Most demonstrations of enterprise artificial intelligence look impressive in laboratory settings. However, when used in real-world scenarios, such as a phone call with a freight broker, resolving price disputes, or updating data across three different systems, they often fail. HappyRobot has raised $150 million in a Series C round at a $1.2 billion valuation to demonstrate a more effective approach.
Investors, including a16z, Base10, and YC, have also increased their investments. New strategic partners include Koch, Orange, T.Capital from Deutsche Telekom, and Bankinter. This has led to a total funding amount of $200 million over 20 months. Nevertheless, for investors, the more significant metric is net revenue retention, which exceeds 150%, indicating that customers are expanding their use of services by 5–10 times.
According to Gartner forecasts, 40% of enterprises may disable autonomous AI agents by 2027. The reason is not the shortcomings of the models themselves, but rather issues with governance and workflows. Data analysis from ChatSee.ai, based on over 10,000 failures, shows that most startups create chatbots that perform only one task. Enterprise solutions, however, require agents capable of managing multi-stage workflows through calls, emails, and various systems, and this is where the failure occurs.
HappyRobot does not rely on a single large language model (LLM). Each voice call is processed by six coordinated AI models running on Kubernetes in AWS, GCP, and Azure cloud environments. These models include voice detection, automatic speech recognition (ASR), turn-taking detection, LLM, text-to-speech (TTS), and proprietary cleaning filters. All six components must complete their work with latency comparable to human performance.
To ensure the required performance, the company has developed dedicated SIP gateways for voice processing, GPU autoscaling, and real-time traffic management. The platform has three tiers. As Thomas Muscher, Head of Wave-X, described it, 'it's not about replacing one task. It's an entire chain: seven phone calls, emails, calculations, and then decision-making.'
To avoid the failures noted by Gartner, HappyRobot is expanding its operations from logistics into telecommunications, insurance, energy, and banking. Since the Series B round, the company has opened eight offices worldwide. The $150 million raised will be directed towards engineering development, go-to-market (GTM), and expansion into these new verticals.
CEO Pablo Palafox, who holds a Ph.D. in computer vision and previously worked at Meta Reality Labs, defines the company's goal as 'enterprise superintelligence'—a system where every workflow performed by an agent improves the performance of the next agent. The enterprise agent market is projected to reach $295 billion by 2035. Gartner notes that by the end of 2026, 40% of enterprise applications will integrate task-performing agents, up from 5% the previous year. HappyRobot bets that true value accumulates in the depth of operational multi-stage workflows, and if they are right, the next phase of enterprise AI development will not be determined by which model is the smartest.
Freehand has raised $75 million to solve expense management problems in enterprise supply chains, which often face manual management and financial leakage as businesses scale.
The funding round was co-led by Battery Ventures and NewRoad Capital Partners. PSP Growth, a firm led by former US Secretary of Commerce Penny Fitzpatrick, also participated in the round, as did Nexus Venture Partners. Nitin Jayakrishnan, co-founder and CEO of Freehand, stated that this funding marks the beginning of true autonomy in the corporate sector.
According to the Bureau of Economic Analysis, American companies spend over $20 trillion annually on goods, logistics, technology, and services. Freehand believes that this model is becoming too expensive to maintain. The company estimates that enterprises spend billions on software, with significantly more funds being spent on manual processes. Freehand claims that businesses spend $16 billion per year on such software and another $348 billion on the labor of people performing tasks that software could handle.
Freehand was founded in 2024 by Nitin Jayakrishnan and Abhijay Manohar. Previously, they worked on logistics at Pando, where they observed procurement and finance teams losing hours due to manual assignments. This experience solidified their belief: software should replace work, not just assist it.
The agents operate based on Freehand's so-called Category Context Graph, which combines structured enterprise data with contracts and emails, providing the agents with the necessary context before taking action. Instead of suggesting answers like a chatbot, they directly read supplier contracts, negotiate rates, approve invoices, and reconcile records within enterprise systems.
Manohar emphasizes that the key difference between an agent that acts and a chatbot that suggests lies in the context. Freehand competes with well-funded rivals such as Harvey, Norm AI, Abridge, and Writer, which have secured multi-million dollar rounds this year, as investors actively seek corporate AI agents. Freehand's distinguishing feature is its narrow specialization in procurement and supply chain finance, as well as its full-scale implementation in large companies approximately two years after its founding, rather than just pilot projects.
Matt Algar, Global Vice President of Supply Chain at Unilever, noted that Freehand has become one of the first examples of full-scale agent implementation at Unilever and represents an early core shift from auxiliary software to software that manages the supply chain. According to Grand View Research, the supply chain management market was valued at about $32.9 billion in 2024, and thanks to the automation of logistics and procurement, it is projected to double to over $76 billion by 2030.
Freehand plans to use the new funding to expand functionality beyond invoice processing to include direct material costs, as well as maintenance, repair, and operating expenses. This will allow the company to become embedded infrastructure within supply chains, rather than just another layer of software on top of them. While enterprises have spent years modernizing their supply chains by layering new software over outsourced labor, Freehand is betting on eliminating both simultaneously.
Running a creative agency or a consulting firm is becoming increasingly difficult due to growing client demands and limited operational budgets. Leaders often cannot accurately determine if individual projects are profitable because traditional project management software fails to cope with modern workloads.
To solve this industry problem, COR raised $30 million in a Series A growth round led by FTV Capital. These funds will allow COR to advance the development of its artificial intelligence-based platform. This tool provides professional service companies with complete information on project budget, team capacity, and precise financial margins.
As AI tools are integrated into daily processes, traditional work structures are transforming: teams now combine human employees with autonomous AI-based digital assistants. COR helps business leaders smoothly adapt to these changes without losing control over net profit.
For a long time, consulting and agency firms relied on manual time tracking, which caused employee dissatisfaction and made it difficult for managers to calculate the real cost of projects in real time. Standard task management tools track operations but rarely reveal the true profit margin. When projects exceed the budget unnoticed, service companies silently lose revenue. COR eliminates this problem by completely removing manual tracking and automatically monitoring project resources.
The COR platform transforms everyday task data into understandable financial analytics. Agency leaders can finally see which clients provide real growth and which ones drain cash flow. COR offers a unified operating system for professional service enterprises that combines task management, automatic time tracking, and resource planning.
Furthermore, the system provides real-time financial analytics on a single centralized dashboard, giving leaders immediate answers about team performance. The software is particularly effective when managing modern hybrid teams. Since companies use AI agents alongside human specialists, tracking overall costs becomes complex. COR calculates the exact return on investment for both human labor hours and AI computing power. This transparency allows agency leaders to negotiate fair prices with clients while protecting healthy profit margins.
The new capital injection of $30 million will significantly accelerate product development. COR intends to integrate deeper autonomous AI capabilities into its operating platform and expand its presence into new geographical markets and adjacent service industries in the coming months.
COR was founded in 2017 by Santi Bibiloni, Jose Gettas, and Gabriel Marin and has already achieved significant global success. The company's annual revenue growth reached 51% by the end of 2025, reflecting its position in the San Francisco startup market. COR currently works with thousands of teams in 38 countries, and large corporate agencies use the platform for daily operations. FTV Capital noted this strong market momentum and provided equity capital for growth. As part of the deal, FTV Partner Alex Malvon and Principal Tommy Tai will join the COR board of directors to assist with future expansion. The core mission remains simple: COR aims to become the indispensable operating platform for every modern agency and consulting firm, helping service businesses remain healthy, competitive, and highly profitable by giving leaders full control over project economics.
The tech startup Genius AI has raised $44 million in investment to capitalize on the growing demand in the personal interaction-focused service economy. With this Series D funding round, the company's valuation reached $1.15 billion.
Venture firm Lux Capital led the round. Other investors included Bessemer Venture Partners, Imaginary Ventures, L Catterton Growth, 2048 Ventures, and StepStone Private Ventures. These funds will allow Genius AI to shift its focus from beauty booking software to autonomous artificial intelligence tools for a wider range of in-person services.
The company, formerly known as GlossGenius, was founded in 2015 by identical sisters Danielle and Leah Cohen-Shohet. They initially created GlossGenius to help salon owners, aestheticians, and spa operators manage their daily operations. Danielle independently learned programming and wrote the initial code, and over time, the software became a dominant force in the market, helping small businesses process payments, book clients, and promote their services.
The company is now changing its name to Genius AI, signifying a broader mission. As Genius AI, the platform will support all in-person professionals. It is planned for use in medical spas, physical therapy centers, fitness studios, injections, and health clinics.
The physical service economy in the United States includes about eight million businesses generating over $2 trillion in annual consumer spending. Although studies show that business owners spend nearly 36% of their working time on administrative tasks, Genius AI aims to completely eliminate this bureaucratic burden. The platform goes beyond simple assistance tools and transforms into an autonomous AI agent capable of handling complex tasks end-to-end, freeing up business owners to interact with clients.
The company demonstrates impressive growth and operational scale. Currently, the system is used by over 125,000 businesses across half of the US zip codes. Genius AI reports that its platform is approaching $200 million in annual revenue. To date, the company's tools have helped clients save over 112 million hours of administrative work. To deepen penetration into the healthcare sector, the company has added full HIPAA compliance, allowing physical therapists and clinical specialists to securely store sensitive patient data. This gives Genius AI a significant advantage over traditional tools lacking privacy protection. As artificial intelligence automates office work, human care becomes even more valuable, as skilled professionals like masseuses and trainers provide care that computer code cannot replicate. The new funding is planned to be used to expand software development and increase the engineering team.
