Automorphic Analysis: $500K Raised
What is Automorphic?
Automorphic builds infrastructure for self-improving language models and describes its product as models maintaining models. The public site frames deployed model output as training data, but it does not publish detailed technical documentation. The company currently advertises a private beta and direct contact through founders@automorphic.ai.
Location
1105 Penrod Court, Folsom, California, United States
Employees
1-10
Founded
2023
Investors
- Y Combinator
- Ritual Capital
- Red Dog Capital
Product Features & Capabilities
- Conduit, knowledge infusion into language models, efficient fine-tuning, rapid iteration with human-in-the-loop feedback, updates models based on feedback, rapid loading/stacking of fine-tuned adapters, OpenAI API compatible, deploy on-premise in VPC, converts unstructured data into structured formats (JSON, XML, YAML).
Pricing
- Free tier available
- Paid plans starting at $4/month
- Another plan available at $15/month
How much Automorphic raised
1: - $500K
Not specifiedLead Investor: Y Combinator, Ritual Capital
Who are the founders of Automorphic
Market Focus
Automorphic primarily focuses on the artificial intelligence industry, specifically in the development of secure, self-improving language models that enhance knowledge infusion through fine-tuning and human feedback.
Competitors Overview
Automorphic operates in the competitive landscape of custom fine-tuned language models and tools for data structuring. Its main competitors include:
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OpenAI: A leading player in the LLM space, known for its powerful models like GPT-3 and ChatGPT. OpenAI has a significant impact on the market, providing robust APIs and tools for developers. Its advantage lies in its extensive research and development, making it a go-to for many applications.
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Anthropic: Focuses on AI safety and the development of LLMs. They emphasize ethical AI and user-friendly interfaces, which can be a notable advantage for organizations concerned about AI governance.
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Meta (formerly Facebook): Released the open-source LLM, Llama 2, which allows developers to customize and fine-tune models. Their open-source approach provides flexibility and community support, appealing to developers looking for cost-effective solutions.
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Google: A pioneer in the LLM field with models like Bard and PaLM 2. Google’s integration of LLMs into its suite of products offers a seamless experience for users, giving it a competitive edge in accessibility and functionality.
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Microsoft: Develops LLMs integrated into various applications, including Azure AI services. Their strong enterprise focus and integration capabilities provide significant advantages for businesses looking to leverage AI in their operations.
These competitors differ in their focus areas, such as ethical AI, open-source solutions, and integration with existing products, which can influence a developer's choice depending on their specific needs and values.
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