Nous Research, the decentralized artificial intelligence developer behind the Hermes agent, is nearing completion of a new funding round that seeks to raise at least $75 million at a valuation of about $1.5 billion, according to reports.
The round is expected to be led by Robot Ventures, with Union Square Ventures and other firms also taking part. If completed on the reported terms, the financing would rank among the larger private raises this year for an open-source AI project, underscoring continued demand for software tools that can automate computer-based tasks, write code, search the web and interact with online services.
The deal would also represent a significant valuation increase for Nous Research. The company was valued near $1 billion in April 2025, when it raised a $50 million Series A led by Paradigm. That round brought its total disclosed funding to about $70 million at the time. A new $75 million raise would push total capital raised well beyond that level and give the startup more resources to expand Hermes, improve infrastructure and develop revenue streams around its agent software.
The latest financing discussions come as open-source AI builders compete with large, closed-model developers and as autonomous agents move from experimental demos toward practical software tools. Hermes is designed to run tasks on behalf of users across local machines, servers and cloud environments. The broader market is watching whether such agents can evolve from productivity assistants into core infrastructure for online work, software development and automated transactions.
A larger bet on open-source AI agents
Nous Research was founded in 2023 by figures known in open-source AI circles, including Quesnelle, Malhotra, Teknium and Mitra. The company has built its reputation around decentralized development, public model releases and tools intended to give developers more control over how AI systems run.
Its known backers have included Paradigm, North Island Ventures, OSS Capital, Robot Ventures and Balaji Srinivasan. The reported participation of Robot Ventures in the new round would deepen its connection to the company, while the involvement of Union Square Ventures would add another prominent technology-focused firm to the cap table.
The size of the proposed raise is notable because open-source AI businesses often face a difficult balance. They can gain rapid developer adoption by publishing code and models openly, but they still need to cover high infrastructure costs, support enterprise-grade products and build durable revenue models. For Nous Research, Hermes appears to be the commercial and technical centerpiece of that effort.
The funding, if finalized, would likely support several priorities. These include expanding product features, strengthening model deployment systems, improving reliability for users running agents continuously, and exploring paid services around hosted infrastructure. The company already offers a cloud-hosted option that reportedly costs between $20 and $200 per month, alongside versions that can run on desktops or virtual private servers.
Hermes gains developer attention
Hermes is an AI agent built to perform a range of computer-based actions. Its stated capabilities include coding, image recognition, web searches and task execution through user interaction. The system is also designed to adapt over time, learning from usage patterns and developing new skills as users work with it.
The product competes with OpenClaw, another open-source framework designed to carry out local tasks on personal computers. OpenClaw gained traction by focusing on practical online chores and local automation. Hermes followed with a broader feature set and has since attracted attention from developers interested in agents that can run either locally or in hosted environments.
Public code repository metrics suggest that Hermes has developed a meaningful community. Available data show roughly 214,000 GitHub stars and nearly 40,000 forks, two signals often used to measure developer interest in open-source projects. Stars do not automatically translate into paying customers, but they can indicate visibility, experimentation and community momentum. Forks are especially important because they show that developers are copying the codebase to modify it, test it or build related projects.
That level of activity gives Nous Research a base from which to turn developer usage into commercial products. The challenge is converting attention into sustainable income without alienating the open-source community that helped the tool grow. Many open-source AI companies face the same issue: broad access can accelerate adoption, but paid features must be compelling enough to support ongoing model development and infrastructure costs.
Hermes also connects with apps such as Telegram and Discord. That allows users to automate communication-related tasks, manage 24-hour operations or build bots that respond to commands and events. Integrations of that kind are increasingly important because AI agents become more useful when they can operate inside existing workflows rather than forcing users into a separate interface.
Why the reported valuation matters
A $1.5 billion valuation would place Nous Research among the more closely watched independent AI-agent companies. The figure also signals that private technology backers remain willing to pay high prices for teams building tools around automation, open-source models and agentic workflows.
The valuation increase from about $1 billion in 2025 to a reported $1.5 billion in 2026 suggests confidence in the company’s progress, although the final terms of the round may still change. The roughly 15-month gap between the prior financing and the new discussions also shows how quickly the agent software market has developed.
AI agents have become one of the most competitive segments of the broader artificial intelligence industry. Unlike chatbots that primarily answer questions, agents are designed to take actions. They can open files, use software, write code, browse websites, summarize information, trigger transactions and coordinate with other systems. That shift has raised expectations that agent software could become a new interface for digital work.
For now, the market is still early. Many agents remain unreliable when given complex tasks, and users often need to supervise their outputs. Security is also a major issue. Systems that can execute commands, connect to accounts or interact with financial rails need strong safeguards to prevent errors, abuse or unintended actions. Any company in this field must show that its agents can be useful without exposing users to unacceptable operational risks.
The reported Nous Research round suggests that major funds believe these problems are solvable, or at least that the market opportunity is large enough to justify continued funding.
The link with digital asset markets
The rise of AI agents has also become a theme in digital asset markets. Separate market-tracking data show that the total value of tokens linked to AI agents increased sharply during the fourth quarter of 2024, rising from about $4.8 billion to $15.5 billion. The move reflected enthusiasm for projects that combine automated software agents with blockchain-based payments, identity systems or decentralized computing resources.
Blockchain networks are relevant to agent software because autonomous tools may need to make small payments, access services, verify activity or coordinate with other programs without relying on traditional payment accounts. Fast, low-cost ledgers are often discussed in that context because they can process frequent, small transactions more efficiently than slower, higher-cost systems.
Public blockchain data dashboards have shown that Solana has held a large share of activity in the agent-linked token segment, with one reading placing its share at 56.48%. The network’s low fees and high transaction throughput have made it a common venue for experiments involving small payments, token launches and consumer-facing applications.
Still, the connection between AI agents and tokens remains speculative in many cases. A rising token market does not necessarily mean that the underlying software is being used in production. Traders following the sector often watch for evidence of real integrations, such as agents paying for services, using wallets, accessing decentralized compute markets or interacting with blockchain-based identity systems.
That distinction is important. The strongest long-term signal would not be token branding alone, but actual usage by agents that need open payment networks to complete tasks. If desktop assistants and autonomous bots begin using public ledgers as part of normal operation, the link between AI software and digital assets could become more concrete. If they do not, the token activity may remain largely narrative-driven.
What traders are watching
Market participants are likely to monitor Nous Research’s public repositories closely following reports of the new raise. Open-source development activity can provide early clues about product direction, especially for companies whose tools are built in public.
For Hermes, traders and developers may focus on whether new software updates add deeper links to open payment networks, wallet systems, decentralized compute platforms or permissioned transaction tools. Any direct connection between a widely used desktop agent and blockchain infrastructure would attract attention across both AI and digital asset markets.
However, public code activity should be interpreted with care. A code commit does not always indicate a commercial launch. Experimental branches, tests and community contributions may never become mainline features. In open-source projects, development can move quickly, but product readiness depends on security reviews, usability and infrastructure support.
There is also a difference between agents that can connect to messaging apps and agents that can safely control money or execute financial actions. The latter requires stronger guardrails. Systems that interact with payments or tokens must handle private keys, permissions, spending limits, fraud prevention and error recovery. A powerful agent with weak controls could create serious losses for users.
For that reason, the most meaningful updates would be those that show not only new connectivity, but also clear security design. Permission management, transaction previews, sandboxing and auditability are likely to matter as much as speed or convenience.
Competition intensifies among agent frameworks
The competitive backdrop is also important. OpenClaw, the rival open-source framework associated with Steinberger, was originally built to handle basic online chores on personal computers. Its early traction helped define expectations for local agents that can operate directly on a user’s machine rather than relying entirely on cloud-hosted services.
That model has several advantages. Local execution can give users more control over data, reduce dependence on centralized platforms and allow agents to interact directly with installed software. At the same time, local agents can be harder to support across different operating systems, device configurations and security settings.
Hermes appears to be positioned as a flexible option that can run locally, on virtual private servers or through a paid cloud service. That distribution model may help Nous Research serve different types of users. Developers may prefer local or server-based setups, while less technical customers may choose a hosted product.
The contest between Hermes, OpenClaw and other agent frameworks is likely to center on reliability, ease of use, extensibility and trust. In the near term, developer enthusiasm can drive adoption. Over time, users will judge these tools by whether they complete tasks accurately, save time and avoid costly mistakes.
Business adoption creates a larger market
The broader business environment is favorable for AI automation. By mid-2026, recent studies indicate that 88% of modern companies use machine learning in at least one core business function. That does not mean all of them use autonomous agents, but it shows that AI has moved deeply into corporate operations.
This adoption creates a large potential market for tools that automate repeatable work. Companies already use machine learning for customer support, fraud detection, document processing, coding assistance, logistics, marketing analysis and internal knowledge management. Agents could extend those uses by not only generating information, but also acting on it.
For example, an agent could monitor support tickets, draft responses, update customer records and escalate unusual cases. A development agent could identify a bug, write a patch, run tests and submit a pull request. An operations agent could track cloud spending, identify unused resources and recommend changes. The commercial value comes from reducing manual steps while keeping humans in control of important decisions.
Nous Research’s challenge is to prove that Hermes can serve these kinds of workloads reliably. Open-source credibility and developer adoption are helpful starting points, but enterprise users often require service-level guarantees, compliance features, documentation, support and clear accountability.
Monetization remains the key test
The reported funding round would give Nous Research more time and resources, but the long-term test remains monetization. Open-source AI projects can attract large communities without immediately producing large revenue. The companies that succeed commercially usually find a way to sell hosting, support, premium features, enterprise tools or infrastructure access.
Hermes’ paid cloud option is one path. By charging for hosted access, Nous Research can serve users who do not want to manage their own machines or servers. The company may also build paid tiers around continuous operation, integrations, collaboration features or enterprise controls.
Another potential route is infrastructure. Agents that run around the clock may require compute resources, memory, storage, monitoring and secure execution environments. If Hermes becomes widely used, Nous Research could earn revenue by making those services easier to manage.
The company may also benefit from partnerships, especially if businesses want customized versions of Hermes or integrations with internal systems. But such deals can be resource-intensive and may pull engineering teams away from open-source development.
Balancing those priorities will be central to the company’s next phase. Traders and technology watchers will be looking for signs that Nous Research can convert community momentum into recurring revenue without losing the openness that helped Hermes stand out.
A deal that reflects a wider shift
The expected $75 million raise at a $1.5 billion valuation is more than a company-specific milestone. It reflects a wider shift toward software that can act, not just respond. AI agents are becoming a major focus for developers, venture firms, enterprise buyers and digital asset communities because they promise to automate work across the internet.
Nous Research has positioned Hermes at the center of that trend with an open-source approach, strong developer visibility and multiple deployment options. The reported new capital would strengthen its ability to compete in a crowded market, but it also raises expectations.
The next phase will depend on execution. Hermes must become more reliable, more secure and more useful in real workflows. If the product expands into payments or blockchain-based services, those integrations will need to demonstrate practical value rather than simply follow market excitement.
For now, the reported financing shows that demand for agent infrastructure remains strong. It also confirms that open-source AI companies are attracting serious capital as automation becomes a larger part of business and online activity. Nous Research may soon have a larger balance sheet to pursue that opportunity, but the market will judge the company by whether Hermes can turn developer interest into dependable, widely used software.
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