Welcome to Vilimbu

AI/ML

Driving ROI Through AI

To be successful at AI and drive high performance, executives should consider five best practices uncovered by ESI Thought Lab

  1. Begin with pilots, but then scale AI across the enterprise. Companies starting out should work closely with business teams to identify use cases
    and demonstrate their value through pilots. 
  2. Lay a firm foundation. The most important lesson is having a proper IT and data management system in place and leveraging the ecosystem of AI partners and suppliers. Defining the business case is vital for driving ROI: 77% of firms generating the highest returns from AI do this well.
  3. Get your data right. Nine out of ten AI leaders are advanced in data management. Ensuring your data is in good shape is not enough; to drive higher AI performance firms should bring in richer sets of data, such as psychographic, geospatial, and real-time data. At the same time, companies should integrate fast growing data formats into their AI applications, such as high-dimensional, video, audio, and image.
  4. Solve the human side of the equation. AI is as much about people as it is about technology. Of the firms in the study generating large returns, 83% have been successful at acquiring and developing the right people. 
  5. Adopt a culture of collaboration and learning. About 85% of firms that generate large AI returns work to ensure close collaboration between AI
    experts and business teams. Nearly nine out of ten AI leaders excel at providing non-data scientists with the skills and tools to use AI on their own. They also decentralize AI authority to help ensure that AI expertise and responsibility are well distributed across their organizations.
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AI/ML Solutions We Offer

Many of the verticals are being revolutionized by AI and IoT. To address the wider adoption, Vilimbu offers a variety of data insights and actionable intelligence that examine and split the uptake of these technologies across key verticals

  • Industry

    Healthcare, Automotive, Retail, Manufacturing, Finance

  • Natural Language Processing

    Syntax analysis, Entity analysis, Custom entity extraction, Sentiment analysis, Emotion analysis, Custom sentiment analysis, Text classification, Toxicity classification, Abusive Analysis, Custom content classification, Large dataset support, Automated Survey Processing

  • Image Recognition / Classification
    • Image labeling & classification, object detection such as face, landmark, optical character recognition (OCR) and tagging of explicit content.
    • Machine learning models to classify your images pertaining  to your own defined labels. Train models from your labeled images and improvise the performance.
    • Assist with a human labeling service for datasets with unlabeled images.
  • Video Recognition / Classification

    Machine learning models to classify frames and segments in your videos pertaining  to your own defined labels

  • Object Tracking

    Machine learning models to detect and track multiple objects in shots and segments. You can use these models to track objects in your videos according to your own pre-defined, custom labels.

  • Product Search

    Aisle-by-Aisle / Shelf rack maintenance, Inventory  audit