AI Engineering
Engineering Intelligence into Instruments
AI Engineering at Tismo is focused on systematically enhancing instruments and connected systems with built‑in intelligence. Our work goes beyond proof‑of‑concept models to deliver production‑ready capabilities that improve functionality, analytical depth, reliability, and long‑term product value.
We collaborate with OEM engineering teams to integrate AI as part of the core product architecture, across software, firmware, electronics, cloud, and edge, ensuring that intelligence is predictable, testable, and maintainable over the entire lifecycle of the instrument.
Building Smarter Instrument
Modern instruments are expected to do more than control or generate measurements.
We help extend product capability by embedding intelligence that improves analytical depth, provide insights, usability, and differentiation, while preserving regulatory and engineering discipline.
Typical enhancements include:
- Adaptive user workflows based on context and operating conditions
- Automated quality checks and confidence indicators
- Intelligent parameter selection and self-tuning behavior
- Software driven feature expansion
These capabilities result in equipment that are easier to operate, more informative, and better aligned with real‑world usage scenarios.
Advanced Analysis of Images, Spectra, Waveforms
Many analytical, medical, and industrial instruments generate high‑value data that can be further leveraged through advanced analysis
Tismo applies ML and data‑driven techniques to extract deeper insight from complex data types, while grounding models in domain knowledge and signal behavior.
Our analysis capabilities include:
- Image analysis for detection, segmentation, and classification
- Spectral data interpretation using multivariate and statistical techniques
- Waveform and time-series analysis for pattern recognition and anomaly detection
- Feature extraction and dimensionality reduction for improved repeatability
Where appropriate, we design human‑in‑the‑loop systems to support assisted interpretation and controlled decision‑making.
Predictive Maintenance with ML
AI enables instruments and equipment to continuously assess their own health and performance
We design diagnostic and predictive maintenance solutions that combine sensor data, logs, and operational history to identify issues early and accurately.
Key capabilities include:
- Detection of drift, degradation, and abnormal operating behavior
- Classification of failure modes and root-cause indicators
- Remaining useful life (RUL) estimation
- Maintenance recommendations based on observed patterns
These solutions help reduce unplanned downtime, improve service efficiency, and extend the operational life of instruments deployed in the field.
AI-based Support, Automation & Edge
Beyond the instrument itself, AI can significantly improve service, support, and operational workflows.
Tismo engineers AI‑driven systems that assist users, service teams, and field engineers while integrating seamlessly with existing enterprise and IoT platforms.
Applications include:
- AI-guided troubleshooting and diagnostic assistance for service teams
- Customer support automation using product knowledge, logs, and historical cases
- Workflow automation across measurement, analysis, and reporting processes
- Embedded and edge AI agents for low-latency, offline-capable intelligence
These capabilities enable scalable support models and more responsive field operations, while maintaining system security and reliability.
How We Engineer AI
Our AI Engineering approach is grounded in established engineering principles and product realities.
- AI is designed as part of the system architecture, not as an after-thought add‑on
- Models are informed by domain knowledge, process and measurement behavior
- Validation, traceability, and explainability are built into the development process
- Solutions are engineered for deployment, monitoring, and long‑term evolution
Regulatory Compliance for Medical
For medical devices, analytical instruments, and life‑sciences products, AI must be engineered within a rigorous regulatory and quality framework
Tismo designs AI systems with compliance, validation, and traceability as first‑class requirements.
Our approach considers:
- Alignment with quality management systems such as ISO 13485 and ISO 9001
- Design controls, documentation, and traceability across data, models, and software
- Verification and validation strategies appropriate for risk class and intended use
- Human‑in‑the‑loop designs where AI supports, rather than replaces, expert decisions
- Clear separation between analytical assistance and clinical decision‑making where required
We work closely with client regulatory and quality teams to ensure AI‑enabled features can be confidently assessed, validated, and maintained throughout the product lifecycle.
Services
- oAI feasibility studies and use-case definition for instruments and systems
- oData strategy, acquisition, and pipeline design n-Model development for analysis, diagnostics, and predictive applications
- oEdge and cloud AI deployment architecture
- oIntegration of AI with existing software, firmware, and electronics
- oVerification, validation, and performance benchmarking
- oLifecycle management, monitoring, and continuous improvement
Technologies
- oPython, C/C++, C#, scientific computing and numerical analysis libraries
- oClassic ML, statistical modeling, deep learning frameworks, time-series and anomaly detection toolkits
- oLibraries for spectral analysis, waveform processing, filtering, and feature extraction
- oImage processing and vision frameworks for detection, segmentation, and classification
- oOptimized inference runtimes for ARM-based and embedded platforms, model compression and optimization tools
- oSecure cloud services for model deployment, monitoring, data pipelines, and analytics dashboards
- oREST APIs, messaging systems, IoT protocols, and secure data ingestion pipelines
- oTools for model performance tracking, drift detection, logging, and auditability
Case Studies
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