Our Core Technology

The NinaData buying intent platform is a real-time contextual data platform for driving in-moment online results for brands.
Using purpose-built AI for semantic analysis of text, video and images, NinaData builds sustainable data value and insights for brands and content owners.

Cutting edge AI

Our solution and methodology center around the shift in focus from Audience targeting to Contextual targeting. For this purpose we have focused on a semantic representation of context and the tools to operate on it. We are especially focusing on capturing the Buying Intent of the content consumer in a way that makes matching against the desired audience segment easy and precise.

NinaData’s platform uses state-of-the-art AI, NLP and finely tuned language models to achieve a high level of understanding of any web page’s intent. This allows the semantic-based platform to optimize the selling of ad inventory by matching URLs to a viewer’s predicted intent based on page-level context. This in turn allows advertisers, ad agencies and marketplaces to precisely target ads with 90+% accuracy without using browser cookies or any other form of personal identifiers. The result is a privacy-friendly, end-to-end platform that provides clients with a publisher-independent web crawler, an application layer, campaign management and an analytics layer.

The Core Features of Our Technology are:

Publisher-independent Crawling

A scalable, robust and protocol-compliant general crawler.


Contextual analytics at the level of individual URLs is much more cost-efficient and precise targeting.

Scalable Multi-linguality

The AI architecture only requires a small amount of fine-tuning for each language.


True automated understanding of the entire content using NLP and Deep Learning AI


A natural way to organize publisher website content into categories in a way that matches the needs of advertisers.


Recognizing the page content intent in a way that matches both publisher intent and the stages of the customer journey, using unique AI.


The process of determining whether the writer's attitude is positive or negative. AI allows this to be done multi-lingually from the entire content of the page.

A Buying Intent Prediction Pipeline

In essence, the platform consists of a pipeline running in the cloud. There are two kinds of input:

1. Online content that is crawled and analysed contextually

2. The targeting needs of a campaign.

The output is a set of contextually analyzed URLs that are of high relevance to the campaign, given the targeting needs.

The system is accessible either platform-to-platform for a continuous real-time setup operating through APIs, or via a graphical self-serve user interface . The UI allows interactive definition of the targeting needs, as well as the downloading of the results -- or their upload to another platform.