Stockholm-based Agaton has emerged from stealth with fresh seed funding, positioning its agentic AI software as a way for enterprises to turn everyday customer conversations into revenue-driving intelligence. The company says its platform helps sales and service teams spot buying intent, churn risk, and sentiment changes as interactions happen. The announcement comes as European investors continue to back automation-focused enterprise AI tools that promise measurable business outcomes.
Seed funding and investors
Agaton reported a $10 million in total seed funding in some coverage, with the round co-led by Inception Fund and Alstin Capital. Seed+speed Ventures and Foundry Ventures also participated, alongside angel investors including Peter Sarlin of Silo AI and Kieran Flanagan, HubSpot’s CMO investing as a scout for Sequoia Capital. The company said the capital will be used to accelerate go-to-market execution, expand AI capabilities, and continue product development while it scales internationally.
Building “AI-powered sales superiority”
In comments published with the funding news, CEO and co-founder Andreas Kullberg framed the company’s thesis around making sales teams “smarter” through AI rather than simply larger. He said Agaton aims to convert every customer interaction into strategic intelligence that frontline teams can act on quickly. Investors echoed the “immediate impact” message, pointing to early revenue traction as proof of product-market fit.
From transcription to agentic action
Agaton is pitching itself as a step beyond conventional conversation intelligence tools that largely stop at recording and transcription. The company says its proprietary engine correlates qualitative and quantitative signals across customer interactions to identify buying intent, shifting sentiment, and churn indicators, then translates them into next-step recommendations. This approach is designed to reduce reliance on sampled data or market assumptions that can skew commercial decision-making.
What the platform is designed to do
According to the company, the software is built to support workflow automation across sales and customer service, including coaching guidance for representatives and assistance for quality assurance processes. Agaton argues that understanding not only what customers say but how they say it can unlock more accurate revenue and retention signals. The broader objective is to improve training, performance management, and even product and pricing decisions using conversation-derived intelligence at scale.
Early traction and performance claims
Agaton says it has signed “millions” in annual recurring revenue within roughly a year of founding and has analyzed more than four million customer calls through the platform. It also reports operational improvements, including reducing average quality assurance handling time by as much as 80 percent for some users. The company further claims seven-fold year-on-year revenue growth, presenting those metrics as validation that its model delivers more than experimental insights.
Customers and partnerships
The startup reports adoption among Nordic enterprises across sectors such as telecom and financial services, naming customers including Telenor, Telia, Lendo, and Axo Finans. Agaton has also announced a partnership with Foundever, which it describes as giving access to a global network of 150,000 agents through the business process outsourcing provider. The company positions these relationships as both a distribution lever and a testbed for scaling best-in-class sales performance across large teams.
Founding team and enterprise background
Founded in 2024, Agaton is led by Kullberg alongside co-founder John Kristensen as COO and CTO Yi Fu, with the team highlighting experience spanning enterprise AI transformation and large-scale commercial operations. Coverage notes prior work tied to organizations including Volvo Cars, Tele2, and other large brands, with an emphasis on integrating into existing enterprise systems. The company says this foundation is intended to reduce friction in deployment and speed up time to measurable results.
Security and data privacy positioning
Agaton is placing data security and privacy at the center of its pitch, stating that customers maintain ownership and control over their conversational data. It says personally identifiable information is automatically redacted and that organizations can decide how long audio is retained, positioning these features as supportive of regulatory requirements such as GDPR. The company also states it does not collect, store, or sell customer data, framing the platform as a way to unlock value without compromising sensitive information.
With $10 million in seed capital, Agaton is betting that agentic intelligence applied to real customer conversations can reshape how enterprises run sales and service operations. Its thesis is that revenue intelligence should be continuous and actionable, not periodic and retrospective, and that automation can help scale top-performer behaviors across large organizations. The next test will be whether the startup can maintain momentum as it expands its team and global footprint while proving repeatable outcomes across a broader international customer base.