Funding
Funding not disclosed
Founders
Product
Problem
Manufacturers often rely on static, heuristic‑based control strategies that cannot adapt to changing process dynamics, leading to variability, scrap, downtime, and underutilized equipment capacity.
Solution
Synaptix offers an autonomous control platform that continuously models and predicts industrial process behavior using AI‑driven adaptive control. The system updates its internal model in real time, detects precursor disturbances before alarms trigger, and automatically adjusts control parameters to maintain optimal operating conditions. By embedding constraint‑aware optimization into existing control infrastructure, the platform reduces variability, prevents unplanned shutdowns, and maximizes throughput without requiring extensive operator intervention. The result is higher overall equipment effectiveness, lower scrap rates, and increased production capacity.
Target Audience
Primary customers are manufacturers of discrete and process industries seeking to improve equipment utilization, including plant engineers, operations managers, and automation teams responsible for high‑value production lines.
Features
- AI‑based process modeling that learns and updates in real time to reflect current plant dynamics
- Adaptive control algorithms that replace static PID tuning with predictive, constraint‑aware adjustments
- Early‑warning detection of instability and precursor events to prevent downtime
- Seamless integration with legacy PLCs and multi‑vendor control systems
- Automated setpoint optimization that continuously maximizes throughput while respecting safety limits
- Dashboard that provides operators with predictive guidance and reduced manual intervention