AI Expertise.
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From AI Curiosity to Industrial AI Clarity
Before implementing AI, manufacturers and industrial operators must know where it delivers the most value. Maya HTT’s Industrial AI Use Case Business Readiness Assessment & Roadmap Creation helps your team identify the highest-ROI opportunities – grounded in your process physics, data availability, and operational priorities.
We evaluate technical feasibility, data quality, and business impact to create a physics-informed roadmap that turns AI ambition into tangible industrial AI outcomes.
From Signals to Predictive Insight. Physics + Data = Smarter Models!
Raw sensor data becomes powerful when guided by physics. EPIQ-M’s AI solutions model layers which combines industrial telemetry with first-principles equations aware to produce accurate, explainable models (or at least interpretable models) that stay valid even under changing conditions.
Whether predicting thermal efficiency, vibration anomalies, or material fatigue, our hybrid models translate data streams into real-world, physics-grounded intelligence.
Connect Your Data. Contextualize Your Operations. Derive Insights where Industrial Data Meets Physical Insights.
Data is only powerful when it’s connected and understood in its physical and manufacturing process or industrial operations context. Maya HTT integrates telemetry, SCADA, historian, MES and PLM systems data into a unified, physics-aware data foundation.
We build semantic data layers that tie every sensor signal to its physical meaning – ensuring that your AI models interpret not just patterns, but the real behavior of your assets and processes. This is the difference between finding correlations versus finding causation!
Acoustic AI Tuned to the Physics and Sounds of Your Equipment
Every machine has a sound signature. Maya HTT’s industrial AI-based solution to real-time machine listening converts acoustic and/or vibration data into actionable maintenance insights.
By combining spectral AI analysis with mechanical physics models, our system distinguishes normal wear and normal background sounds from true acoustic anomalies.
The result: early detection of bearing, pump, and motor issues – before they become costly downtime events.
AI Vision That Understands Materials and Mechanics
Maya HTT’s approach to AI-based machine vision fuses deep learning with foundation model built from engineering-based synthetic image understanding to detect surface defects, assembly errors, or material inconsistencies.
Unlike generic computer vision, our models incorporate physical context – lighting, texture, reflection, and geometry – for more robust inspection in harsh industrial environments. The result: fewer false positives, higher yield, and faster root-cause analysis.
On Demand Industrial Knowledge from a chat interface
Maya HTT’s M-Bot transforms complex operational knowledge into accessible, conversational intelligence. Powered by domain-trained GenAI, it understands plant vocabulary, physics-based constraints, and historical data.
Engineers can ask “What caused yesterday’s efficiency drop?” or “When is the next maintenance window optimal?” – and get grounded, explainable answers, not guesses.
Industrial-Grade AI That Improves Over Time
Industrial AI in manufacturing or industrial operations isn’t a one-off model – it’s a living system. Maya HTT’s industrial ML-Ops framework manages deployment, versioning, retraining, and validation with the same rigor as engineering or manufacturing simulation.
Each model’s lifecycle is tracked and verified through physics-based benchmarks or curated and regularly updated past telemetry test datasets, ensuring consistent performance as conditions evolve. This closes the loop between industrial AI development and the real world at scale and standing the test of time.