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Puma AI is architecting the foundational privacy infrastructure for the generative AI age. Their primary offering is a sophisticated mobile browser that serves as a user-controlled intermediary between individuals and Large Language Model (LLM) providers. Their mission centers on empowering users to discover and utilize emerging crypto protocols and AI models while maintaining a strict "private by design" philosophy. The long-term vision is to establish a "privacy as infrastructure" model where all data flows are exclusively consented, transparent, and auditable.
The company addresses the escalating friction between the undeniable utility of AI and the systemic erosion of data privacy. Their proprietary approach utilizes a multi-modal strategy: executing open-source models (such as LLaMA variants) directly on-device to eliminate data leakage, and providing a comprehensive "Privacy Console" that redacts sensitive identifiers from prompts before they are transmitted to third-party APIs like OpenAI or Anthropic. This solves the critical risks of shadow AI and involuntary data exposure for both individual users and security-conscious professionals.
The platform operates by routing every user prompt through a local, private mediation layer. Users are empowered with three primary execution paths:
The result is a contextually rich yet privacy-hardened response delivered via a browser interface that natively supports Web3 identity (ENS/HNS) and decentralized storage (IPFS).
Founded in 2019, Puma (Puma Technologies) is a remote-first team bolstered by an elite roster of technical luminaries. Notable supporters include Stefan Thomas (Interledger), Jason Warner (ex-GitHub CTO), Illia Polosukhin (NEAR Protocol), and Sridhar Ramaswamy (Snowflake/Neeva). Their organizational culture is deeply rooted in the core values of digital agency, transparency, and rapid iteration.
Puma AI stands as a Category Creator within the nascent AI Privacy Infrastructure space. While traditional privacy browsers focus on blocking trackers, Puma focuses specifically on the prompt lifecycle. They act as a vital Bridge between decentralized technologies and centralized AI powerhouses, serving as a Disruptor to the standard "data-for-access" model that dominates current LLM interfaces.
A mobile browser that acts as the privacy layer between you and LLM providers.
A simple QsP workflow using the Simeoni TG model being presented at ICOP-India 2026
AskPumas paper about evaluating and comparing Large Language Models
Repository for introductory Pumas paper and accompanying code examples
Scripts for reproducing the results of the paper: DeepNLME - Conditional Generative Scientific Machine Learning with applications in Pharmacology
A two-day DeepPumas workshop at PAGE
This is the material for the Pumas Berlin virtual workshop in 2025.
Material for the 2024 DeepPumas workshop at ACoP
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