Kraków, Poland-based Synerise, an AI-first behavioural data platform, announced that it has raised $23M (approximately €21.90M) in a Series B round of funding led by Carpathian Partners, a CEE-focused technology investment fund.
The round included a primary capital raise and a secondary share acquisition, and was joined by several prominent business angels.
The proceeds from this round will help Synerise expand in the US market and to continue investing in the company’s deep-tech behavioural data processing, AI & process automation platform.
About Carpathian Partners
Carpathian Partners is a late-VC and early-growth-equity investment platform that provides expansion capital to technology-driven companies originating in CEE and targeting global markets. The firm is founded and led by seasoned private equity professionals with a track record of over $2B of capital deployed across 20 investments.
Cezary Pietrasik, co-founder and Venture Partner at Carpathian Partners, says, “The depth of the Synerise product is astounding. Even the biggest software firms in the US do not have such an elegant, unified, and highly-performant solution. We believe that the combination of unique scientific prowess of the platform, thoughtful go-to-market approach, and solid funding will allow Synerise to build a huge business in America. We plan to scale the company quickly in the US.”
Pietrasik will become the new President of Synerise’s US business with a mandate to lead the company’s expansion in North America.
About Synerise
Founded in 2013 by Jaroslaw Krolewski, Krzysztof Kochmański, and Miłosz Baluś, Synerise is a B2B SaaS platform that allows its clients to store and process all their heterogeneous data and automate data-related processes with the support of an AI and a no-code/low-code interface.
The company supports its corporate clients in e-commerce, retail, telecom, financial services, and automotive industries across 30 EMEA markets in collecting and analysing data about customers, users, objects, their behavioural & environmental context, delivering actionable analytics and insights, and deployment of data-based decisions into live use-cases.
Synerise has 150+ team members operating out of offices in Warsaw, Krakow (Poland), and San Francisco (US).
The vision of Synerise
Synerise claims to address key challenges of modern behavioural data operations by combining real-time heterogeneous data collection and analytics, with automated and AI-enhanced decisions and instant use case implementation/deployment into live business scenarios.
The company’s proposition stands in contrast to how enterprises tend to work with behavioural big data. These often include expensive technology stacks with multiple disparate systems and applications from multiple vendors. The result is a chaotic system architecture, data silos, security risks, and excessive human resources required to staff these operations. Consequently, enterprise data ecosystems rarely operate in real-time, despite low latency claims from individual point-solution vendors. Synerise is solving these problems.
According to a statement, the company’s platform provides one environment where most enterprise business processes can be managed. Some of the many use-cases possible through Synerise include individualised product recommendations, content management, loyalty systems, marketing automation, predictive analytics, scoring & propensity models, churn prevention, NPS measurement, fraud prevention, pricing optimisation, and hyper-segmentation, all working across the web, mobile apps or even physical channels (eg., a PoS).
Real-time execution, within under a second from the triggering event, through data queries, analytics, decisions, and automated deployment, is possible due to the speed of Synerise’s proprietary database technology, Terrarium, claims the company.
Jarosław Królewski, CEO and co-founder of Synerise, says, “Our vision is to always be in real-time mode, no matter how much data you need to process. We have created, from scratch, a column & row-oriented real-time behavioural database engine for heterogeneous multi-modal data ingestion, which powers our platform. It enables the daily handling of billions of requests responsible for enterprise-level decisions, without any pre-aggregations or dividing data into hot and cold storage for separate analytical and transactional operations. This gives us an advantage in building effective out-of-the-box AI models with self-optimisation.”
