Liria develops a safety monitoring platform designed to prevent accidents in human-machine interactions across various industries. The platform actively detects and mitigates safety risks before they escalate, enhancing transparency and reliability in collaborative environments. This focus on operational safety enables partners to ensure compliance, reduce risk exposure, and improve overall efficiency.
Funding
Funding not disclosed
Founders
Product
Problem
Human‑machine interactions in sectors such as automotive, manufacturing, and smart infrastructure often lack continuous safety oversight, leading to accidents, equipment damage, and regulatory non‑compliance. Existing safety checks are typically manual, episodic, and dependent on specialized personnel, which limits scalability and real‑time risk mitigation. Consequently, organizations face higher operational downtime and liability exposure.
Solution
Liria offers a cloud‑native safety monitoring platform that continuously observes human‑machine interfaces and automatically identifies emerging hazards before they materialize. The system ingests data from on‑board sensors, vision systems, and IoT devices, applying edge‑level analytics to generate instant risk scores. Detected issues trigger automated mitigation actions—such as adaptive control adjustments, operator alerts, or shutdown sequences—reducing the likelihood of accidents. All events and compliance metrics are logged in a secure, centralized repository accessible through a web dashboard and API, enabling auditors and operators to verify safety standards in real time. By standardizing safety inspections across diverse equipment, Liria helps partners maintain regulatory compliance, lower insurance costs, and improve overall operational efficiency.
Target Audience
Primary customers are OEMs, industrial manufacturers, fleet operators, and safety‑critical service providers that require continuous monitoring of human‑machine interactions to meet safety regulations and reduce operational risk.
Features
- Multi‑sensor fusion engine that aggregates data from cameras, LiDAR, force sensors, and PLCs for holistic risk assessment
- Edge‑computing analytics module with pre‑trained machine‑learning models that deliver sub‑second hazard detection
- Automated mitigation workflows that can adjust machine parameters, issue audible/visual alerts, or initiate safe‑stop procedures
- Centralized compliance console with configurable dashboards, audit trails, and exportable reports (CSV, PDF, API)
- RESTful and OPC‑UA APIs for seamless integration with existing MES, SCADA, and EHR systems
- Role‑based access control and end‑to‑end encryption meeting ISO 27001 and GDPR requirements
- Scalable SaaS architecture supporting thousands of concurrent devices across multiple sites
- Domain‑specific modules, starting with automotive vehicle safety and damage appraisal, with extensible plug‑ins for other industrial verticals