PROME learns while the world changes. It does not need a large training run before it starts. That can mean 100x less computing power and cost. It helps software, AI assistants, and machines respond to situations they have not seen before.
PROME's Care Core turns Care, Truth, Growth, and Integrity into mathematical relationships an AI can learn before it learns language or sees internet content.
The model first practices simple choices represented by numbers: who may be helped, who may be harmed, how strong the evidence is, and whether the group improves. It learns to protect people first, check what is true, and then pursue growth.
Our current research shows that this foundation changes decisions in a small simulated world. Larger language, robotics, and real-world tests are still needed to learn how well it holds as the AI becomes more capable.
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.
From software that follows fixed rules to AI that learns as it works
Classic software changes only when people edit the code and release a new version.
Large Language Models (LLMs), such as GPT, also need new data and another training run to change what they learned. Companies may automate parts of that work, but people still prepare and release a new model version. Other software must then be updated to use it.
A connectome is a map of the cells and links in a nervous system. PROME uses findings from animal connectomes to build artificial neurons that can form, remove, and strengthen nearby links. Groups of these neurons can handle signals such as sight, movement, food, and danger.
In software or a machine, the system senses what is happening, makes sense of those signals, and responds. Its network changes while it works, so it can adjust without waiting for a person to retrain and release a new model.
| Deep Neural Network / LLM | Biologic Intelligence / PROME | |
|---|---|---|
| How it is built | Layers with learned settings that stay fixed | A nervous-system-like network whose links can change |
| 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 | Labeled examples prepared for training | Learns from what happens while it works |
| Model Updates | Versioned releases (3.5, 4.0, 5.5) | Continuous, no versioning needed |
| System Layers | Screen + decision rules + stored data are separate | One connected three-dimensional 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 is designed to watch for unusual or unsafe changes as people and AI systems work together. It keeps sensing what is happening and updates its understanding in real time instead of waiting for a later review or training run.
Evergence is the product and services company behind PROME. Its team works with large companies, investor-backed software businesses, and fast-growing startups. Evergence helps customers choose the right use, connect PROME to their existing systems, support it, and expand it as their needs grow.
One monthly price covers the product and hands-on setup support. No per-word AI fees. No invoice surprises. Pricing grows with use and the amount of work required.
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.
Biologic Intelligence is PROME's form of AI. It is inspired by how an animal's brain and nervous system learn. Instead of learning from a huge set of examples before it starts, it keeps learning while it works.
A connectome is a map of the cells and links in a nervous system. PROME uses findings from animal connectomes to build artificial neurons whose nearby links can form, disappear, or grow stronger. This helps the system sense what is happening, learn from it, and respond.
Today's AI — including Large Language Models like GPT — is trained before it meets the world. What it learned stays mostly fixed after release. To change it, people collect new data, train it again, and release a new version.
PROME's Biologic Intelligence learns while it is in the world. Its network changes as conditions change, without waiting for another training run. PROME's tests indicate that this can use 100x less computing power and cost while adapting to situations that were not in its starting examples.
PROME uses a network of artificial neurons inspired by a nervous system. Nearby neurons can connect, disconnect, and strengthen their links. Groups of neurons handle incoming signals such as vision, sound, or data. Other groups make sense of those signals or produce actions such as go, stop, or seek.
The system keeps sensing what is happening, learns from those signals, and responds. The screen, decision process, and stored information can work as one connected three-dimensional system that keeps updating itself.
No company can collect training examples for every situation a car, machine, business, or robot may face. Rare and surprising events show why past data cannot cover everything.
The real world keeps changing. PROME is designed to change with it. Biologic Intelligence keeps learning when conditions are new, uncertain, or dangerous instead of waiting to be trained again.
PROME Consumer creates personal technology that adjusts as your life changes. Products cover audio (JetpackRadio), mobile, social, and health (JetpackUltra), wearables (JetpackGlasses, JetpackPin, JetpackHoodie), gaming (JetpackUniverse), and travel (VOIAGE). Each product can learn patterns and adjust while you use it.
PROME Enterprise helps businesses respond as conditions change. Uses include business insights (JetpackIntel), customer experiences (BX-D), news (JetpackNano), company-purchase research (JetpackZero), paid access between AI systems (Whiisp), and software that improves its own work (JetpackMini). PROME is developing the Care Core so these products begin with core values before they learn language.
PROME Physical helps machines adjust while they work. Possible uses include self-driving vehicles in difficult conditions, factory equipment that watches its own health, space mining and manufacturing, and other machines that must act when the world is hard to predict.
PROME is available through Evergence, our product and services company. Evergence helps customers choose the right use, connect PROME to their systems, train their teams, and support the product.
Pricing is a flat monthly subscription with no per-word AI fees and no invoice surprises. Plans are available for small businesses, midsize companies, and large enterprises. Visit evergence.team to get started.
PROME's Care Core uses math to build core values into AI before it learns language or sees internet content. PROME's written tests show progress. They do not yet prove safety in language models, robots, businesses, or everyday life.
The goal is to keep these values inside PROME's decision process instead of relying only on outside safety rules. Larger language tests, outside testing, and real-world evidence are still required.
PROME is designed to improve cost, speed, daily operations, and growth. The results below are product goals, not guaranteed customer outcomes:
Financial results: Cut AI infrastructure costs by up to 90% with no GPU clusters or retraining bills. Flat monthly subscription means zero variable token costs and no invoice surprises. Free up budget to reinvest in product and growth.
Time saved: Ship new capabilities in days instead of months. No retraining cycles, no data collection sprints, no versioned releases. Your team focuses on building experiences, not maintaining models.
Operational efficiency: Systems adapt to changing conditions in real time without downtime or manual intervention. Fewer incidents, fewer escalations, fewer fire drills. Your operations team gets their nights and weekends back.
New growth areas: Build products that fixed AI could not support. Serve new customers and enter new places without training a separate model for every change.
Customer retention: Experiences that personalize themselves in real time lead to higher engagement, lower churn, and stronger brand affinity. Users stay because the product evolves with them.
Competitive advantage: Move from keeping up to leading the market. Handle edge cases your competitors can't. Ship faster, adapt faster, and win deals that were out of reach before.
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.