Founder
Nous Research
Nous Research develops and releases high-performance open-source language models and agentic tools under permissive MIT licenses. Its flagship product, Hermes Agent, is a self-improving AI agent with a built-in learning loop that creates reusable skills from experience and builds a model of user preferences across sessions. The company also offers Hermes for Businesses, enabling enterprises to build and own their intelligence stacks with model choice optimization and private AI scaling.
- Artificial Intelligence
- AI Agents
- Developer Tools
- Software Only
Updated 27 days ago
Funding
Raised to date
$158MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
across 3 rounds
+17$90M · Series B
Announced Oct 2026 · from article date
Disclosed cumulative: $145.2M
3/3
RoundDateAmountValuationInvestors
Founders
Product
Problem
Proprietary large language models dominate the market, limiting transparency, increasing cost barriers, and often embedding unchecked biases. Organizations that need customizable, auditable AI capabilities lack accessible, high-performance open-source alternatives for training and deployment.
Solution
Nous Research addresses this gap by developing and releasing high-performance open-source language models and agentic tools that can be fine-tuned for specific domains. The company builds a modular training stack that supports distributed compute across heterogeneous clusters, enabling unbiased model scaling without reliance on single-vendor hardware. Their data synthesis pipelines generate diverse, ethically curated corpora to reduce systematic bias during pre-training. By open-sourcing model architectures, training scripts, and evaluation suites, they empower downstream users to audit, extend, and deploy models under transparent licensing. Integrated tooling for reasoning and instruction tuning further enhances model utility for complex tasks while remaining fully auditable. The company's flagship product, Hermes Agent, is a self-improving AI agent with a built-in learning loop that creates skills from experience, improves them during use, and builds a deepening model of user preferences across sessions.
Target Audience
Primary users are AI research labs, enterprise engineering teams, and developer communities that require transparent, customizable language models for proprietary or public-interest applications. The offering also serves NGOs and policy groups focused on AI ethics and human-rights-aligned technology.
Features
- Scalable, container-native training framework compatible with Kubernetes and Slurm for multi-node GPU orchestration
- Open-source model architectures published under permissive MIT licenses, with documented hyperparameter configurations
- Synthetic data generation engine that blends curated web crawls, domain-specific corpora, and bias-mitigation filters
- Fine-tuning toolkit supporting LoRA, adapter modules, and instruction-following paradigms for rapid task adaptation
- Reasoning augmentation layer implementing chain-of-thought prompting and tool-use APIs out-of-the-box
- Hermes Agent with built-in learning loop that creates reusable skills from experience and persists knowledge across sessions
- Public model hub with versioned checkpoints, metadata, and evaluation benchmarks accessible via RESTful API and Python SDK
- Community governance model that incorporates external audits and contribution guidelines to maintain unbiased development