Our algorithm adapts in real time as the world around it changes, with no up-front training required. That means 100x less compute and cost. We help you self-drive your software systems in a more trustworthy, reliable, and fail-safe way, working together with classic software, LLMs, and our proprietary biologic intelligence.
PROME's biologic intelligence is built with foundational concepts like Care embedded directly into the model architecture — not bolted on as an afterthought or a safety filter layered on top.
Just as a living organism has deeply ingrained instincts that prevent it from harming itself or others, PROME's connectome-based system carries core values that guide every decision in real-time. These values act as a protective harness: they help prevent runaway AI, block machines from doing harm to themselves and others, and ensure that adaptation never comes at the cost of safety.
Because these values are structural — woven into the neural connections themselves — they cannot be bypassed, fine-tuned away, or overwritten. They are part of the intelligence, not a constraint placed upon it.
The next quantum leap in AI and Robotics — beyond today's state-of-the-art LLMs, extending their capabilities into new territories.
No pre-training. 100x less compute and cost. Real-time intelligence that adapts as the world changes.
Today's AI is trained before it meets the world. PROME learns while it is in the world.
The core difference is not merely efficiency. It is when and how intelligence is created. No pre-training → 100x less compute → 100x lower cost. Real-time learning → real-time adaptation.
You can't train for the real world. The real world changes. PROME changes with it.
No pre-training means no massive GPU clusters. PROME runs on off-the-shelf hardware.
1% of the compute means 1% of the cost. The economic advantage is structural, not incremental.
Classic software doesn't change unless a human physically goes in and changes the code by typing new characters on a keyboard or deleting existing lines from the code base. Every update is a manual, versioned release.
Large Language Models (LLMs) do not change unless a human goes in and collects new data by hand, updates training instructions by hand, and then runs new training sessions by hand. The industry is attempting to automate this entire process, but it still represents a versioned software release (e.g., OpenAI 3.5, 4.0, 5.5). Then classic software integrates with these LLMs by hand and releases versions of their software products (e.g., Apple's iOS 27 with Siri Intelligence).
Our scientists collect information about animal connectomes from a laboratory setting and mimic the nervous system connections — the number of neurons, the connections between them, the strength of each neural connection, and the ability to connect or disconnect from other neurons. Clusters of these neurons represent vision, smell, movement, food, danger, and more.
When placed into a software or robotics system, it detects the world around it using these sensory mechanisms, makes sense of it using its cortical processing features, and then reacts much like muscles do to the changing environment. This biologic intelligence changes its model architecture in real-time in response to its environment without any human intervention.
| Deep Neural Network / LLM | Biologic Intelligence / PROME | |
|---|---|---|
| Architecture | Layered, frozen weights | Connectome, dynamic connections |
| Learning | Pre-trained offline | Real-time, in the world |
| Adaptation | Retrain when things change | Adapts automatically as things change |
| Connections | Fixed after training | Connect, disconnect, strengthen in real-time |
| Training Data | Supervised, annotated examples | Unsupervised, learns without examples |
| Model Updates | Versioned releases (3.5, 4.0, 5.5) | Continuous, no versioning needed |
| System Layers | UI + Logic + Database (separate) | Collapsed into one interconnected 3D system |
| Compute | Massive GPU clusters | Off-the-shelf hardware |
| Cost | High | 1% of the cost |
| Human Intervention | Required for every update | None — self-updating |
PROME's protective harness safeguards businesses and people from runaway AI by detecting anomalies even when systems continue to vary inside a company or household. It does it by continually sensing and updating its model architecture in real-time as the dynamics of the interactions occur between people and AI agents.
Evergence is the product and services company behind PROME, with deep relationships across Fortune 1000 enterprises, private equity-backed software companies, and high-growth startups. Evergence handles go-to-market, implementation, and forward-deployed engineering — ensuring PROME's biologic intelligence is integrated, supported, and scaled across every customer environment.
A flat monthly subscription covering product access and forward-deployed implementation services. Zero variable token costs. No invoice surprises. Pricing scales with usage and complexity.
For small and midsize businesses getting started with adaptive intelligence. Core product access with standard implementation support.
For growing companies with multi-team deployments. Expanded product access, dedicated implementation engineering, and priority support.
For Fortune 1000 and complex enterprise environments. Full product access, forward-deployed engineering teams, custom integrations, and SLA-backed support.
With three decades of hands-on experience, Sean has built product and service businesses, driving billions of dollars in shareholder returns. His expertise spans corporate development, strategy, and product development-driven growth, making him a trusted partner for boards and management teams alike.
Sean specializes in transforming businesses using emerging tech solutions that enable defensible growth, streamline operations, and create sustainable economic advantages. He primarily works for the Fortune 500, mid-market Private Equity-backed companies, and high-growth startups.
Sean has an MBA from Chicago Booth and a BS in Mathematics & Actuarial Science from the University of Iowa.
Tim has been building artificial neurons for over three decades. He co-founded the OpenWorm project and was the first person to mimic an animal's biologic intelligence into real-world robotics. In addition to his emerging tech experience, he has decades of experience managing enterprise IT environments and teams at planetary scale, including permissions, security, and 24x7x265 uptime. For example, Tim managed a Fortune 25 company's global IT infrastructure and budget.
After 10 years of pure Research & Development into Biologic Intelligence, combining insights in computer science, mathematics, biology and robotics, PROME is ready for commercial use.
Tim has a BS in Computer Science, with a minor in Psychobiology, from the University of California Riverside.