Learn more about PV Intelligent Automation and AI

PV Intelligent Automation and AI

  • Evaluation of the client’s existing PV environment with respect to intelligent automation, knowledge processes, data management practices and technical capacities.
  • Tailored strategy and roadmap for more automated and AI-driven/-assisted PV processes including data acquisition (monitoring, intake), case processing or signal detection.
  • Transition by initializing and driving relevant Proofs of Concepts, implementation projects and corporate change initiatives
  • Covered intelligent automation improvements might include:
    • Monitoring of relevant data sources - literature, social media, mail inboxes etc.
    • Exploratory Data Analysis, data/text preparation and pre-processing
    • Entity recognition and pre-coding (MedDRA PTs, products), AERs and duplicate detection/classification, seriousness suggestion, case summarization, results evaluation
    • Simulations, visualizations, modeling temporal relations and causality assessment
    • Augmented AI patterns (AI vs. human-assisted) and related explainability and validation compliance
    • Tuning models (hyper-parameters) and architectures for regression, classification, deep learning (NLP) and others
    • Productionalizing PV IT operations towards scalable architectures, faster turnaround (CI/CD), continuous improvements and Machine Learning PV IT operations (MLOps covering train/test/validation/production pipelines, etc.)
    • Active awareness of relevant community activities - open-source models and libraries, no-code SaaS tools, regulatory AI PV guidelines and actions, ethical and green AI, and more.

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