By developing robust frameworks for multi-agent systems, we’re helping to realize the vision of a society where human-machine collaboration mirrors human-to-human teamwork. Hundreds of institutions have already integrated Emergence’s agents, which proactively solve complex problems, self-teach, and control external tools.
Web automation via a general-purpose LLM and a properly compacted HTML DOM.
Self-improving agents have varying objectives, and the issue of aligning them with human values is critical.
These agents self-teach in pursuit of one predetermined goal.
Our products reverse the relationship between humans & machines and provide a new experience of naturally interacting with technology.
Our open-source projects showcase the capabilities of our specialized agents. Due to our team’s cutting-edge research, these capabilities can be deployed using small-scale, purpose-built language models. They’re leaner, quicker, and more hallucination-resistant than resource-demanding, purpose-agnostic models trained on the entire internet.
Whatever your institution’s mission, Emergence can fundamentally advance the way it works, with white-glove integration of bespoke agent systems. Our researchers and engineers have worked on some of the world's most scalable AI systems, including IBM Watson, Twitter, Alexa, and Amazon Video. Each organization has unique needs, and partnering with us empowers them to develop end-to-end solutions elevating approaches previously considered optimal.
Emergence is committed to creating safe AI and remaining highly transparent. We open source our work in hopes of building far-reaching trust; closed-source projects raise privacy concerns and risk hidden errors. Opportunities to automate will inevitably impact communities, and our team envisions that impact as being universally positive. We’re dedicated to ensuring this technology is properly democratized.
