case study

AI-driven “Content intelligence” platform adds native Marketing Automation integrations - iPaaS for SaaS

About is an embedded integration platform for SaaS companies. helps AI companies to add a wide range of integrations to their platform. These integrations can either capture data from multiple data sources (cloud applications) to feed the AI engine, or they can send results from the AI platform to other cloud applications. Since AI relies heavily on data, these integrations are a key element of the AI solution.

About the customer

The customer is a fast-growing SaaS company based in the USA that developed an innovative AI solution to analyze and optimize online content strategies.

The integration challenge

The company applies AI on the campaign data coming from marketing automation platforms such as Salesforce, Hubspot, Marketo, Eloqua, etc. in order to optimize the content strategy of their customers.

The company was looking for a solution to quickly add a wide range of out-of-the-box integrations to their platform without the need for custom development.

“Classic” custom development turned out to be very costly, hard to maintain, and impossible to customize for individual customers. Further more, their development team had limited knowledge on the destination platforms, and they did not have readily available test accounts which significantly delayed the creation of the integrations. Therefore the company decided to work with for all its integrations.

martech integration

Integration use case and requirements

The AI platform needs to extract campaign data from various sources (marketing automation platforms) in order to analyse these campaigns. The data consists of a time series of metrics (page views, clicks, interactions per content piece etc.), and these metrics are normalized before being analyzed. The requirements provided to were:

 Support for the top marketing automation platforms

 Ease of use – integration can be activated with a few clicks by end-customers (marketing managers)

Seamless integration in the UI of the AI platform

Near real-time sync of new data

How the integrations were built on

The integrations were created and published using the platform in 4 steps.

Step 1: and the AI platform worked out the detailed requirements of the integrations together, as well as the datamodel.

Step 2: The first integration templates were created by, and handed over to the customer success team of the AI company. Next, the customer success team started building new integration using

Step 3: Test environments were provided by

Step 4: Integrations go live. Lead time: 4 to 6 weeks.

Integration activation per end-customer

The SaaS company applies the “self-service delivery model”. This means that end-customers activate integrations themselves with just a few clicks. This is accomplished thanks to the deep embedding of the integrations, inside the UI of the AI platform.

Who does what



7-9 months lead time saved by building integrations with instead of doing “classic” development

The SaaS customer closed new deals because their AI platform now supports most marketing automation platforms used by their customers

 Increased customers’ satisfaction