Deepfake detection and digital identity protection for public figures
Loti detects and removes deepfakes, impersonations, and unauthorized likenesses across social media and the broader public internet. The stack reveals a hybrid on-chain/off-chain architecture—Solidity, IPFS, and The Graph sit alongside AWS, Postgres, and Node.js—suggesting they're building enforceable IP agreements as smart contracts while running high-volume API services for content detection and removal. Active projects center on biometric verification, zero-knowledge identity, and legal ontology for on-chain rights enforcement, all critical for scaling protection across millions of potential impersonations.
Loti AI protects celebrities, public figures, and corporate intellectual property from deepfakes, impersonations, and unauthorized content replication. Founded in 2022, the company operates a detection and removal platform spanning social media, adult sites, and the broader public internet. Core offerings include likeness protection, content location and takedown services, and contract enforcement mechanisms. The team is headquartered in Seattle with distributed engineering across the U.S. and India, and is actively developing creator and consumer protection products alongside their current public-figure focus.
Loti runs Solidity, IPFS, and The Graph for blockchain/decentralized infrastructure; AWS, GCP, and Azure for cloud compute; PostgreSQL, MongoDB, and DynamoDB for data storage; and Node.js and Python for backend services. Docker and Kubernetes manage containerization and orchestration.
Loti is based in Seattle, WA. The company hires engineering and product roles in the United States and India.
Active projects include biometric likeness verification, zero-knowledge login prototypes, legal ontology for on-chain IP compliance, enforceable IP agreements in Solidity, and scalable API platforms for high-volume content detection and transaction processing.
Other companies in the same industry, closest in size
Loti's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.