach is the way of working, and that carries across every tool.
Customer outcomes
Solutions engineered for impact
FAQs
Frequently asked questions
We start by understanding how each team works today. Then we run the sessions, including hands-on build workshops. By the end, every team walks away with:
- a working AI-assisted workflow
- a reusable prompt pack
- a simple, written way of working
- named champions who can lead adoption
You also get follow-up support for up to 24 weeks, plus an AI assistant based on what was covered, tailored to your environment.
Teams that run real business work. This includes functions like operations, finance, HR, customer service, marketing, and technology teams. You can run it team by team, or as a cohort across roles.
No. If someone is comfortable with tools like email, Excel, or internal systems, they can take part. Technology teams can go deeper and work in their own repositories, but that is not required.
A typical pilot runs 2 to 4 weeks for one or two teams. Sessions are scheduled around working hours. Each batch usually includes 15 to 25 people, grouped by team.
No. Prompting is one part of it. Teams also learn:
- where AI works well and where it doesn’t
- how to check and trust outputs
- how to choose the right tool for a task
- how to turn workflows into something repeatable
The goal is not prompts. The goal is better ways of working.
We work with what you have already approved. This could be ChatGPT, Claude, Gemini, Microsoft Copilot, or others. If you have not chosen yet, we help you decide during the pilot.
Yes. We sign an NDA upfront. Everything runs inside your approved tools and environment. We use sample or sanitised data during the programme, and data rules are built into how teams work.
We measure how work runs before we start, and again at the end. For business teams, this usually means time, turnaround, and quality. For technology teams, we look at delivery speed, defects, and review cycles.
The idea is simple: show what changed, not just what was taught.
Pricing is fixed per pilot. Once we understand your teams, workflows, and goals in a discovery call, we share a clear scope and a fixed fee.
Your teams continue from what they have already built. Champions carry the work forward internally. You can extend to more teams, add leadership sessions, or schedule check-ins as needed.
Yes. Business and technology teams learn AI on the tools they already have and on their own work. They ship working AI workflows in 2 to 3 days, with measurable improvement in 6 weeks.
Yes. Hands-on AI training for business teams, technology teams and universities, where participants build on their own work and results are measured.
Bring us one team and one process.
Forty-five minutes with the person who owns it. We come back with a two-page pilot scope, a baseline plan and a fixed price.