Israeli startup 42AI has come out of stealth with $62.5 million in seed funding, saying it is building a “behavioral world model” that can predict what people are likely to do, even in situations they have never faced before. The company is first running its predictive system at financial brokerages, where it says the model can anticipate how individual traders will respond to volatile market conditions, TechCrunch reported on November 2.
“Behavior is not deterministic; it’s constantly probabilistic,” 42AI’s chief executive and co-founder Amit Gal-Or told TechCrunch. His argument is that people carry underlying psychological tendencies that shape their decisions across changing circumstances, and those tendencies can be measured and turned into data a model can work with.
How the model works
42AI tries to infer internal motivations rather than simply extrapolating from past behavior. The company studies how people react to seemingly unrelated events. For a trader, that might mean completing KYC checks, onboarding, support calls, money transfers or actual trading, co-founder and CTO Ehud Ezra said.
“When the person is talking to support or sales in the initial process […] we’re looking at the sentiment, we’re looking at the voice, we’re looking at a lot of interactions that they’re doing, how many times do they call, and so forth,” Ezra said. “And all of those data points are going into the model. Later on, you have the interactions: how you buy and sell, and when, and we’re looking at the market at that stage.”
The observations are converted into mathematical representations of traits and fed into a transformer-based world model that lays out probabilities for possible decisions under different circumstances. A separate language model generates explanations for the predictions. The model is trained to keep a person’s underlying tendencies stable in simulation: if someone is usually risk-averse and the model suddenly treats them as a risk-taker, “the target is off,” Ezra explained.
Three years of data collection
42AI spent three years developing the approach, combining psychological research with neuroscience and genetics, plus advice from psychology and PTSD experts and from Dan Shechtman, the 2011 Nobel laureate in Chemistry. The team first studied thousands of people through psychological assessments and behavioral scenarios, then added government and biobank datasets covering more than 2 million people. Its customer datasets now cover almost 30 million people, Gal-Or said.
In live deployments, the system analyzes customers’ existing records, including transactions and support calls. Gal-Or said the model does not need personally identifiable information, arguing that “the model never knows who the person is.” The company still builds individual behavioral profiles from linked customer activity, a tension the article flags rather than resolves.
What it claims, and its limits
On trading performance, the claims need careful reading. 42AI says its model achieves 98 percent accuracy in predicting market trades, but Gal-Or clarified that this measures whether trading flows fell within a predicted range, not whether each trade was predicted correctly. He also said the model consistently reaches an F1 score of 0.8 to 0.85 for predicting trading direction and volume, a machine-learning metric balancing correct predictions against false alarms and misses.
The founders also volunteered the ceiling. “There’s a natural ceiling because you really don’t have access to everything that a person experiences,” Gal-Or said. Accuracy drops when the system misses important context, such as a trader changing course on a friend’s advice. “A week from now, you might be a different person, but your tendencies will always play out in certain areas to a probability or distribution,” Ezra added.
Business and money
42AI says it works with 10 large brokerages using the model to manage liquidity, margin requirements and hedging exposure, and is generating more than “seven figures” in revenue, though Gal-Or would not specify a number. Customers pay a flat fee or a share of the value the platform helps them capture; he claimed one brokerage generated roughly $30 million in additional value through dynamic hedging.
The $62.5 million seed came from the founders and Infinity Group over three years and was not entirely raised from outside investors. Infinity was founded by Gal-Or’s father, Amir Gal-Or, who is also 42AI’s chairman and a co-founder. The company now plans to raise more. Beyond finance, 42AI is exploring gaming, fraud prevention and cybersecurity, and eventually wants robots and AI agents that understand people, though Ezra acknowledged the model must be retrained on rules and context for each new domain.
Why it matters
Predicting individual behavior from probabilistic traits is one of AI’s oldest ambitions and one of its most fraught. 42AI arrives with unusual credibility markers, Nobel-adjacent advisors, biobank-scale data and paying brokerage customers, and unusual candor about the technique’s limits. The open question, which Ezra himself called “a valid concern,” is what stops a brokerage from using a model of its customers’ psychology against them. The founders pointed to regulations, monitoring and an internal ethics committee, without explaining what, if anything, would actually prevent that.
