Service
Architecture review before implementation
Implementation scope and rollout planning
Clear next-step recommendation
Mitigate legal exposure and ensure operational safety with certified AI systems engineered for industrial compliance.
Deploying uncertified AI in physical environments exposes your company to significant liability. Without adherence to ISO 10218 and ISO/TS 15066 for human-robot collaboration, your systems lack the legally defensible safety frameworks required for industrial insurance and operational permits.
Our engineering delivers certified safety architectures that transform AI from a liability into a documented, compliant asset.
Partner with us to build AI that meets the stringent requirements of Industrial AI Safety and Compliance Engineering, ensuring your robotics and autonomous systems are both powerful and legally sound. Explore our broader capabilities in Physical AI and Industrial Robotics Integration or learn about securing AI with Confidential Computing for AI Workloads.
Our engineering approach translates technical safety measures into measurable business value, ensuring your AI-powered industrial systems are not only compliant but also a source of operational efficiency and competitive advantage.
Achieve ISO 10218 and ISO/TS 15066 compliance for human-robot collaboration in 4-6 weeks with our pre-validated safety frameworks, reducing your time-to-market for new robotic deployments by over 60%.
Implement real-time human presence detection and predictive collision avoidance systems that operate with 99.99% uptime, preventing costly production halts and protecting your workforce without interrupting operations.
Demonstrate certified safety engineering and auditable compliance logs to insurers, leading to premium reductions of 15-25% and shielding your enterprise from costly litigation related to autonomous system incidents.
Build operator confidence in AI-driven systems with transparent, explainable safety protocols and intuitive spatial computing interfaces, leading to faster workforce adoption and a 40%+ increase in human-robot collaboration efficiency.
Proactively adapt to evolving global standards like the EU AI Act and upcoming OSHA guidelines with a modular safety architecture, avoiding expensive last-minute re-engineering and ensuring continuous operation.
Replace subjective safety assessments with data-driven risk scoring powered by real-time sensor fusion AI, providing C-suite with clear metrics on hazard reduction and enabling informed capital allocation for safety investments.
Our safety engineering services directly implement technical controls to meet and exceed global industrial standards. This table maps core features to the specific regulatory requirements they address.
| Safety & Compliance Feature | ISO 10218-1/2 (Robots) | ISO/TS 15066 (HRC) | IEC 61508 (Functional Safety) | Custom Risk Assessment |
|---|---|---|---|---|
Real-time Human Presence Detection | ||||
Predictive Collision Avoidance Algorithms | ||||
Safety-Rated Monitored Stop (SMS) | ||||
Speed & Separation Monitoring (SSM) | ||||
Power & Force Limiting (PFL) Integration | ||||
Audit Trail & Event Logging (Data Lineage) | ||||
Safety Integrity Level (SIL) 2/3 Certification | Optional | |||
Custom Risk Assessment & Mitigation Plan | ||||
Ongoing Compliance Monitoring & Reporting | Basic | Standard | Advanced | Continuous |
Typical Implementation Scope | Single Robot Cell | Collaborative Workcell | Full Production Line | Enterprise-Wide System |
We de-risk your AI safety integration with a structured, four-phase process that prioritizes compliance and operational reliability from day one, ensuring your systems meet ISO 10218 and ISO/TS 15066 standards without disrupting production.
We conduct a comprehensive gap analysis of your current robotics and AI systems against target safety standards (ISO 10218, ISO/TS 15066). This includes a review of operational procedures, physical safeguards, and software logic to establish a baseline compliance roadmap.
We develop and validate core safety functions—like real-time human presence detection and predictive collision avoidance—in a controlled simulation environment. This phase uses tools like NVIDIA Isaac Sim to test edge cases and failure modes before any physical deployment.
We deploy and integrate the validated AI safety modules into a single, non-critical production line or robot cell. Our engineers monitor system performance in real-world conditions, collecting data to fine-tune models and verify compliance under actual operational variance.
We orchestrate the enterprise-wide rollout of the certified safety systems, including installation of necessary edge compute hardware and integration with your MES/SCADA systems. We establish continuous monitoring dashboards and documentation for ongoing compliance audits.
Enabling Efficiency, Speed & Accuracy
We build AI systems for teams that need search across company data, workflow automation across tools, or AI features inside products and internal software.
Before integrating AI into your physical operations, technical leaders need clear answers on process, security, and compliance. Here are the most common questions we address for CTOs and engineering leads.
Our engineering process is built around a compliance-by-design approach. We start with a formal risk assessment (HAZOP/FMEA) to map all human-robot interaction points. Our safety systems are then architected as deterministic, redundant layers—combining certified safety-rated hardware (e.g., Pilz, Sick) with AI-driven predictive software for collision avoidance and human presence detection. We deliver a compliance dossier with all required documentation, test reports, and validation records for your notified body audit. This structured methodology has been proven across 50+ industrial deployments.
About the author
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
How We Work
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
The first call is a practical review of your use case and the right next step.
