Capture more revenue
Improve pricing, targeting, prioritization, and timing with probabilities tuned to each decision.
A new class of predictive AI
The next generation of AI predicts what happens next.
Large Event Models learn from sequences of real-world events to estimate what may happen, when, and with what probability—giving leaders a more rigorous foundation for every high-value decision.
The economic advantage
Better forecasts create better economics.
Every consequential business decision contains a forecast: what customers will buy, where demand will move, which transactions carry risk, when equipment may fail, or how conditions may change.
Even modest improvements can compound across thousands—or millions—of decisions. Large Event Models turn fragmented signals into decision-ready probabilities so you can pursue revenue more precisely, protect margin, and deploy resources where the expected value is highest.
Protect more margin
Anticipate shifts, disruptions, and adverse events before they become expensive.
Allocate with conviction
Put capital, inventory, and attention behind the best probability-weighted opportunities.
Move at machine speed
Bring sub-second predictions into live commercial and operational workflows.
The architecture
LLMs predict language.
LEMs predict events.
Traditional analytics explain the past. Point forecasts choose one answer. Expert intuition can be powerful, but takes decades to build and does not scale. Large Event Models learn the full distribution of possible outcomes from complex event streams.
Large Language Model
What word comes next?
Predictthenexttoken
Learns patterns in sequences of words to generate language.
Large Event Model
What event happens next?
Learns patterns in sequences of events to return calibrated probabilities and uncertainty.
01
→
Learn
Identify patterns across high-dimensional event histories and contextual signals.
02
→
Condition
Evaluate the specific transaction, intervention, or scenario under consideration.
03
→
Predict
Return a calibrated distribution of possible outcomes—not a brittle point estimate.
04
Act
Deliver intelligence through APIs or private infrastructure into existing workflows.
Applications
One architecture.
Many consequential decisions.
Where outcomes unfold over time and historical events contain predictive information, a Large Event Model can create a measurable edge.
Revenue & pricing
Predict purchase, conversion, renewal, and price-response probabilities.
Commercial intelligenceDemand & operations
Forecast demand ranges, capacity needs, delays, and bottlenecks.
Operational leverageSupply chain
Anticipate shortages, late deliveries, inventory imbalances, and disruption.
ResilienceHealthcare
Model patient demand, resource utilization, care-pathway events, and capacity.
Resource precisionInsurance
Quantify claim likelihood, severity, retention, and emerging portfolio risk.
Explicit uncertaintyEnergy
Estimate demand, production, congestion, equipment, and market events.
Dynamic planningRisk, fraud & compliance
Prioritize adverse events, suspicious behavior, failures, and escalation.
Focused attentionYour highest-value decision
Find the repeated judgment where a small predictive edge could generate an outsized return.
Explore it with us →Evidence from the first proving ground
Validated where small errors carry enormous cost.
Our first production application was built for corporate bond pricing—one of the world’s most demanding prediction environments. The result is tangible evidence that Large Event Models can learn complex event dynamics, quantify uncertainty, and deliver fast enough for live decisions.
The architecture is broader than finance. This is the first proof point—not the limit.
44–48%more accurate than a leading incumbent in a 413,000+ trade out-of-sample test
80Mparameters in production
3.3Bparameter model validated
19calibrated percentiles
<1 secAPI inference
Results shown are from a specific corporate-bond evaluation and may not generalize to other datasets or use cases. New applications require independent validation.
How we engage
Start with the decision—not the model.
We identify repeated, high-value decisions where better probabilities could materially improve outcomes, then build the evidence required to act.
Find the leverage
Define the decision, economics, available data, and measurable success criteria.
Prove the edge
Test an initial model against historical data, established baselines, and out-of-sample metrics.
Deploy & compound
Integrate through an API or private environment, then extend the edge across more decisions.
Executive consultation
What would better event prediction be worth to your organization?
If your business makes repeated, high-value decisions under uncertainty, the opportunity may be larger than it appears.
Book a confidential conversation with Nathaniel Powell to identify the decisions, data, and workflows where a Large Event Model could create measurable economic value.
NP
Nathaniel PowellFounder & CEO · 15 years in AI and software engineering
Select a time