A Berlin-based startup has raised $15 million to scale its platform for enterprise AI customer agents, a bet that companies don't need to build their own artificial intelligence to fix customer service operations. telli, founded in 2024, secured the seed round led by redalpine, with participation from Cherry Ventures, Y Combinator, and other investors, according to the company.
The platform automates customer interactions across voice calls, WhatsApp, live chat, and email. telli says its enterprise clients, including Sky, Enpal, Viessmann, and Vaillant, already rely on the system for millions of customer interactions.
Multi-channel design and funding strategy
The investment is earmarked for scaling telli's enterprise AI agent platform, which automates customer contact across multiple communication channels rather than confining itself to a single one. That multi-channel design is central to why investors backed the round. Traditional contact center software tends to be built channel by channel, forcing companies to stitch together separate tools for phone, chat, and messaging. telli instead built what it calls an AI-first platform from the ground up, letting enterprises manage the full spectrum of customer contact through a single system.
Rather than pouring the funding into research on new AI models, telli is directing resources toward workflow automation, enterprise integration, and expanding the reach of its existing platform. That distinction positions the company as an applications layer sitting on top of established AI technology, not as a competitor to the foundation-model labs.
How the platform works with human teams
telli's AI solutions handle first contact with customers, provide answers to common questions, evaluate potential leads, and facilitate support requests across voice, messaging, and digital platforms. A support system called Charlie, based on AI, reviews the content of those conversations, flags challenges, and helps refine agent performance over time.
The platform is not pitched as a replacement for human staff. It is designed to augment customer service teams, taking over repetitive interactions so employees can focus on relationship management and more complex conversations. That framing matters for enterprise buyers wary of AI rollouts that promise full automation but end up frustrating customers who need a human touch for nuanced issues. For professionals exploring how these tools fit into existing workflows, resources on AI for Customer Support and AI Agents & Automation can clarify practical applications.
Clients and founders' track record
telli says its platform already supports millions of interactions for major companies such as Sky, Enpal, Viessmann, and Vaillant. These partners are already expanding their deployments, a sign that adoption is deepening rather than just spreading across new logos. Growth, according to the company, has come largely through referrals and expansion within existing enterprise accounts.
telli's founders previously helped scale Enpal's heat pump business, giving them firsthand exposure to the operational strain of managing large, customer-facing teams. That background shows up in the company's product philosophy: telli builds enterprise applications using existing speech recognition, large language models, and voice generation technology rather than chasing its own foundation models. The approach allows the company to focus engineering effort on integration and workflow automation instead of AI research that larger labs are already pursuing at massive scale.
What comes next
telli plans to keep expanding across Europe before pursuing growth outside the continent, a sequencing that suggests the company wants to deepen its base of enterprise clients first. With fresh capital, an expanding customer roster, and growing reliance on referrals from companies like Sky and Enpal, telli is positioning itself inside a European enterprise AI ecosystem that investors are betting will keep expanding.
Why this matters for customer support professionals
For people working in customer support, telli's model points to a specific near-term future: AI handling the high-volume, repetitive tier of interactions while human agents take on complex cases and relationship work. The company's emphasis on augmenting teams rather than replacing them, combined with its founders' operational background, suggests that practical integration skills will matter more than AI expertise alone. Support professionals who understand how to work alongside these systems may find themselves managing the exceptions and escalations that automation can't resolve.
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