Abhishek Jyothi
Founder & CEO
Sets the product vision and leads how ValWithProof turns raw ideas into evidence founders can act on.
LinkedInGet real market insights, expert feedback, the right APIs and a clear report — before you write a single line of code.
Every mentor here passed an identity check. They set their own price — you see it before you book.
Example idea · hostel meal planner
Your idea against similar ideas in the same category.
Matched against 278,288 real records.
Written once. Every feature reads it.
What the idea implies it needs.
Ranked by what your product actually needs.
Food-tech operator · Hyderabad
Offer a slot. The mentor confirms it.
Never confirmed until payment succeeds.
Slot held while the mentor decides
Or an alternative slot is offered
Your brief and the Meet link are ready
An example idea, shown in the product's own screens.
Each one is a complete engine in its own right. You write your idea once and it runs through all three — no feature asks you to type it again.
Your idea scored against 278,288 real records — hybrid lexical and semantic retrieval, no language model inventing numbers.
The capabilities your idea implies, matched to a catalogue of real APIs and ranked by what your product actually needs.
Operators who have shipped something like it. They set their own price, and you see the exact amount before you book.
No account setup, no configuration, no waiting on a model to think about it.
A paragraph of plain English, entered once. Nothing structured, no forms, no taxonomy to learn.
Your idea is matched against 278,288 real records — hybrid lexical and semantic retrieval, no language model inventing numbers.
The APIs your idea implies, ranked. Then the operators who have shipped something like it.
From retrieval over 278,288 real records, using TF-IDF with a 160-dimension SVD and a hybrid lexical/semantic blend. No number in a report is generated by a language model. That constraint is the entire point of the product, and it is why the Reports engine loads a real index at startup rather than calling an API.
No — once. It is the only input in the product. The report scores it, the API engine reads it for the capabilities it implies, and the expert brief is matched on the same text. Change it on the Idea dashboard and every feature picks up the new one.
Reports and API recommendations are free — generate as many as you like and download them. The only thing that costs anything is time with a mentor, and the mentor sets that price themselves. You see the exact amount before you book, in rupees.
No. Every feature runs on its bundled data with no keys set — the API engine falls back to a catalogue of 76 APIs and deterministic extraction, and the other two never call out at all. Adding a language-model key improves the prose in API explanations; it does not change any score.
Seven of us, working on the same problem: that founders are asked to bet a year of their life on an opinion.
Founder & CEO
Sets the product vision and leads how ValWithProof turns raw ideas into evidence founders can act on.
LinkedInCo-Founder
Works across product and platform, shaping how validation signals are captured and scored.
LinkedIn
Co-Founder
Focused on the mentor network — how operators are sourced, matched, and kept engaged.
LinkedIn
Co-Founder
Builds the systems behind real-time signal collection and keeps the pipeline fast and reliable.
LinkedIn
Co-Founder
Drives go-to-market and founder growth, getting ValWithProof in front of early teams.
LinkedIn
Co-Founder
Owns design and the founder experience, from first click to reading the final report.
LinkedIn
Co-Founder & Data Analyst
Turns raw market and demand signals into the numbers behind every validation score.
LinkedInFounders validate an idea and book mentors. Mentors keep a profile, set their own price and take sessions. Both start at the same door.