Greenlight

The problem: before a financial ad can run, it has to clear several regulators at once. In India that means RBI, SEBI, and ASCI, three bodies with overlapping requirements. Today this happens in email threads, PDFs, and the heads of a few reviewers. It is slow, inconsistent, and when a regulator later asks who approved a claim and on what basis, there is rarely a clean answer. GreenLight turns that review into a coordinated agent workflow, and the workflow itself becomes the record. You drop an ad creative into a Band room. A Case Desk agent opens a case and picks the rulebooks. A Claims Analyst extracts every claim. When the creative touches investments, the Case Desk recruits a SEBI specialist into the room on the spot, only when needed. A Compliance Reviewer rules the advertising and lending standards in parallel. The Case Desk consolidates both into one verdict, and a human signs off before anything clears. Every step is the audit trail, captured as it happens. The system runs two AI stacks on purpose. The coordinating agents run on the Claude Agent SDK inside Band. The SEBI ruling, the highest-stakes reasoning in the pipeline, is produced by Anthropic Opus 4.8 served through the AI/ML API and invoked through a bridge. The AI/ML call runs at runtime on every case and its findings are tagged separately on the dashboard. It is real, not mocked. The dashboard renders each case as a downloadable clearance record: the creative, the agents and their frameworks, the coordination timeline with the live recruit marked, every finding with its rule ID, and the human sign-off. Live on Railway, backed by Postgres. The Indian rules are a demonstration, not a limit. The engine is regulator-agnostic: load FCA, SEC, or MAS rules and the same desk clears them. The room transcript becomes a system of record, so regulated industries get an audit trail for free, because the coordination is the trail.