Evalueserve: supporting customers with AI adoption

Rigvinath Chevala, CTO at Evalueserve discusses his experiences in tech, the company’s AI platforms, the benefits they bring and its plans for the future

Tell me about Evalueserve, your roles and your responsibilities.

Evalueserve is a leading analytics partner that helps clients increase the effectiveness and efficiency of their core processes by applying a unique mind+machine™ methodology. More than 25% of the Fortune 1000 trust Evalueserve teams in 45 countries to resolve the most complex business challenges with our AI products & solutions that enable successful business outcomes. Our 4,500 subject matter experts help companies achieve mission-critical initiatives with their data by adapting the latest domain-specific AI technologies to solve business problems.

My role as a CTO is to ensure our business lines have a cohesive software product strategy and execute our customer-centric support efforts. Our products seek to elevate our impact through the use of software, domain-specific AI, and domain expertise that we have built over the last two decades. I help our product managers and engineering teams create a vision, execute product roadmaps, architect the right solutions, deliver superior customer experience, and take pride in making a meaningful impact on our end users.

How have your experiences with tech companies such as Trimble, MRI software and Brandmuscle shaped the way your approach your CTO role at Evalueserve? 

I started my career at a software product startup and have continued in that space for my entire career. Building products requires a unique mindset, one that ensures reusability and maintainability at the core of it. 

In traditional software development, you build to spec. based on each customer and stakeholder's requirements. Once built, you are off to another project. However, products are built for an entire market or a sub-market with tons of customers with similar pain points. And the team that builds it is also required to maintain it for a longer-term with new bells and whistles added along the way. 

That is truly what helps me in my current role at Evalueserve. My experiences help us ensure we have a consistent paradigm to create wonderful products irrespective of the industry or domain. 

Rigvinath Chevala

How does Evalueserve support clients with AI? Talk me through your different platforms. 

We apply AI in a broad range of use cases across different industry segments. If I condensed all of that into a simplified term, it's essentially AI for Research and Analytics (AIRA - an internal code name I coined). In short, we support our products with AI-enabled features in two major areas - NLP and Computer Vision

We do this by creating reusable AI models that are trained first on generic data and then fine-tuned using domain experts to deploy industry-specific AI models. For example, we have sentiment analysis for news articles that are fine-tuned for specific domains such as Automotive, Oil and Gas, Pharma or even specific languages within each. 

We deploy all of these models on a scalable architecture like Kubernetes behind a secure API gateway so our products can leverage them in different steps/workflows of the application. We have several products -- Insightsfirst, Spreadsmart, MRMRaptor, Researchstream to name a few -- that solve specific market pain points. Our customers respect our culture of innovation and see us as the best of the breed.

What benefits do customers gain from this? 

In a nutshell, customers either receive decision-ready insights from AI and data and/or benefit from our tools in terms of productivity and efficiency in their everyday processes. Ultimately, what we are doing is helping them take diverse data sources and create actionable insights from them. 

Obviously, there are many more nuances and hurdles to creating these insights so that they are useful. I think some of them that directly benefit our customers include creating a culture that embraces AI with strong data governance and continual review and improvement. There is the ownership of the algorithms which as proprietary tools give them their unique domain-specific applicability that you cannot get from a general platform. 

Finally, there is the delivery of the analytics- how decision-makers need them and when they want them. This last step seems obvious, but it’s not. You really have to understand how decisions are made within the culture and then fuel the decision-makers with the analytics in a manner that makes them most useful.

What's next for Evalueserve?  

With a substantial customer base already in place, we feel that we are poised to be capturing patterns across customers and across industries to create cutting-edge products and innovate rapidly.  Our approach of making our AI models domain sensitive really draws out the power of expertise that was built over the last two decades (which very few companies can tout).

It’s an exciting time for us as we continue moving into the modern era of analytics. We’re so driven by all the possibilities that industry-specific expertise combined with AI technologies provide, that I think the future is going to be pretty amazing. 


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