Healthcare systems depend on absolute trust in data, identity, and communication, where even minor inaccuracies can have life-altering consequences. As hospitals and providers digitize records, enable telehealth, and integrate AI into diagnostics and operations, they face growing exposure to synthetic data, impersonation, and manipulated inputs. RealityChek introduces a verification layer that ensures every interaction—patient records, clinician communications, and system inputs—is authentic. This safeguards clinical decision-making by ensuring that care is based on verified, trustworthy information.
Fraud in healthcare extends beyond billing abuse into identity theft, prescription fraud, and falsified medical records. AI-generated identities and deepfake documentation can be used to access services, obtain controlled substances, or manipulate insurance claims. RealityChek’s detection capabilities analyze behavioral patterns, content authenticity, and identity signals in real time, identifying anomalies before they enter critical workflows. By preventing fraudulent access and submissions, it protects both patients and providers while reducing financial and regulatory risk.
Patient identity verification is a persistent challenge, particularly with the rise of remote care and digital onboarding. Traditional methods can be bypassed using synthetic identities or manipulated credentials, leading to mismatched records and compromised care. RealityChek continuously validates identity throughout the patient journey, ensuring that the individual receiving treatment is accurately linked to their medical history and records. This reduces the risk of medical errors, duplicate records, and unauthorized access to sensitive health information.
Healthcare operations rely heavily on accurate data flows across interconnected systems—electronic health records, lab results, imaging systems, and insurance platforms. AI-driven manipulation of these data streams can disrupt diagnoses, delay treatments, or lead to incorrect clinical decisions. By embedding detection directly into these systems, RealityChek ensures that incoming data and communications are genuine. This enhances the reliability of clinical workflows and supports better patient outcomes by maintaining data integrity at every stage.
As healthcare continues to adopt AI for diagnostics, automation, and patient engagement, the need for a robust “truth layer” becomes essential. RealityChek provides this foundation by integrating AI detection, identity validation, and fraud prevention into a unified framework tailored for healthcare environments. It enables providers to innovate with confidence while maintaining compliance, protecting patient safety, and ensuring that trust remains at the core of every interaction in an increasingly digital and AI-driven care ecosystem.
A unified truth and identity layer—integrating the most advanced detection models to secure enterprise transactions.
We analyze text, images, video, and voice to determine whether content is AI-generated, altered, or authentic. Using advanced forensic models and signal analysis, we identify manipulation before it enters decision-making systems—reducing exposure to misinformation, fraud, and reputational risk.
We verify who or what is behind every interaction, combining device signals, behavioral patterns, and contextual data to establish identity confidence. Each entity is assigned a dynamic trust score, enabling real-time risk assessment across users, partners, and systems.
We design frameworks that structure raw data into clear, predictive signals. From KPI mapping to real-time dashboards, every insight supports smarter, faster decisions.
We operate a multi-model decision engine, combining leading third-party detection systems with our own proprietary technology. This layered approach improves accuracy, reduces false positives, and continuously adapts as new AI models and attack vectors emerge.
We deliver our capabilities through APIs, SDKs, and native integrations, embedding directly into enterprise products and workflows. From onboarding to moderation to internal operations, we bring truth verification into the core of how systems operate.
We make truth visible and actionable by applying clear, persistent labels to content and identities. Each label is backed by attribution data and confidence signals, enabling users, platforms, and regulators to instantly understand what is real, synthetic, or unverified.
We maintain a comprehensive, tamper-resistant record of detections, identity validations, and transaction decisions. This creates a verifiable audit trail that supports regulatory compliance, internal governance, and forensic analysis in AI-driven environments.
We're in Beta and hand-picking partners to shape what comes next. If you are interested in early access, enterprise integration, or exploring our AI verification and identity infrastructure, please contact us, tell us your needs, and we'll build a solution for you.