Tredence's Journey in Empowering Healthcare with AI

Shub Bhowmick is the CEO and Co-Founder of Tredence, a data science and AI engineering company focused on solving the last mile problem in analytics. 

“I embarked on this journey in 2013 to bridge the gap between insight creation and value realisation,” he says. 

Tredence is now 2,000-plus employees strong and serves 30+ Fortune 500 companies globally.

Bhowmick’s journey began with a pivotal moment in 2002, while writing essays for business school, where the idea of entrepreneurship took root. After completing his MBA from Northwestern University’s Kellogg School of Management, Bhowmick ventured into the technology landscape. Having held senior executive positions at Diamond Consultants (now PwC), Mu Sigma, Liberty Advisor Group and Infosys, his passion for empowering decision-makers led to the founding of Tredence.

“The early 2000s presented an exciting time to delve into technology, particularly in utilising data and analytics meaningfully. Envisioning a startup that leverages global STEM talent, I pursued an MBA at Northwestern University’s Kellogg School of Management,” said Bhowmick. 

Inspired by Silicon Valley's entrepreneurial ethos, Tredence was founded in 2013 with a clear mission: to empower enterprise decision-makers with actionable insights. Bhowmick was fortunate to meet his fellow Co-Founders, Sumit and Shashank, who shared the same enthusiasm that he did for empowering enterprise decision-makers with actionable insights.

“It became evident that Fortune 500 companies needed partners capable of solving vertical-specific business challenges and delivering high-quality data analytics services at scale,” says Bhowmick. “Meeting Sumit and Shashank, we launched Tredence in 2013, working from a three-bedroom flat in Bangalore. Ditching conventional analytics methodologies, we embraced a highly focused, solutions-driven approach, selling our last-mile vision to some of the world’s largest retailers, CPG firms and manufacturers.”

HealthEM is a dedicated healthcare AI Subsidiary of Tredence, which taps into the vast potential of the value-based care market and is projected to reach US$1tn in enterprise value by 2030. 

“We aim to address the unique challenges faced by healthcare organisations in this transformative shift,” said Bhowmick. “At the heart of this collaboration is the HealthEM.AI platform, equipping healthcare entities, including WellBe and Marquee Dental Partners, with normalised data, advanced analytics, and risk-based tools. This platform serves as a strategic asset, enhancing care delivery, optimising processes, and driving both revenue growth and cost savings.”

Tredence's leadership in data and AI significantly contributes to the technological modernisation of the healthcare sector. With HealthEM.AI, Tredence provides more than just a tool; it offers an ‘AI chassis for value-based care’, facilitating breakthrough value realisation. 

“This strategic approach solidifies us as a distinctive and invaluable partner in the healthcare industry's data transformation journey,” said Bhowmick. “The HealthEM.AI platform, complemented by Tredence's AI & Data Science expertise, serves as a dynamic asset driving innovation, delivering crucial insights and realising substantial value in the evolving healthcare landscape.”

Specialised AI and Data Science solutions in healthcare

Tredence has cultivated its expertise to aggregate extensive patient data comprehensively from diverse sources, including health plans, providers, labs, pharmacies and more. 

“Our focus is on crafting an integrated, real-time 360-degree consumer view of the highest quality, accessible to clinicians at every interaction point,” says Bhowmick. “These consumer views are elevated with AI-driven insights derived from cutting-edge models specifically tailored for the healthcare domain, harnessing the power of healthcare-specific AI and Generative AI-based large language models like BioGPT and PubMeBert.”

Tredence’s commitment extends to generating precision care plans assisted by AI, empowering collaborative navigation of the health journey for both patients and clinicians. By optimising the three pillars of value-based care - care quality, cost, and the patient and clinician experience - the company can leverage data and embed AI seamlessly into workflows.

“Two key facets distinguish our approach: Firstly, all our AI models are meticulously developed using granular patient-level data aggregated from diverse sources, ensuring a level of precision that sets us apart. 

“Secondly, we prioritise the implementation of explainable AI. Each insight or recommendation generated by our AI models is accompanied by clear explanations, fostering transparency.” 

This transparent approach instils confidence in clinicians, fortifies the feedback loop, and, consequently, propels both the adoption of Tredence’s solutions and ongoing innovation.

Helping companies to modernise their data foundation using AI and Machine Learning

Tredence helps companies to modernise their data foundation and transform their enterprise data into actionable insights using AI and Machine Learning. 

“We play a pivotal role in assisting healthcare organisations in the modernisation of their data foundation and harnessing the transformative potential of AI and Machine Learning to convert enterprise data into actionable insights. Our focus addresses the primary challenge stemming from the limitations of healthcare data due to Electronic Health Records' (EHR) insufficient data readiness and constrained interoperability.”

To overcome these obstacles, Tredence provides a comprehensive solution through HealthEM.AI's Data Integration and Activation Block, featuring five crucial steps: 

• Interoperability
• Aggregation
• Hydration
• Activation
• Harmonisation. 

“These steps are intricately designed to tackle fragmented information and data silos, allowing hospitals and health systems to unlock the intrinsic value of their data and make well-informed decisions,” says Bhowmick. “We facilitate the integration of diverse system members and patient data, creating a unified member record. Our implementation of accurate Machine Learning models aids in predicting patient needs, identifying risk-prone members and establishing chronic care programmes. Furthermore, we address the absence of social determinants of health in the client's current ecosystem.”

The outcome is a comprehensive 360-degree view of patients, providing healthcare professionals with valuable insights to make data-informed decisions that persist in EHR and other transactional systems. Tredence’s approach aims to eliminate the struggles associated with data loading or usage, fostering a more efficient and informed healthcare ecosystem.

Over the next year, Tredence has an unwavering goal to propel value creation for its shareholders, employees and clients. 

“We also rewarded our employees with a significant ESOP buyback programme worth US$30m earlier this year, recognising their invaluable contributions.”

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