The company that taught software to read customer feedback - all of it, from everywhere - and answer the only question that matters: what should we build next?
EXHIBIT A: The Enterpret calling card. A logo for a company whose entire job is to make sense of the noise - fittingly, it keeps its own signal clean.
It is a Tuesday. A product manager has eleven Slack tabs open, a spreadsheet of survey responses, a folder of Gong call recordings, and a gut feeling. Three teams want three different things shipped, and each is certain the customers agree with them. The customers, of course, are not in the room. They are scattered across support tickets, app-store reviews, community forums, and a sales call from last March that nobody remembers.
This is the meeting Enterpret was built to end. The platform pulls feedback from more than 50 channels into one place, reads it with adaptive AI, sorts it into a taxonomy that belongs to that company and no other, and ties every complaint and compliment back to the account and the revenue behind it. The argument stops being about whose gut is right. It becomes a query.
“You should be able to write a SQL query on your customer feedback.”
That is the whole company in one sentence. Everything else - the funding, the agents, the Forbes lists - is just what happens when an unglamorous idea turns out to be right.
Every company swears it is customer-centric. Then it stores the customer's actual words in fourteen different tools that do not speak to each other. Support has Zendesk. Sales has Gong. Product has a survey tool, a community, and a Notion doc titled "ideas (do not delete)." The feedback exists. It just cannot be counted, weighted, or trusted.
The old fix was to hire someone to read it all and make a slide. That worked until the volume crossed from hundreds of comments to millions. Manual tagging does not scale, and generic AI categorizers force every business into the same dozen preset buckets - which is roughly as useful as a map that only shows continents.
“The Voice of the Customer provides direction, not just data.”
The tension Enterpret exists to resolve is simple to state and brutal to solve: customers are talking constantly, in their own messy words, across channels no single team owns - and almost none of it reaches the people deciding what to build. Closing that gap is the entire game.
Enterpret began in June 2020 with Varun Sharma and his brother Arnav. Varun had seen the problem up close - he had done customer success at Amplitude and spent time at LinkedIn, where the gap between what customers said and what teams built was a daily frustration. Arnav had been doing NLP research and engineering, with a stint at Uber, and could actually build the machine to close it.
Their bet was contrarian for the time: do not build another survey tool, and do not bolt generic sentiment analysis onto a dashboard. Instead, build custom NLP models that learn each customer's own language and construct a taxonomy unique to their business. Treat feedback like structured data you can interrogate, not a word cloud you squint at.
“No black boxes, no guesswork - just clarity teams can trust.”
Strip away the category names and Enterpret does four concrete things. It unifies feedback from 50+ sources - tickets, reviews, social, surveys, and even calls and videos - into one repository. It categorizes that feedback with an adaptive taxonomy custom-built per company, not a generic preset. It connects each signal to accounts and revenue through a Customer Knowledge Graph, so a complaint from a $2M account does not get drowned out by a hundred from free users. And as of late 2025, it acts - with no-code AI agents that detect bugs, route issues, and close the loop.
The emphasis on explainability is not a marketing line. Because product decisions ride on these insights, the platform is built to show its work: where a theme came from, how it was classified, and which exact pieces of feedback sit underneath. A black box nobody trusts is a black box nobody uses.
For a product manager, that is the difference between "I think users want dark mode" and "412 enterprise accounts asked for dark mode, weighted at $1.1M of at-risk revenue, trending up since the last release." One of those statements survives a budget meeting.
It is one thing to claim you can organize feedback. It is another to have the companies famous for caring about feedback hand you theirs. Enterpret's customer roster reads like a list of products people actually like using.
“Canva and Monday.com use Enterpret to catch early signs of churn and validate product hypotheses.”
The money followed the same logic. A $4.3M seed in 2022 became a $20.8M Series A in December 2024 - raised, notably, after the company had doubled its ARR in about seven months. Investors do not usually double down on tidier dashboards. They double down on a wedge.
Enterpret describes its ambition as building the "operating system for customer centricity." It is a grand phrase for a grounded idea: most companies want to listen to customers and simply lack the plumbing to do it at scale. Fix the plumbing, and customer-centricity stops being a poster on the wall and becomes a habit teams can actually run.
“Help every company unlock insights from customer feedback.”
The 2025 move into agents is the logical next step. Reading feedback well is useful; acting on it automatically is the payoff. If the first version of Enterpret answered "what are customers saying?", the agentic version starts answering "and what should we do about it?" - without a human first having to notice.
The fair pushback: isn't "AI reads your feedback" a feature every analytics tool will ship eventually? Probably. But the moat was never the reading. It is the per-company taxonomy that compounds over time, the knowledge graph tying words to revenue, and the trust that comes from showing your work. Those take years to build and customers years to switch away from. Generic sentiment analysis is a commodity. A model that knows your business is not.
Whether Enterpret becomes the category's default or one strong player among several is still an open question - the space has plenty of competitors, from Dovetail to Productboard to the big CX suites. What is clear is that the underlying bet has aged well. Customer signal is multiplying, attention is not, and the companies that win will be the ones that can hear clearly through the noise.
“The feedback was always there. Enterpret is the company that learned to read it.”
Back to that Tuesday meeting. The eleven Slack tabs are closed. The spreadsheet is gone. The screenshot argument is over - not because someone won, but because the question got answered. Somewhere, a product team looked at the data, agreed on what to build, and went and built it. That is a small thing. Done a few million times, it is the whole point.