AI Model Implementation

AI Model Implementation

AI Model Implementation

AI applies to every industry and company these days. Planning and scheming about AI is one thing; building working AI models is much more challenging. Many companies don’t have the skills necessary to build their own, effective AI models.

This (typically) multi-week engagement defines and builds a custom AI model specifically to address your business needs. Models can be built using no-code/low-code tools or directly in Python or Jupyter. Costs can be minimized by using open source packages like Tensorflow, PyTorch, Spark, scikit-learn, MLflow and others (if desired). The final result is a high-quality, working AI Model to solve your specific business problem.

While each project is unique, the high-level process is generally:

  • Discuss project requirements and aspirations with stakeholders to understand the business value, business goal and relevant business context.
  • Provision data.
  • Exploratory Data Analysis (EDA) to find important patterns.
  • Construct and train the AI model.
  • Review results with stakeholders.
  • Refine and iterate on requirements and training (as needed).
  • Deliver all source code, datasets, documentation and executables.
  • Work with client's team to get them up to speed so they can continue the model's evolution (if needed).
  • Deploy to production.

We have worked in a wide variety of industries, implementing a wide variety of AI models:

  • Keeping elders safe in their homes by converting low-level sensor signals to high-level human behaviors in Spark
  • Build AI models against large knowledge graphs for genetics and eldercare.
  • Match and rank resumes to job descriptions.
  • Educate Intellectual Patent attorneys about AI.
  • Analyze football videos.
  • Predict urban traffic in a European city.
  • Predict metrics in financial markets.
  • Detect anomalies in electrical power equipment using edge computing.
  • Use Generative AI for news synthesis.
  • Predict patient behavioral health risk.
  • Characterize wireless signals.

Dr. Scott Gerard, a certified Distinguished Data Scientist with decades of deep expertise in the IT industry, personally runs each engagement. Engagements are completely or mostly remote. Contact us at Info@KnowledgeReactor.aito discuss your needs.

Mention Discount Code "AI4" for AI4 attendees to get for 20% off for first 3 months for contracts signed in August.

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