PIKAI
PIKAI provides a physics-verified AI platform for manufacturing plants that connects to existing PLCs and SCADA systems to deliver predictive maintenance and operational recommendations. The system automatically identifies PLC tags, runs every recommendation through a machine physics model, and can operate in an autopilot control mode while running on the plant's own Linux server.
- Manufacturing / Industry 4.0
- Industrial Automation
- Artificial Intelligence
- Internet of Things
- AI Agents
- Software Only
- Data & Analytics
Funding
Founders
Founder details are not available yet.
Product
Problem
Korean small and mid-sized manufacturers and major infrastructure operators operate reactively, fixing equipment and systems only after they fail. This approach generates massive unplanned downtime costs—estimated at KRW 47 trillion—while 42% of SMEs cite financial burden as the primary barrier to adopting enterprise-grade predictive tools from incumbents like Siemens or PTC, which require $1M+ budgets and 12+ month implementations.
Solution
PIKAI delivers a Predictive Intelligence System that unifies four technology layers—Edge AI, Digital Twin, Physical AI, and Agentic AI—into a single operating intelligence platform. The system performs on-device inference with sub-10ms response times, creates real-time virtual replicas for scenario simulation, applies computer vision and spatial intelligence to physical environments, and enables autonomous decision-making without human bottlenecks. PIKAI connects to PLCs over OPC UA, S7, or Modbus, automatically identifies what each tag means from live behavior, and checks every recommendation against a physics model of the machine before an operator sees it. The platform runs on the plant's own Linux server, so no data leaves the site, and it can operate in an autopilot control mode that continuously tunes setpoints within operator-defined limits.
Target Audience
Primary customers are Korean SME manufacturers and infrastructure operators, including airports and facility service providers, who need affordable predictive maintenance capabilities to reduce unplanned downtime.
Features
- Edge AI layer with on-device inference and sub-10ms response latency for real-time decision-making
- Digital Twin technology providing real-time virtual replicas and scenario simulation capabilities
- Physical AI combining computer vision and spatial intelligence for environmental understanding
- Agentic AI enabling autonomous decisions with zero human bottlenecks in operational workflows
- Automatic PLC tag identification from live behavior, eliminating manual tag mapping and scaling
- Physics-verified recommendations that hold back advice when readings disagree with the machine model
- Autopilot control mode that continuously optimizes setpoints within operator-defined limits
- Plant chat interface answering questions in plain language
- On-premise deployment on the plant's own Linux server with no data leaving the site