Varun Sharma and his brother Arnav have developed Enterpret, a platform designed to integrate customer feedback and improve business decision-making.
In a landscape increasingly shaped by artificial intelligence and automation, the need for businesses to effectively capture and utilise customer feedback has become paramount. Despite growing technological advancements, many companies continue to struggle to manage this vital data, as evidenced by a 2020 survey from Productboard, which revealed that a staggering 90% of companies fail to successfully harness feedback from all available channels. Furthermore, one-third of the firms surveyed reported having no formal feedback-capturing mechanisms in place.
This disconnect between potential and practice was evident to Varun Sharma during his tenure leading customer success initiatives at LinkedIn, Amplitude, and Scale AI. Noticing a persistent gap in how product and customer experience teams were able to make informed decisions based on customer insights, Sharma began to devise a solution. In 2020, he partnered with his brother, Arnav Sharma, who had three years of experience as a software engineer at Uber, to develop a platform designed specifically to alleviate these challenges.
Speaking to TechCrunch, Varun Sharma articulated the importance of customer interactions as a valuable yet largely underutilised dataset for enterprises. He stated, “If they’re unlocked meaningfully, they can build best-in-class products and drive business growth.”
The result of their collaboration is Enterpret, a platform that integrates with various customer feedback sources and utilises sophisticated algorithms to derive actionable insights. By capturing data in real-time from sales calls, support tickets, survey responses, and other interactions, Enterpret quantifies this information and correlates it with product usage and revenue. This integration allows companies to operationalise decision-making processes and better understand their customers’ needs.
“Enterpret is able to pull in all customer interactions of a company in real-time… and then join the output with product usage and revenue data of the company to operationalize decision making,” Varun explained. With a commitment to data privacy, Enterpret employs established protocols to remove personally identifiable information to comply with GDPR regulations.
The platform has already attracted high-profile clients, including design platform Canva and project management tool Monday.com. Through its analysis of millions of customer feedback entries, Enterpret has been instrumental in both identifying early signs of customer churn and validating product hypotheses.
Despite the competitive landscape, which includes players like ScopeAI and Zendesk-owned Klaus, Enterpret appears to be making definitive strides. The San Francisco-based startup reported a substantial growth trajectory, doubling its annual recurring revenue between May and the present. Varun Sharma noted that the company’s contract value has also doubled over the past year, complementing success with a recent funding boost of $20.8 million in a Series A round, led by Canaan Partners with participation from several prominent investors, including Kleiner Perkins.
“Our ARR is in the seven figures,” Varun stated. “The momentum is strong. We decided to raise capital to support the growth.” Looking ahead, the company plans to allocate funds from the Series A towards hiring initiatives and advancing product research and development. Overall, Enterpret has now amassed a total of $25 million in funding since its inception.
“Their ambitious vision is rooted in the realisation that customer feedback is the most valuable data set of any company,” Varun pointed out. The mission of Enterpret is clear: to create the ultimate platform for businesses that aim to place customer-centricity at the heart of their operations.
Source: Noah Wire Services
- https://dialzara.com/blog/ai-powered-customer-feedback-automation-guide/ – Corroborates the use of AI in automating customer feedback collection, analysis, and response, highlighting benefits such as improved customer satisfaction and data-driven decision-making.
- https://www.zonkafeedback.com/blog/ai-customer-feedback-management – Supports the role of AI in customer feedback management, including natural language processing, sentiment analysis, and workflow automation to enhance customer service and efficiency.
- https://survicate.com/blog/customer-feedback-ai/ – Details the benefits of AI in customer feedback analysis, such as saving time, understanding customer needs better, and performing sentiment analysis to drive actionable insights.
- https://www.artsyltech.com/blog/the-ai-as-a-tool-for-processing-customer-feedback – Explains how AI transforms customer feedback processing by providing real-time insights, detecting trends, and automating feedback analysis to improve customer satisfaction and operational efficiency.
- https://www.lumoa.me/blog/artificial-intelligence-customer-feedback-analysis/ – Highlights the precision and uniformity of AI tools in analyzing customer feedback, saving time and resources, and enhancing customer experience through real-time interactions and sentiment analysis.
- https://dialzara.com/blog/ai-powered-customer-feedback-automation-guide/ – Discusses the integration of AI with various feedback sources and the importance of responding to customer feedback to increase loyalty and satisfaction.
- https://www.zonkafeedback.com/blog/ai-customer-feedback-management – Emphasizes the use of AI in automating feedback collection from multiple channels, such as surveys, chatbots, and social media, to provide comprehensive insights.
- https://survicate.com/blog/customer-feedback-ai/ – Describes how AI helps in identifying areas for improvement and monitoring the impact of changes made based on customer feedback, leading to faster and more informed decision-making.
- https://www.artsyltech.com/blog/the-ai-as-a-tool-for-processing-customer-feedback – Illustrates the capability of AI to prioritize issues based on frequency or severity of feedback, enabling companies to address critical customer concerns promptly.
- https://www.lumoa.me/blog/artificial-intelligence-customer-feedback-analysis/ – Explains how AI tools can analyze customer behavior patterns, needs, expectations, and pain points, and highlight correlations between different data sets for better decision-making.
- https://dialzara.com/blog/ai-powered-customer-feedback-automation-guide/ – Outlines the continuous improvement process using AI, including tracking feedback trends and monitoring the impact of changes to ensure effective customer feedback management.












