11 weeks ago VIDI was basically an experiment.
No team.
No funding.
No traditional legal background.
Just a simple idea:
What if founders could better understand financial and legal risk in a contract before signing it?
Since then:
• 90+ contracts analyzed
• $10M+ in total contract value reviewed
• agreements ranging from ~$40K to $6.7M+
• usage across multiple countries
• early repeat usage starting to emerge
One thing that surprised me early:
The strongest usage patterns appear when contracts become materially important to a business decision.
That observation changed how I think about the company.
At first I thought VIDI was simply “AI contract analysis.”
Now I think there may be a much larger opportunity around contract risk visibility before signing.
Still extremely early.
But over the last few days I’ve:
• started speaking with angels/operators
• opened a small SAFE round
• spent a lot of time learning how investors think about workflow businesses vs AI features
One thing I’m learning quickly:
Investors care much less about “AI analyzing documents” and much more about:
• repeat behavior
• trust
• workflow positioning
• whether the product becomes part of real decision-making
Still building every day.
Still figuring things out in public.
Curious if other founders experienced a similar shift where user behavior changed the company thesis.
VIDI: https://vidicontract.tech
If anyone around early-stage investing, AI infrastructure, or workflow software finds this interesting, happy to connect on LinkedIn as well - especially as I start conversations around the SAFE round.
LinkedIn: https://www.linkedin.com/in/meirambek-mukhametkaliuly-2b72272a4/
Hi Meirambek! Awesome work for just 11 weeks.
When launching your MVP, where did you first start talking about your idea? How were you able to get enough feedback to actually go through with what you were building, and get enough visibility? I just built a landing page speaking about my idea before committing to it, but I'm having a hard time finding the best place to seek feedback on it.
Anyone here who raised through a SAFE at the pre-seed stage - what ended up mattering most in investor conversations?
Still learning a lot in real time around positioning, traction, and how early investors evaluate workflow businesses vs AI features.
This is a fantastic real-world validation story — from 0 to $10M+ in reviewed contracts in 11 weeks is seriously impressive.
Quick question: How are you handling the trust gap? Founders putting a $6.7M contract through an AI tool is a big leap of faith — did the early users come from personal networks, or did you do something specific to de-risk that first review?
Love that user behavior is reshaping your thesis. That's the sign of a founder who's actually listening.
Wishing you well on the SAFE round.
Really impressive trajectory in such a short time, especially the speed at which you’re moving from early usage signals to a structured raise.
What stood out to me is how quickly things shift once real contract value / revenue context enters the picture. At that stage, it feels less like “early traction” and more like you’re starting to validate whether this becomes infrastructure vs just a useful tool.
I’ve noticed a similar pattern in other early-stage products: once usage starts connecting to real financial risk or decision-making, the feedback loop changes completely, users stop evaluating features and start evaluating trust.
Curious how you’re thinking about timing the SAFE relative to that signal maturity, are you optimizing for speed to capital, or waiting for a more stable usage pattern to emerge first?
Appreciate that 🙌 Still very early, so right now I’m mostly focused on learning, improving the product, and understanding where the strongest long-term fit actually is.
Strong signal on usage spiking for high-stakes contracts—that’s where this shifts from analysis to decision-making.
Also agree: investors care more about workflow + repeat use than “AI features.”
Curious how you’re moving into the pre-signing stage.
Appreciate it 🙌 still figuring that out in real time honestly. A lot of the learning so far has come from watching where trust and repeat behavior naturally start forming.
huge progress for just 11 weeks -turning a simple experiment into real usage and real contract volume that fast is impressive
love how the thesis evolved from “AI analysis” into workflow + decision infrastructure. that shift usually comes from actually listening to user behavior, not hype. congrats 👏
Appreciate it 🙌
That shift honestly surprised me too. The more usage came in, the more the behavioral side started standing out over the AI layer itself. Still very early, but definitely changing how I think about the product long term.