Koreo and Kro share a lot of similarities in that both allow you to build abstractions that encapsulate a lot of complexity. For instance, in Kro you could implement a ResourceGraphDefinition that builds a "Workload" abstraction that produces a Workload CRD that, say, lets you specify a container image, a database, and a bucket. Then when you create an instance of this CRD, Kro might map this to a Lambda function, RDS instance, and an S3 bucket, perhaps using ACK for example. In Koreo, this would be a Workflow that has various ResourceFunctions which produce the Lambda, RDS, and S3 bucket. Just like with Kro, this would be triggered off of a CRD. In essence, both let a platform team (or whoever) provide high-level APIs that encapsulate resource management.
One difference is just in how the two approach doing this. Koreo takes an approach of providing primitives that can be composed or reused and, importantly, are actually testable (since testing is a first-class thing in Koreo). This lets you more easily validate automations but also makes it easier to provide "building block" like components that can be shared between Workflows.
Another difference is in how Koreo solves configuration management. Rather than relying on string templating or unstructured YAML overlays, Koreo treats configuration as structured data. This allows you to specify and tweak configurations in a predictable and typesafe way by transforming, validating, and composing them programmatically. Koreo is very much modeled after functional programming principles, so we can, for instance, define functions that validate preconditions or apply standard tags to resources in an environment. This model also enables configuration reuse and overrides across teams and environments without introducing tight coupling or duplication. Instead, we can apply configuration "layers" to build up a resource. Kro really focuses more on resource orchestration and leaves the configuration management up to the user.