Deceptio AI

Deceptio.ai is a St. Petersburg, FL-based startup offering AI-driven deception detection for written and spoken communications. Founded 2023, veteran-owned, approximately 1 employee, $0 revenue per Latka. Marketed to law enforcement, legal industry, insurance, and investors. Media coverage includes Bloomberg Law (Nov 2025, skeptical: ‘App Marketed to Lawyers Contends’), The Atlantic (Jul 2024, critical), and Fox13 News. Technology donated to Skull Games Task Force (anti-human-trafficking). Appears pre-product-market-fit — media coverage exists but no evidence of adoption by legal practitioners. ALL Facebook mentions appear to be from coordinated spam — the same account posting identical text (‘deceptio.ai (this is creepy good)’) across dozens of legal industry Facebook pages. No independent validation of deception detection accuracy found. Scientific basis for AI lie detection remains highly contested. AI deception detection output would likely face serious Daubert challenges — courts require testing, error rates, peer review, and accepted standards, none of which are published for this tool.

Key Capabilities

• Text analysis: Analyzes written statements, emails, and texts for linguistic indicators of deception
• Voice analysis: Assesses spoken communications for behavioral deception markers
• Use cases: Witness credibility assessment, insurance fraud detection, due diligence vetting, law enforcement investigations

Who It’s For

Primarily marketed to law enforcement investigators and insurance fraud analysts. Legal industry applications include litigation attorneys assessing witness credibility and VC/PE due diligence teams vetting founders.

What We Haven’t Verified

• No independent validation of deception detection accuracy found — scientific basis for AI lie detection remains contested in academic literature
• $0 revenue reported by Latka — appears pre-revenue
• Bloomberg Law (Nov 2025) and The Atlantic (Jul 2024) covered the company with skeptical framing
• No G2, Capterra, or review site presence
• No confirmed paying customers in the legal industry
• AI model and methodology not publicly documented
• Ethical implications of AI deception detection in legal proceedings not addressed by vendor