For Business
Role-based AI training for HR, finance, marketing, sales and product teams. Built around the tasks your people run every week.
Prefer to read first? See what each track covers.
Why most AI training fails
Every one of these is fixable, and each one shaped how the tracks are built.
A course that teaches prompting in the abstract leaves your team to work out how it applies to a variance report or a hiring rubric. Most never make the jump.
Training built around one vendor's interface is obsolete the moment the interface changes. What lasts is the judgement about when to use AI and when not to.
Seat licences get bought, completion is never measured, and the following year nobody can point at what changed in the actual work.
What actually changes
The specific tasks that get faster or better once the track is done.
After the track, this is what changes in the week-to-week work.
After the track, this is what changes in the week-to-week work.
After the track, this is what changes in the week-to-week work.
After the track, this is what changes in the week-to-week work.
After the track, this is what changes in the week-to-week work.
The catalogue
Each is ten modules, sixty topics and thirty-nine labs. Same structure, content written per role.
Inside a module
Every module in every track is built to the same shape, so a sponsor knows exactly what a seat buys.
What the module covers, written for the role rather than the tool.
Stated up front, so a sponsor can check them against the job.
Run against a real artefact: a CV pile, a ledger export, a call recording.
The same task attempted across ChatGPT, Claude and Gemini, then compared.
Output that stays with the learner and goes back into the work.
Tools covered
The same task is attempted across more than one assistant and the outputs compared, so your team is not locked to whichever vendor you standardise on this year.
How a rollout runs
Nothing is bought at full scale before a pilot group has been through it.
We map the roles you want covered against the five tracks and agree what success looks like before anything is bought.
A small group runs the track end to end. You see completion, the projects they produce, and the questions they raise.
Seats are issued across the wider team with your admin controlling access, cohorts and reporting.
Completion, project output and tool adoption are reported back against what you agreed at scoping.
Delivery
The track content is the same. What changes is the pace and how much live time you want.
Seats are issued and people work through the track on their own time. Lifetime access, so they can return when a task actually comes up.
The team moves through together on a schedule, with checkpoints at the end of each module block. Better for teams that need shared vocabulary fast.
The track is self-paced, with live sessions run against your own workflows and documents at agreed intervals.
Fair questions
All four are reasonable. Here is the honest answer to each.
“We already pay for ChatGPT licences
Then you have solved access, which is the easy half. The licence does not tell a recruiter which parts of screening are safe to hand over, or a finance analyst which numbers the model will confidently invent. That judgement is what the tracks carry.
“Our people can learn this from YouTube
Some will. The ones who do tend to already be comfortable with the tools. The value of a structured track is the middle of the distribution: the people who will not spend their evenings piecing it together, and who quietly keep doing the task the old way.
“We ran AI training last year and nothing changed
Usually because it was generic and nobody measured it. The two fixes are in this page: content written per role, and a pilot with agreed success criteria before a full rollout is bought.
“Our data cannot leave the building
Labs run in the learner's own tool accounts against material they control, so working documents do not pass through us. If your policy blocks public AI tools entirely, tell us at scoping; that changes which labs are usable.
How this differs
A generic AI course, or asking an internal champion to run enablement.
| Generic AI course | edBuddy Pro tracks | Internal enablement | |
|---|---|---|---|
| Who it is written for | Anyone, any role | Your team, by role | Whoever volunteers |
| What it teaches | The tool's interface | The task, using whichever tool fits | Whatever the internal champion knows |
| Shelf life | Until the interface changes | As long as the workflow exists | Until that person leaves |
| What the learner keeps | A completion badge | Ten projects built on real artefacts | Notes, usually |
| Failure modes covered | Rarely | Bias, confidentiality, invented figures, per role | Ad hoc |
| How you measure it | Seats issued | Completion, projects, tool adoption | Not measured |
Administration
Seat allocation, completion by team and per-person progress, exportable for your own reporting.
Illustrative layout
Data and security
The short version: your working documents never pass through us.
Labs are run by the learner, signed into their own assistant, against files they already hold. We host the course and the progress record; nothing else crosses the line.
Labs are run in the learner's own ChatGPT, Claude or Gemini account against documents they control. We host the course, not your data.
Account and progress data is handled under India's Digital Personal Data Protection Act, 2023. Full detail in the privacy policy and security page.
Pricing
Individual seats are ₹4,999 one-time with lifetime access and GST included. Team pricing depends on headcount, track mix and delivery format.
Questions
Tell us the roles and rough headcount and we will quote for that rollout. Volume pricing applies as the seat count grows.
The five tracks are built around role workflows rather than job titles, so a people-ops analyst and an HR business partner both fit the HR track. At scoping we go through your org and agree which track each group takes.
No. Every track is built on the assumption that nobody writes code at any point. The tools used are ChatGPT, Claude, Gemini and the document and spreadsheet software your team already has.
Each track carries ten projects built on real artefacts: a screening rubric, a variance commentary, a campaign brief. Those stay with the learner and with you.
Learners work in their own accounts on the AI tools, so their material does not pass through us. Course accounts and progress data are covered by our privacy policy and the DPDP Act.
We agree the reporting with you at scoping. As a minimum you get enrolment and completion progress for every learner on the rollout.
Tell us which roles you want covered. We will scope it, run a small group through it, and you decide from there.