Enterprises need to strategically leverage AI as a core accelerant for digital business initiatives.

According to the Gartner 2020 CIO Agenda Survey, “Enterprises are expected to double the number of artificial intelligence (AI) projects in place within the next year, but the reality is that most organizations struggle to scale the AI pilots into enterprise-wide production, which limits the ability to realize AI’s potential business value”.

AI creates opportunity and industrializes business processes by augmenting your workforce, eliminating repetitive and unproductive tasks, reducing the influence of subjectivity, reducing the frequency and impact of mistakes.

Aiming to deliver value swiftly, CEOs and COOs are leading the charge in initiating AI projects. AI skills, experience, and tools need to be on par with the enterprise production requirements and known processes, such as convenient AI development environments, automation of routine tasks, production stability and reliability.

“Although the potential for success is enormous, delivering business impact from AI initiatives takes much longer than anticipated,” says Chirag Dekate, Senior Director Analyst, Gartner. “IT leaders responsible for AI are discovering ‘AI pilot paradox’, where launching pilots is deceptively easy but deploying them into production is notoriously challenging.”

One example of AI use cases that are making tremendous impact in many industries is Natural Language Processing (NLP). Enterprises must shift from tactical to strategic use of natural language solutions to ensure greater portability of language assets and models.

Overcoming common hurdles like managing unstructured data, integrating data silos, redressing data quality and governance lapses, developing a solid foundation with sound data management, and eliminating the ubiquitous spreadsheets in your manual operations are key to industrializing and automating paper-based and other people-dependent business processes.

The Journey:

Haystream specializes in AI Processes and Platforms and enabling operational excellence by defining, building, and deploying solutions to securely and efficiently ingest and consume large volumes of data from structured and unstructured data sources. Our experts can accelerate your AI journey by identifying the most valuable use cases, creating the most direct path to value, and enabling your data assets through Machine Learning on any data source form and format, including Structured Operational Data, Time Series Data, Unstructured Data, Images, Audio, Video, and others, thereby, helping you:

  • Accelerate your business processes.
  • Reduce operational costs by automating manual processes.
  • Reduce the frequency and impact of mistakes in your manual processes.
  • Improve auditability, compliance and regulatory controls.
  • Identify new revenue streams and connect with your clients in new ways.

The Strategy:

Your success is furthered by our custom development, smart use of open-source tools and product and platform partnerships to design and deploy machine learning and advanced analytic solutions that fit your objectives. This includes:

  • Supervised Learning – including classification and regression.
  • Unsupervised Learning – including clustering and dimensionality reduction.
  • Reinforcement Learning – including model-based and model-free algorithms.
  • Deep Learning – including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs).

Haystream specializes in helping Enterprise leaders including C-suite executives understand:

  • How to make AI a core IT competency.
  • How to effectively use AI as part of the Digital Strategy.
  • How to identify, ideate, evaluate, and prioritize AI use cases.
  • How departments and functions within organizations can be made more productive with AI.
  • Responsible application of Enterprise-wide AI.

Artificial Intelligence

AI creates opportunity and industrializes business processes by augmenting your workforce, eliminating repetitive and unproductive tasks, reducing the influence of subjectivity, reducing the frequency and impact of mistakes.