Our technology.

From gathering data, to extracting insights and using them in our AI models – discover the uniqueness of our approach.

Your passport to
revenue growth.

Our unique understanding of businesses lets us accurately predict the likelihood of businesses buying from another, their value to each other, and the best messaging to use.


Unlike many vendors, we don’t buy-in 3rd party data. We create it ourselves from open-source, unstructured data on the web. Because we own the entire data supply chain, we can build new signals to meet any need, across any geography.

Tackling data scarcity.

99% of the world’s private companies are small businesses. But most company data is only captured for the larger enterprises because of their significantly greater digital footprint.


You can detect that Microsoft is looking into predictive analytics by linking content consumption to IP addresses. But you cannot detect if a 5-employee plumbing business is looking to buy a vehicle tracking software for their vans. Traditional company attributes fail to explain the nuanced reasons why SMEs buy from one another and intent data is non-existent.

Giving data meaning.

Adzact ingests raw, unstructured data from millions of sources including text, imagery and code. Most of the data is just noise – it’s unorganized and useless to a human being because it’s hard to derive meaning from.



We apply artificial intelligence to organize and classify data into – highly unique and hard-to-replicate – signals. Whilst we have given the data meaning in the form of signals, it’s still not useful for marketers. There’s too much of it and it’s hard to know what’s predictive and what isn’t.

Recognizing buying patterns
with Machine Learning.

Machine Learning allows us to recognize patterns between our signals and a customers’ wins and losses and other conversion metrics. The patterns form the basis for predictions of likelihood to buy and engage, potential customer value, and messaging pointers.

The advantages of
full-stack data science.

Our customers love the predictive power of Adzact’s AI models, but it wouldn’t be possible without owning every part of the process. Because we own the full-stack data science process, we can:

Build new signals from scratch where traditional data
providers are limited to existing data.

Better predict buyer fit and value resulting in up to 5x better conversions
and higher deal value.

Better match businesses to their online identities enabling cross-platform activation.

What does Full-stack Data
Science look like in practice?

Whilst one signal is never indicative of whether a business will buy, it’s useful in
illustrating how full-stack data science works.


Plumbing Company Inc. has images on their ‘About Us’ page of their website.


Business that have bought vehicle tracking solutions also display similar images (along with a combination of other signals).


The images are classified as showing company vehicles. 


98,000 other businesses display similar patterns. These are the ones most likely to click on an ad, have a positive decision-maker conversation and buy from you. They’re prioritized by likelihood to buy from high to low.

Join hundreds of sales and marketing leaders
driving growth with Adzact.

Transform the way you go to market.