TruthGuard – AI System That Detects Invalid Survey Responses

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Hi HN , I’m Vivek Jaiswal, Founder & Technology Strategist at QBits Marketing Research. We built TruthGuard, an AI-powered validation platform designed to detect synthetic, low-quality, or fraudulent survey responses in large-scale research datasets — a $10B+ issue in global data collection. TruthGuard runs a multi-stage validation pipeline combining: LLM-based semantic verification (OpenAI, Anthropic, Azure models) Vector similarity scoring using Qdrant/Chroma Anomaly & pattern detection for response duplication Adaptive thresholding tuned with live dataset feedback It processes 100K+ responses per day with 99%+ accuracy, cutting operational costs by over 60% for our enterprise clients. I’d love to get feedback from this community — especially around: Improving real-time validation at scale Better approaches for prompt consistency between multiple LLMs Efficient ways to benchmark accuracy on mixed human + AI datasets Code architecture and system design overview (non-confidential parts) are here: github.com/vivekjaiswal-ai/truthguard Thanks for reading — open to ideas, critiques, and collaborations! — Vivek

Visit product View on Hacker NewsOct 31, 2025

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