Emergence is committed to creating AI responsibly.

In order to build a society that can place trust in intelligent agents to perform sensitive tasks, we must ensure our technology is transparent, reliably safe, and secure.

PRINCIPLES

We strive to develop systems that minimize harm and risk.

Our context-aware Appropriateness model.

The HELM (Holistic Evaluation of Language Models) benchmark, created by Stanford University's Center for Research on Foundation Models (CRFM), is a robust framework introduced to assess appropriateness-determining language models. Emergence’s appropriateness-determining model achieved top performance against HELM metrics.

Mar 17, 2024

Emergence’s Appropriateness Evaluation Model

The high accuracy and precision of our model represent a new achievement in reliably identifying unsuitable prompts and biased datasets.

SECURITY

Security and privacy are our top priorities.

Emergence is fully SOC-2 compliant and adheres to the NIST Cybersecurity Framework. We’re dedicated to creating means by which AI can positively impact even highly sensitive or regulated domains.

We maintain consistent and stringent practices:

  • Red Teaming

    Simulating potential threats to identify
    vulnerabilities.

  • Data Privacy

    Implementing privacy-by-design, data minimization, encryption and other strong privacy measures.

  • 3rd Party Risk Assessment

    Simulating potential threats to identify
    vulnerabilities.

  • Data Security

    Safeguarding sensitive data within AI workloads, adhering to privacy regulations, and preventing data breaches.

  • AI Security Posture Management

    Implementing strategies to secure AI applications throughout their lifecycle, from development to deployment.

  • Continuous Monitoring

    Utilizing tools with periodic human-in-the-loop validation and monitoring.

COMMUNITY

Transparent and community-minded.

We work closely with the open source community. Two of our most advanced agents are open-source, in an effort to ensure any developer may contribute to the growing Emergence ecosystem. Our self-improving agents benefit from widespread use, and by virtue of this powerful technology being in the hands of the public, it is safeguarded against hidden errors or privacy concerns.

RELIABILITY

Purpose-built and beneficial.

  • We use a walled garden model for grounded responses (RAG).

  • We use the right model size for right tasks.

  • We train LLMs to be hallucination-resistant.

  • We identify domain-specific workflows.

  • We do rigorous testing and validation.

  • We maintain a high level of configurability.

CAREERS

Come join Emergence.

There’s a place here for all those interested in emergent systems and the future of AI. Come work in one of our offices in New York, Irvine, Spain, or India, or join us remotely.