Voyantis

Prediction instead of looking at the conversion

Voyantis was founded in mid-2020 by Ido Weisenberg and Eran Friendinger, according to the founder's account on the company's website. It developed a platform for marketing and growth teams who want to understand which customers are likely to be valuable over their relationship with the business. In a Globes article it is described as an Israeli company with teams in Israel and other markets. The problem the product targets is the gap between a first action, such as signing up or installing, and the revenue and loyalty that become clear later. The company uses the business's data to estimate what comes next, earlier.

The data the model receives

According to Globes, the prediction is based on data the business collected itself, information the user provided, activity and revenue. The system estimates the future value of each customer and updates the prediction along the way. On its current website, Voyantis also lists business preferences, growth goals and limits for optimization. The output is not just a label of a good or weak customer. It is a numerical prediction used to choose audiences and divide marketing resources, along with the context the business defines. The company's description stresses updating according to new behavior, not a one-time estimate. The Globes article notes that the data used for prediction is anonymized. The recommendations for action also include timing, so that each step fits the stage the customer is at.

How the prediction reaches advertising

The company's website describes a process of choosing a model, producing predictions and turning them into signals adapted to each ad network. The signals are passed to systems such as Google, Meta and TikTok to help find customers similar to those the business is expected to gain value from. The company notes that the adaptation includes the form of the signal and when it is delivered. The system receives feedback from the platforms and from actual performance, and recalibrates the signals. In this way the prediction is built into how the campaign runs, instead of staying a report that an analyst has to pass on by hand.

Acquisition and retention with the same approach

In the 2022 launch post, the founder wrote that the predictions can be used to adjust bids, divide budgets and build audiences. According to the company's website, for its customer Klar the method lowered customer acquisition cost (CAC) by 25 percent and raised return on ad spend by 32 percent. A 2025 Globes article also described adding recommendations for actions and incentives into Salesforce and Braze. The company lists customers such as Miro, Rappi and MoneyLion; the launch post also mentioned Notion and Ipsy. The names refer to the date of each source. So the company presents use both in acquiring customers and in actions throughout their life as customers, not only in measuring the number of clicks on an ad.

Funding, and reliance on the business's own data

On 11 February 2025, Globes reported a $41 million raise led by Intel Capital, bringing the total to $60 million. Participating investors included Square Peg, Target Global, Jibe Ventures and Redseed. The company remains private and continues to present an active product. Describing the background to the founding, the founder points to privacy changes that made things harder for marketing teams, and to a shift toward profitable growth. The answer the company presents relies on connecting to the business's internal data and on predictions that keep updating, alongside how the ad networks work.