MACHINE LEARNING


Enrich information assets with metadata for process automation

Harmonize all information sources for key business insights

Extract facts, entities and relationships for better analytics

Machine learning is a branch of cognitive computing that employs algorithms and mathematical models to discover, recognize, and classify patterns in data. Computers can be programmed to "learn" these patterns and subsequently used to make predictions or automated decisions.

Some selected examples include:

  • Computer vision:  identification and classification of images and videos
  • Predictive maintenance:  alerting to when a machine may have a fault or failure
  • Anomaly detection for sensors and event recorders
  • Fraud detection
  • Speech recognition (Siri & “OK Google”)
  • Document classification
  • Customer analytics: attrition prediction; targeted marketing; segmentation
  • Recommender systems (“you might be interested in”)
  • Cybersecurity: hacker intrusion and malware detection

ANALYTICS STRATEGY

We can guide you to the Analytical Competitor stage through:

  • Assessments and audits
  • Predictive maintenance:  alerting to when a machine may have a fault or failure
  • Planning and roadmaps
  • Proofs-of-concept
  • Capabilities development and mentoring.

OUR ENGAGEMENT MODEL

Our collaborative engagement model leaves your team with the "know-how" to do analytics. We consider an engagement to be unsuccessful if we cannot establish you as the owner-operator of the solution.

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