LTTS AiKno® Cognitive Metadata Extraction

LTTS AiKno® Cognitive Metadata Extraction

As AI adoption moves beyond R&D, early adopters are poised to define the frontiers of what’s next. However, the road to Industrial Artificial Intelligence is riddled with challenges. Unlocking the secrets hidden in industrial data requires high levels of precision and accuracy. Strengthened by the cumulative experience of LTTS experts, AiKno® takes precision and accuracy to the next level. From optimizing production, distribution, and field-services to improving efficiency across all industrial stages, AiKno® opens the floodgates of opportunities for your business. Manual digitization of legacy data is both time-consuming and cost-intensive. The AiKno® Metadata extraction solution comprises three steps: First, proprietary advanced Image Processing algorithms process images despite any noise from scanning artifacts or chemical reactions. Next, the text is extracted using an OCR engine. The output is passed to the third step, an NLP engine to extract the meta data.

*Please note that member solutions are often customizable to meet the needs of individual enterprise end users.



  • Data Digitization
    Automates Data digitization
  • Autocorrection through Self Learning
    Drives rules based on human feedback eliminating re-engineering
  • Detects special icons and symbols
    Detects special icons and symbols used in engineering documents
  • Multiple Algorithms
    NLP engine extracts data using multiple algorithms such as Picklist, Regex, Table, Rules-Based, Key-Value pairs etc
  • Optimized on Intel® Xeon® Processors
    Powerful Intel® Xeon® Processors helps accelerate the compute intensive cognitive metadata extraction steps



WorldwideDefense and SpaceEnergy and UtilitiesData Preparations and ManagementImage/Object Detection/Recognition/ClassificationOtherCSP - Amazon Web ServicesCSP - Microsoft AzureIntel® Xeon® Scalable ProcessorIntel® Core™ ProcessorIntel® Distribution of OpenVINO™ Toolkit powered by oneAPIIntel® Distribution for Python*Intel® Optimization for TensorFlow*Models can be trained - requires labeled dataWindowsLinux ProprietaryDeep LearningMachine LearningOther