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Previse Labs is a modeling company for performance advertising on connected TV.

Advertisers set a budget and a goal. We spend it across streaming inventory, deciding for each impression which ad to run and what to pay for it. Better decisions mean better performance for advertisers and more revenue for publishers on the same inventory.

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Predicted action Four input signals, behavior, content, creative and commerce, feed a single Previse model. The model fans out to three outcomes: purchase, sign-up and install. The sign-up path is highlighted as the predicted outcome. Behavior Content Creative Commerce Purchase Sign-up Install Predicted action Four input signals, behavior, content, creative and commerce, feed a single Previse model. The model fans out to three outcomes: purchase, sign-up and install. The sign-up path is highlighted as the predicted outcome. Behavior Content Creative Commerce Purchase Sign-up Install

Model quality.

Ad platforms all describe themselves as AI-driven now. The quality of the model underneath is what shows up in performance.

Connected TV allows a new ad decision at delivery time. A deep learning model weighing the viewer, the show and the creative has far more to work with than “men in their twenties.”

The team behind Previse has built and operated high-performing ad-delivery infrastructure at the frontier of the field. We are bringing that operating experience to model-driven delivery on connected TV.

US TV advertising is a $100B market.

That is Meta-level scale, and performance budgets have barely touched it. Search and social looked like this once. Handing each decision to a model is what made them work for performance advertisers at all, and raised the value of an impression.

How it works.

You give Previse one outcome and a budget. Deciding where the money goes is the model’s job. It learns from what happens next, so its decisions improve the longer it runs.

  1. Set the goal

    You set a budget and one outcome: purchases, installs, sign-ups or revenue.

  2. Bidding

    Previse bids on each eligible impression at what that outcome is worth.

  3. Matching

    Previse ties the business results that follow back to the ads people saw. That link is the hard part, because the purchase happens later and usually on a different device.

  4. Retraining

    Those results train the next cycle.

For advertisers

Put connected TV to work for customer acquisition.

Delivery is optimized toward the outcome you pick, and a campaign can be judged on the numbers you already track.

US connected-TV ad spend is near $38B in 2026 and growing about 14% a year, with forecasts putting it past traditional TV by 2028 (eMarketer, 2026).

A different audience
Streaming reaches whole households on the main screen, in a moment a feed or a search box never sees. For an advertiser already at scale there, this is the next increment of reach.
Make the full pitch
Full-screen, sound-on creative has room to show the product and explain why it is worth buying.
Talk about a campaign

For publishers

A higher CPM ceiling for connected-TV inventory.

Previse bids in your auction on behalf of advertisers paying for outcomes. The model that finds them a customer is the same one deciding what your impression is worth.

Inventory sold on age and gender is priced on reach. When delivery is guided by the chance of a purchase, one buyer can value an impression far above the rest, and the bidding reflects it. Meta priced on demographics in its early years, and most connected-TV inventory still does.

Talk about inventory

Where things stand.

We are working with a small set of design partners and building the founding engineering and go-to-market team.

See open roles

Let’s talk about performance TV.

Tell us the business result you optimize toward or the connected-TV inventory you manage.

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