LangInMotion provides a runtime control layer for enterprise AI systems that enforces standard operating procedure (SOP) compliance, policy‑backed claim validation, and safe escalation when evidence is insufficient. By scanning AI outputs for groundedness, SOP adherence, and handoff safety, the platform helps organizations mitigate production risks and maintain governance over language models. Their AI Readiness & Risk Scan service delivers a baseline risk score and actionable insights for deploying trustworthy AI.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprise AI deployments often generate language outputs that conflict with internal standard operating procedures (SOPs), make unsupported claims, or trigger incorrect API calls, leading to policy violations, operational errors, and missed escalation events.
Solution
LangInMotion adds a runtime control layer to AI workflows that validates each language output against the organization’s approved SOP clauses and current workflow state. The platform checks that claims are policy‑backed, that required SOP steps are followed, and that any escalation triggers are respected. When evidence is insufficient or the workflow state disallows a commitment, the system automatically escalates rather than asserting a response. An AI Readiness & Risk Scan can baseline risk, score groundedness, and assess SOP compliance before production rollout. Together, these capabilities help enterprises enforce compliance, reduce erroneous API usage, and ensure safe handoffs in live AI applications.
Target Audience
Primary customers are large enterprises and regulated organizations that deploy generative AI in customer‑facing or internal automation workflows and need to enforce SOP compliance and policy governance.
Features
- Real‑time validation of language outputs against approved SOP clauses and workflow context
- Policy‑backed claim verification to ensure all statements are supported by documented procedures
- Automatic escalation logic that routes uncertain or prohibited responses to human operators
- AI Readiness & Risk Scan that benchmarks groundedness, compliance risk, and handoff safety for existing models
- Configurable validators and release thresholds that can be piloted on specific SOP‑driven workflows
- Integration hooks for inserting the enforcement layer into existing AI pipelines without code rewrites