Joinable Labs Secures $2M Seed, Launches RAG in a BOX for Private AI

Joinable Labs has officially emerged from stealth, announcing its launch with a $2 million seed funding round aimed at revolutionizing the deployment of private AI systems. The San Francisco-based company is focused on drastically accelerating what it terms “Time-to-Intelligence” (TTI), the critical period it takes for organizations to transform raw, fragmented data into fully operational and effective private AI solutions.

The seed funding round saw participation from a diverse group of investors, including founders and technical leaders from six AI and Web3 “unicorns,” alongside prominent venture firms such as Accomplice Blockchain, Tess Ventures, and VitalStage Ventures, as well as various strategic angel investors. This substantial backing underscores the market’s recognition of the challenges businesses face in leveraging their proprietary data for AI.

At the core of Joinable Labs’ offering is its Time-to-Intelligence Acceleration Platform. This platform is designed to streamline the complex process of building AI, particularly for sensitive or proprietary data. It achieves this by extracting unstructured or siloed enterprise data—from PDFs and spreadsheets to images and HR records—parsing it into AI-ready formats, and then training private, secure AI models tailored to an organization’s specific needs. Brian Shin, Co-Founder of Joinable Labs, emphasized that “AI Builders need more than models—they need alignment and momentum,” highlighting the company’s goal to enable teams to deploy AI from raw data in hours, rather than months.

The company’s debut product, “RAG in a BOX,” is positioned as a pivotal tool for achieving this acceleration. RAG, or Retrieval-Augmented Generation, is an AI framework that enhances the capabilities of large language models (LLMs) by integrating them with external, trusted data sources. Unlike traditional LLMs that rely solely on their pre-trained data, RAG allows models to access and incorporate real-time, specific information from an organization’s internal knowledge bases. This process significantly improves the accuracy, relevance, and factual grounding of AI-generated responses, mitigating issues like “hallucinations” or outdated information.

“RAG in a BOX” provides an all-in-one toolkit for AI builders to rapidly prototype and deploy Retrieval-Augmented Generation AI systems using their own custom, proprietary data. It allows users to load various data types, choose from leading LLMs (including those from DeepSeek, Google, Meta, and Alibaba), and deploy solutions instantly via no-code templates or an API. Joinable Labs claims this approach can accelerate the prototyping and deployment of AI systems by up to 50 times faster than conventional methods, offering speed, flexibility, and full control over data.

The focus on “Private AI” is particularly relevant in today’s data-sensitive landscape. Private AI environments are designed to process data and generate insights while maintaining strict privacy and security controls, often running models on local hardware or private cloud infrastructure to keep sensitive data in-house. This addresses critical concerns for enterprises regarding data privacy, compliance, and intellectual property protection, which are often significant barriers to adopting public AI services. Challenges in deploying private AI traditionally include high implementation and ongoing costs, the need for specialized in-house talent, and the complexity of integrating diverse data sources. Joinable Labs aims to simplify these complexities, making private AI more accessible and efficient for businesses ranging from startups to large enterprises.

Joinable Labs’ strategic roadmap includes further tools for AI model evaluation, scalable data processing, custom AI model fine-tuning, and community-powered data aggregation and self-labeling, signaling a comprehensive approach to empowering AI builders. By tackling the “Time-to-Intelligence” challenge head-on, Joinable Labs is positioning itself to be a key enabler for businesses seeking to unlock the full potential of their data with secure, high-performing private AI.