@advocaterajat743
Rajat KaushikFounder▲7
Developer, VakilDost™
6d ago · AI Adoption · Noida

A legally correct AI answer is not always a useful answer

I've been thinking about this a lot while building VakilDost.
Imagine someone in India lends ₹50,000 to a friend. The money is transferred through UPI, repayment is promised over WhatsApp, and months later, nothing comes back.

Most AI tools can explain the legal remedies available.
But that's only half the problem.

Can the person actually prove it was a loan? Are the messages sufficient to establish the repayment agreement? What's missing? And what should they realistically do next?

That's the gap I'm trying to address with VakilDost, an AI powered legal information platform focused on India.

The idea is simple: don't just explain the law. Help people understand their facts, available evidence, missing information, and possible next steps.

We're still at an early stage, and I'm learning that building AI for legal problems requires much more than generating convincing answers. Accuracy, trust, and knowing when the AI should acknowledge uncertainty matter just as much.

I'd love to hear from other founders building AI products in areas where trust really matters.

How are you testing whether your AI is genuinely helping users make better decisions, rather than just giving them answers that sound impressive?

Comments2

  • @ryanallis
    Ryan Allis
    Founder of AI Lounge and SaasRise, helping founders reach $100M+ exits
    5d ago

    The ₹50,000 UPI loan is the right example, because the real test is what the person does after reading the answer. I'd call a handful of users two weeks later and ask whether they sent a notice, got their money back or gave up, since that tells you more about whether VakilDost helped than any rating of the answer itself.

  • @advocaterajat74
    Rajat Kaushik
    Founder, VakilDost™ | Advocate | Building Legal AI for India
    5d ago

    Thank you, Ryan! That's a valuable insight. Our vision for VakilDost™ is to go beyond explaining laws and help people understand their legal position, available evidence, missing proof, and next steps. I completely agree that legal AI must acknowledge uncertainty rather than provide misleading confidence. Your suggestion about connecting AI assistance with professional legal services is particularly interesting. We're exploring how to integrate optional advocate-led drafting and document review while maintaining trust and regulatory compliance in India. From your experience, what would you prioritize validating first: the evidence-based AI experience or the paid professional review model?

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