Retroguard - AI Safety Guardrails API

Developers building AI applications need verifiable, cryptographically secure protection against harmful outputs. Retroguard provides drop-in guardrail integration with outcome-based pricing model. Target users are enterprises and startups deploying AI systems that require security compliance.

AI safety and compliance requirements are accelerating fast following the EU AI Act, SEC guidance on AI disclosures, and enterprise procurement teams adding AI risk questionnaires to vendor reviews — demand for programmatic guardrails is real and growing now. The closest incumbent is Guardrails AI (open-source, with a cloud tier), and LlamaIndex, LangChain, and AWS Bedrock all ship native content filtering, meaning the competitive surface is crowded with free or bundled options that will be the default choice for most developers. Outcome-based pricing sounds differentiated but is genuinely hard to instrument — defining a "harmful output" event in a way that's auditable and billable across diverse enterprise use cases is a product and legal problem that will eat roadmap. The single most likely failure mode is that hyperscalers (OpenAI, Anthropic, Google) continue absorbing safety features directly into their model APIs, commoditizing the entire layer before a standalone vendor can establish switching costs.