Moderra.ai

Moderra.ai gives AI product teams one place to enforce guardrails, route risk, review edge cases and produce audit-ready evidence across text, image, video and voice. Maddison Lake is chief executive. Six service families are orchestrated through a single API: a guardrails API for real-time policy enforcement on prompts, outputs and multi-turn sessions; human review queueing and disposition workflows; immutable compliance evidence mapping decisions to regulatory requirements including the EU AI Act; continuous website audits watching public surfaces for disclosure gaps and policy drift; agent and quality controls covering groundedness, task adherence, protected material and copyright risk; and adversarial red-team simulation with runtime security analytics.

Its commercial argument is unusual and worth stating precisely, because it is not the argument a moderation vendor normally makes. Moderra leads not with the harm of letting unsafe content through but with the opposite failure: the crude refusal. It calls this the over-refusal tax, and holds that every false block kills a legitimate request, churns a user, spikes a support ticket and quietly collapses trust, at about the same cost as the failure everyone does measure. The alternative it offers is policy enforcement that distinguishes signal from noise: allow what is safe, flag what is grey, route what is hard, refuse what is clearly out of bounds, each with a reason a team and a regulator can read.

Coverage is genuinely multimodal. Text and code: prompt injection, toxicity, PII redaction, jailbreak attempts. Image and vision: deepfake detection, CSAM, gore, likeness controls. Audio and voice: real-time interruption, transcript safety, crisis detection. Video: frame-by-frame analysis, audio-visual alignment, consent registries. The published API response carries an action, a stated reason, a confidence score and a route-to-human flag rather than a bare allow or deny, which is the whole thesis expressed in a JSON object.