AI-powered incident response and threat detection for physical security
Robotic Assistance Devices builds autonomous security systems—part hardware (mobile and stationary robots), part agentic AI—to automate incident detection, verification, and response. The tech stack (PyTorch, TensorFlow, LangChain, LangGraph) paired with active projects around agentic AI design and retrieval-augmented generation signals heavy investment in AI reasoning layers. Adoption of RAG and RPA, plus recurring pain points around sales automation and reporting, reveals a sales ops scaling challenge: international operations generating noisy metrics that currently require manual intervention.
Robotic Assistance Devices operates in physical security, deploying intelligent robotic systems and AI software to automate threat response workflows. The product combines stationary and mobile hardware with agentic AI (SARA—Speaking Autonomous Responsive Agent) to detect, verify, and escalate security incidents without human intervention at each step. Customers are mid-market and enterprise security operators seeking force multiplication. The company is based in Ferndale, Michigan and operates a distributed hiring footprint (active recruitment in Sri Lanka). A public company with 51–200 employees, RAD is engineering and data-heavy, with active projects spanning hardware platform optimization, sales dashboard automation, and UX design for web and mobile surfaces.
RAD uses Salesforce and HubSpot for CRM, PyTorch and TensorFlow for machine learning, LangChain and LangGraph for agentic AI frameworks, and Python for backend development. Design tools include Figma, Sketch, and Adobe XD.
SARA is RAD's Speaking Autonomous Responsive Agent—an agentic AI system that automates incident verification, escalation, and response in real time. It won SIA's 2025 Judges' Choice Award for security innovation.
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