Co-Founder/CRO
Arcee AI
Arcee AI builds open-weight foundation models and an enterprise platform for customizing, deploying, and owning AI systems. The company's Trinity model family spans from on-device models to a 400B parameter mixture-of-experts model, with all weights released under permissive licenses. Arcee's platform supports secure fine-tuning within virtual private clouds for regulated industries.
- Artificial Intelligence
- Developer Tools
- Software Only
- Enterprise Software
Updated 5 days ago
Funding
Raised to date
$180MRaised 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 4 rounds
+10$150M · Series B
Announced Sep 2026 · from article date
Disclosed cumulative: $180M
4/4
RoundDateAmountValuationInvestors
Founders
Product
Problem
Enterprises and developers face a trust deficit in generative AI: closed-source models lack transparency, while open-source options often raise security and performance concerns. Generic large language models also lack the domain-specific knowledge required for accurate and relevant content generation in specialized industries, producing outputs that are too broad or contain inaccuracies.
Solution
Arcee.ai provides a platform for building, customizing, and deploying open-weight language models that organizations can understand, adapt, and own. The company develops the Trinity family of foundation models, ranging from ultra-lightweight models that run on-device to a 400B parameter mixture-of-experts model for frontier reasoning tasks. Arcee's end-to-end platform operates in a virtual private cloud, enabling organizations to fine-tune models with their proprietary data securely within their own environment. The company also offers an API and hosted SaaS version, Arcee Cloud, for teams that prefer a managed deployment.
Target Audience
Primary customers are enterprises in regulated industries such as legal, healthcare, insurance, and financial services, as well as developers, researchers, and public institutions that need secure, customizable, and cost-efficient AI models.
Features
- Trinity model family with consistent skills across scales: Trinity Large (400B MoE), Trinity Mini, and Trinity Nano for on-device use
- Open-weight models released under Apache-2.0 licenses, ensuring portability and no vendor lock-in
- Model Merging technology that combines multiple AI models into a single, more capable model without increasing size
- Spectrum training optimization that reduces computational resources and training time for cost-effective custom model development
- Secure fine-tuning within a virtual private cloud environment for regulated industries
- API access and self-hosted deployment options, with models designed for efficient inference and structured outputs