Netomi, a San Francisco-based startup specializing in enterprise AI for customer service, has secured $110 million in new funding. The round was led by Accenture Ventures, with significant participation from Adobe Ventures, WndrCo, Silver Lake Waterman, NAVER Ventures, Metis Strategy, and Fin Capital.
Notably, Jeffrey Katzenberg, co-founder of DreamWorks and managing partner of WndrCo, has joined Netomi’s board. This latest investment builds upon early backing from prominent AI figures, including OpenAI co-founder Greg Brockman, Google DeepMind co-founder Demis Hassabis, and Microsoft AI CEO Mustafa Suleyman.
While the financial figure is substantial, the strategic implications of the deal are more significant. It signals a shift in enterprise AI: moving away from simple chatbots toward systems that operate effectively within the complex, regulated environments of large corporations.
A Strategic Pivot in Enterprise AI
The current AI landscape is saturated with capital, but Netomi’s funding round highlights a distinct evolution in how businesses view artificial intelligence. The market is no longer divided by whether companies have a chatbot or not; rather, the divide is between those who can demonstrate AI efficacy in real-world, high-stakes operations and those whose solutions only succeed in controlled demos.
Competitors are moving fast. Sierra, led by former Salesforce co-CEO Bret Taylor, raised $350 million at a $10 billion valuation in September 2025 and has already made three acquisitions in 2026. Similarly, Decagon tripled its valuation to $4.5 billion in January 2026. Major platforms like Salesforce, ServiceNow, and Intercom are integrating AI agents into their ecosystems, with Intercom’s Fin AI agent reportedly generating $100 million in annual recurring revenue. Gartner predicts that by the end of 2026, 40% of enterprise applications will include task-specific AI agents, up from less than 5% in 2025.
Netomi’s $110 million raise is strategically constructed to compete in this space. By combining Accenture’s global consulting reach and Adobe’s dominance in digital experience management with Netomi’s production-ready technology, the company aims to embed AI as the core intelligence governing digital interactions, rather than a superficial add-on.
“Most companies in the customer experience space are simply swapping a human for an AI. We are leapfrogging that altogether — merging the two layers.”
— Justin Wexler, Partner at WndrCo
Distribution as a Competitive Advantage
The structure of Netomi’s funding deal reveals a sophisticated approach to market penetration. Beyond capital, the company has secured critical distribution channels:
- Accenture Alliance: Accenture has entered a global partnership to deploy Netomi’s platform to its Fortune 100 clients. Hundreds of Accenture consultants are undergoing training on the Netomi system, providing a distribution network few startups can match.
- Adobe Integration: Netomi will integrate into Adobe’s Brand Concierge agentic ecosystem. This allows the AI to operate within the software layer many large brands already use for website and content management.
- CIO Advisory Access: Metis Strategy provides access to chief information officer networks, facilitating high-level enterprise adoption.
Ndidi Oteh, CEO of Accenture Song, described the partnership as a way to help clients “reinvent how they serve their customers — seamlessly, responsibly and at scale.”
From Reactive to Preventative: The “Upstream” Model
Netomi’s core thesis challenges the traditional model of customer service. Currently, most AI systems are downstream : a customer encounters a problem, contacts support, and waits for a resolution. Even if AI speeds up the response, the friction and frustration have already occurred.
Netomi aims to move upstream, anticipating issues before they generate a support ticket. CEO Puneet Mehta argues that the $500 billion spent annually on human labor for customer service is largely reactive. By preventing problems, companies can eliminate the cost and friction of support interactions entirely.
This approach is rooted in Mehta’s background in low-latency automated trading on Wall Street. He draws a direct parallel between trading systems and customer experience:
- Multi-Signal Analysis: Just as trading algorithms process market data, news, and risk assessments simultaneously, Netomi’s AI analyzes customer context, behavior, and history.
- Situational Awareness: The system doesn’t just react to what a customer says; it infers what the customer needs based on their situation.
- Proactive Resolution: If the AI can predict a problem, it can resolve it before the customer even realizes there is an issue.
“What large language models by themselves did was they essentially democratized just raw intelligence. We are democratizing context, and that changes everything.”
— Puneet Mehta, CEO of Netomi
Real-Time Orchestration and Governance
Netomi’s technology, described as AI-embedded customer experience orchestration, goes beyond text-based interactions. It can dynamically rearrange digital interfaces based on individual user needs.
For example, using its integration with Adobe Experience Manager, Netomi’s AI can:
* Reorganize product pages in real-time based on browsing behavior.
* Surface specific warnings or compatibility issues before checkout.
* Present different content to different users visiting the same page, creating a personalized “generative website” experience.
This capability extends to physical spaces. Coach (owned by Tapestry) deployed Netomi’s platform in its flagship stores during the holiday season to guide customers through the retail space, with plans for a chainwide rollout.
Safety and Compliance
Given the high stakes of enterprise environments, Netomi emphasizes governance. The platform uses an AI authority matrix, a real-time system that determines when AI can act autonomously and when it must escalate to a human. This “autonomous driving” approach ensures that:
* Regulated industries can lock specific endpoints to deterministic, rules-based flows.
* All actions are version-controlled, traceable, and auditable.
* Metadata is retained for seven years to meet compliance standards.
Performance at Scale
Netomi claims its system can handle extreme loads without sacrificing accuracy or speed. Reported metrics include:
* DraftKings: Handling over 40,000 concurrent requests per second during major sporting events with sub-three-second response times and 98% intent classification accuracy.
* Paramount: Deploying across chat and voice channels in two weeks, then scaling successfully through a weekend featuring a major UFC event and the AFC Championship.
While these figures are self-reported and lack independent benchmarking, they illustrate the shift from simple Q&A bots to distributed systems challenges. At this scale, the question is not just whether the AI can answer a question, but whether the entire system can make safe, consistent decisions under pressure.
Conclusion
Netomi’s $110 million raise represents a bet that the future of enterprise AI lies not in more conversations, but in fewer necessary interactions. By leveraging partnerships with Accenture and Adobe, and applying trading-engine logic to customer experience, Netomi aims to make AI support invisible, proactive, and deeply integrated into the digital fabric of large businesses. As the market matures, the ability to deliver trusted, governed, and scalable AI will likely distinguish the leaders from the laggards.
