Ultimately, it’s the flexibility that stands out: we can embed the Senzing engine into any solution and within virtually any architecture or cloud platform. Entity Resolution is a crucial foundational capability for solutions that range from traditional master data management and data quality to fraud and financial crime, customer 360 and others - so flexibility of deployment is key. The fact that Senzing is very well documented SDK, we can also easily leverage it using AI Agents, deploy it on any cloud platform, have full control over how to scale it and at a very low market price point.. Finally, from an accuracy point of view, Senzing works virtually right out of the box - we've rarely had to reconfigure any of the inbuilt features and principles. Review collected by and hosted on G2.com.
Until recently, there was a moderate engineering cost to build a solution that utilises Senzing: each data source had to be profiled, cleansed, transformed, and loaded into the Senzing engine. We also had to think carefully about how to build security, scalability, and redundancy into the architecture for each client. Now, AI coding agents are much better versed in working with Senzing, and we can more easily build our own MCP layer to automate a large portion of this work. That makes it extremely quick to onboard new sources. Review collected by and hosted on G2.com.
