Accelerate Your AI Journey with Insight

Artificial Intelligence can lead to exciting and vital insights for businesses. Capturing the market with a valuation of $39.9 billion in 2019 alone, AI initiatives are already changing the game for organizations today. With a growth of 270% in 4 years, more than half of the businesses have reported a boost in productivity and reported cost savings after having implemented AI.  

At Wavelabs, we have the vision to foresee these rapid evolutions in technology, agility to proactively invest in new competencies and customer centricity to help accelerate the adoption of the same. Wavelabs Insight was launched with the idea of understanding the true potential of AI and what it can do for enterprises at a large scale. 

What is Wavelabs Insight? 

Wavelabs Insight is a systematic approach of identifying business needs through use case discovery and building innovative AI capabilities for deployment and scale. It brings together the know-how of diverse technologies, tools and platforms to make it easy to build and train AI models. With extensive expertise gained from numerous customer implementation and successes, we can help explore the untapped possibilities of data, analytics, and AI for various industries.

Wavelabs Insight leverages open-source software modules and custom-built components to accelerate the time-to-deployment of AI initiatives. The workflow is implementation and industry-agnostic, and we augment support to all new algorithms and AI frameworks.

Why Wavelabs Insight? 

Advancements in technologies appear almost every single day. With many of these technologies, there are no tried and tested business models or “best practices” in place. In today’s world, businesses need an approach where they see immediate benefit and use that solution to improve productivity. 

With innovation at our core, we build competencies to gain advantage by learning and experimenting with different workflows to find what works best.  

With Wavelabs Insight framework, we can analyze massive amounts of data (audio, image, video, text and graphical data) with applications in machine translation, understanding objects, mapping, ranking user preferences, ad placement, etc. Machine learning techniques and models can be used to identify previously undetected patterns and anomalies in data and streamline repetitive tasks to alleviate costs.

Conclusion:

Wavelabs Insight is a complete framework in data processing, model training, and serving. It is capable of bringing profound changes to various industries including finance, health care, retail, and manufacturing when it enters the stage of implementation and scale. 

With an internal reference architecture, it helps you realize the true potential of your AI initiatives and accelerate AI application deployment. 

While it may look like a huge investment of time and resources to build and deploy a platform like this, the truth is that it can be built incrementally. It is a holistic view of the end-to-end pipeline that is key to successful deployment and scaling of enterprise-wide AI systems.

The Insight framework from Wavelabs is designed to help accelerate and simplify this journey.