Refine builds an AI-powered review platform that detects serious errors in academic articles and technical documents before they reach referees, regulators, customers, or opposing experts. Its checks cover mathematical reasoning, calculations, logic, evidence, internal consistency, claims, references, and agreement between prose, tables, figures, and code. The company works with clients in academia and scientific research, academic publishing, universities, central banking and financial regulation, enterprises, and legal and litigation.
Under the hood, a proprietary harness coordinates frontier AI models alongside deterministic checkers and purpose-trained classifiers. The classifiers are trained on documents seeded with subtle errors that individual models commonly miss. Technical work spans independent AI verification, AI/LLM orchestration, document error detection, cross-modal consistency checking, and mathematical reasoning verification. A single review runs roughly 300 times the compute of a standard AI call and typically returns within 20 to 40 minutes.
The platform is available through a web application for individual researchers and organisations, a REST API for integration into customer workflows, and a Model Context Protocol (MCP) integration. Data handling practices include encrypted storage, SOC 2 and ISO 27001 certification, and a policy of never using uploaded content to train AI models.
