The Next Evolution of Trust: Realistic Reviews

    (Coming Soon)

    Most review systems are just numbers and text. Our Realistic Review feature—launching soon—is designed to strip away the "fake" and give your customers a 100% authentic look at a business before they step inside.

    What Makes a Review "Realistic"?

    Verified Visual Evidence

    No more stock photos. Realistic reviews will encourage users to upload unedited, real-time photos and videos of their experience (e.g., the actual food served, the real condition of a PG room, or the live atmosphere of a gym).

    Mandatory "Niche" Tags

    Users won't just say "it was good." They will rate specific specialized criteria like hygiene, staff behavior, waiting time, and value for money.

    The "No-Filter" Policy

    We are creating a space where honest, constructive feedback is prioritized over paid promotions, ensuring that what you see on the map is what you get in person.

    Review Verification

    Every realistic review will be cross-referenced with our "Verify People" tech to ensure it’s coming from a real person who actually visited that zone.

    Coming Soon: How It Will Work

    Interactive Review Prompts

    Instead of a blank box, we’ll ask specific questions: "How was the crowd at the Rajouri Garden market today?" or "Was the liquor shop inventory as per the app?"

    Video Snaps

    A 10-second "Live Look" option to show the current state of a shop or stall. Instant visual proof of what's happening right now.

    Realistic Badges

    Reviewers who consistently provide helpful, honest, and verified photos will earn a "Trusted Guide" badge in their zone.

    "Standard reviews are just opinions. Realistic Reviews are digital proof."

    The Difference

    Comparing Standard vs. Realistic review architecture.

    FeatureTraditional ReviewsOur Realistic Reviews
    Trust FactorLow (can be faked / bought)
    High (Verified & Cross-checked)
    VisualsOften missing or outdated
    Live, user-shot photos & videos
    DetailingVague (e.g. "Good shop")
    Category-specific (Staff, Speed, Hygiene)
    AccuracyOne-sided opinions
    Balanced & context-driven feedback