Assisterr, a Cambridge-based AI Infrastructure startup dedicated to revolutionizing artificial intelligence through community ownership and a network of small language models, has successfully closed a $1.7 million pre-seed funding round. The investment round saw participation from prominent Web3 venture funds including Web3.com Ventures, Moonhill capital, Contango, Outlier Ventures, Decasonic, Zephyrus Capital, Wise3 Ventures, Saxon, GFI Ventures, X Ventures, Koyamaki, Lucid Drakes Ventures, and notable angels, including Michael Heinrich, co-founder & CEO at 0g.ai, Mark Rydon, co-founder & CEO at Aethir, Nader Dabit, Director of Developer Relations at Eigen Labs, Anthony Lesoismier-Geniaux, co-founder at SwissBorg, Ethan Francis, Head of Developer Relationships at Particle Network and more committed to advancing decentralized AI solutions. The company aims to empower developers to build their own AI use cases using Assisterr's infrastructure.
Assisterr is revolutionizing the AI landscape with its innovative approach to Small Language Models. Leveraging the Solana blockchain, Assisterr empowers communities to collaborate, aggregate, and monetize their data and expertise in specialized subjects. Small Language Models (SLMs) are tailored AI models optimized for efficient performance on edge devices focusing on specific domain tasks.
Since its launch, Assisterr has achieved major milestones, including attracting 150,000 registered users to its platform. Assisterr has also successfully launched more than 60 Small Language Models (SLMs) curated for leading Web3 protocols such as Solana, Optimism, 0g.ai, and NEAR. Additionally, the company has garnered recognition by winning multiple global hackathons, including the recent AI x Crypto event hosted by BeWater, OKX, and Binance Labs. Furthermore, Assisterr has been selected to participate in Google's AI Startups program, securing $350,000 in funding that supports its GPU, CPU, and cloud infrastructure needs.
Nick Havryliak, CEO, and Co-founder at Assisterr shared the company’s vision:
“At Assisterr, we are building an AI tokenization stack to ensure fair compensation for data owners and contributors. Our platform manages the entire lifecycle of SLM training, enabling features like data provenance tracking, fine-tuning, and the launch of SLM-powered Agents. Web3 component allows data-owners to contribute their data and expertise to domain-specific SLMs and capture the value from such contributions.”
Assisterr’s core technology stack
Small language models are neural networks trained on extensive text data sets. They are primarily designed to generate text resembling the patterns found in their training data. SLMs are smaller and more efficient than traditional Large Language Models (LLMs), capable of handling up to 8 billion parameters. Their deployment on edge devices including laptops and smartphones makes them ideal for applications where data privacy and efficiency are the need of the hour.
Assisterr’s core technology stack features several core components. The Data Provenance Protocol plays an important role in enabling decentralized coordination, ensuring the accuracy and reliability of domain-specific Small Language Models (SLMs). Their AI Lab incorporates intuitive no-code functionality, empowering users to seamlessly create, customize, and manage community-owned SLMs and SLM-powered Agents. Additionally, the SLM-Agent Marketplace serves as a platform for tackling distribution challenges by attracting early adopters and fostering growth within the AI ecosystem. These solutions support Assisterr’s commitment to advancing decentralized AI technologies while enhancing accessibility and innovation in AI model development and deployment.
With the influx of fresh funding, Assisterr will focus on several initiatives including protocol development and forming strategic partnerships to strengthen its infrastructure. The company also plans to drive ecosystem growth by launching an incentive program tailored for model builders and data contributors.
Additionally, Assisterr aims to enhance accessibility with the introduction of a no-code AI lab module, designed to attract a broader range of creative AI model builders to its platform. As Assisterr continues to expand, the platform's primary objective is to enhance its infrastructure, broaden its support for additional use cases, and onboard the first million SLM-builders to the ecosystem.
About Assisterr.ai
A Cambridge-based startup building a Network of Community-Owned Small Language Models (SLMs). By leveraging the Data Provenance Protocol and providing an end-to-end infrastructure for launching and maintaining community-owned SLMs, Assisterr unlocks the value of aggregating human intelligence.
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