Why Dharmic Data
Dharmic Data I spent more than ten years working across software and teaching. Now I help people choose one useful AI project, test it against their work, and decide what is worth doing next.
I spent more than ten years working across software and teaching. Now I help people choose one useful AI project, test it against their work, and decide what is worth doing next.
Bring one workflow or repository. We will define a small experiment and decide which tools fit it. You leave with clear data boundaries and a written 30 day test. Shakti shows the same method in public.
What AI guidance gives you
You leave with a clear use case, a tool and subscription choice, data boundaries, and a small test you can run over the next 30 days.
Start with your workflow
Name the work you do now, the friction you feel, and the result that would matter.
Choose local or cloud
Use local AI when privacy or control matters. Use a hosted model when speed and reach matter more.
Set data boundaries
Decide what the model may read, what stays private, and which actions always need review.
Build one small test
Test one task before you automate a whole job or buy more infrastructure.
Trace model and tools
Inspect the prompt, context, tool calls, outputs, cost, and failure cases.
Leave with next steps
Write the next experiment, the plan that fits it, and what evidence would change your mind.
Build, then show the work
A project earns a place here when the useful path works and the evidence is visible.
01 - Start with a person
Write down who may use the project and the small task they need to complete.
02 - Use named sources
Build the shortest useful path and keep every source close to the claim it supports.
03 - Test and publish
Run known cases, save the results, name what failed, and invite the next builder.
Showing the proof
Four views of Shakti show the live result, the five borough sample, the source trace, and the no AI public runtime.
Hear from people like you
These nine video reviews come from Jai's teaching with QEDC in Queens. Each person brought different work, but they all needed a first step they could use.
Built confidence using AI in client workSeema KothariReal estate
Found the next move after years of frictionNicholas StebenneFounder, Marketito
Made her ideas easier to put into actionCareen GFounder, Synergized Strategies
Moved from scattered courses to a useful next stepToyaFuture entrepreneur
Turned AI curiosity into practical client toolsKathy MillsPrincipal, kamil graphics
Clarified how AI can support community buildingParul KumarCo-founder, The Devi Circle
Made the business case for AI more concreteNgozi OditaFounder, AFRICANXT
Rebuilt planning around her environment and strengthsAnne FlanaganOwner, Anne Flanagan LLC
Saw what was possible for a health care practiceSamina QuraishiDoctor of AcupunctureNine published video reviews. No names or outcomes were added for this page.
Book AI guidance · $125These case studies show what people worked on with Jai and what they reported after the work changed.
Selected case studies
Participant reported85% less time spent onboarding new hiresHow a real estate leader reclaimed more than 15 hours a week
Participant reported$6,500 in event risk uncoveredHow Marketito found the vendor problem worth solving
Participant reportedThousands saved on copywriting and designFrom overwhelm to a complete AI-built business platform
Participant reportedMore than $30,000 in traditional build cost avoidedFrom three months to a global-ready platform in 35 minutes