Introducing Harpin Native: Identity resolution in your environment
We’ve just made our powerful harpin AI identity resolution solution more accessible than ever!
Traditionally available only through our SaaS platform, you can now use harpin AI tools in a Docker container or via an Amazon Sagemaker Jupyter notebook. Run the harpin code completely inside your own ecosystem so that no data ever leaves the safety of your internal network.
What is identity resolution, and why should you care?
In today’s world, customer data is scattered across multiple systems—CRMs, CDPs, POS platforms, and more. A clustering process is necessary to connect the events for the same customers from different source systems. Historically, a clustering process is quadratic in nature and requires intensive computation, which makes it hard to create accurate, unified customer profiles.
So, what is identity resolution? It’s a comprehensive suite of tools backed by a team of experts—like us at harpin AI. We solve your identity data challenges by using cutting-edge machine learning and AI techniques to:
- Unify profiles across systems
- Clean up customer data
- Eliminate duplicate records
The result? Better customer insights, improved marketing effectiveness, and operational efficiency.
How can you run harpin Native?
With the harpin AI Docker image, you can run harpin AI anywhere you can run a Docker container. Try it out with Docker Desktop on your local machine, spin it up in a cloud-managed container service such as Amazon ECS, or, run it in any Kubernetes cluster. The container has a command line that will walk you through the setup process then read input data in CSV, Avro, or Parquet format. It can even access data in Amazon S3!
We built the harpin AI Amazon SageMaker algorithm to allow data scientists, data engineers, or anyone comfortable working with Jupyter notebooks to easily access the harpin AI toolkit. Simply subscribe to the free algorithm on the AWS Marketplace, then reference the algorithm in your Jupyter notebook. We have examples available on GitHub that you can import directly into Amazon SageMaker to get up and running quickly. Access data in CSV, Avro, or Parquet format stored in Amazon S3.
Whether you’re a data engineer or scientist, our toolkit is built to handle the complexity of modern data environments, securely and at scale. Start exploring today! Test it out in your own environment and see the results for yourself.
Why stop there?
We will continue to iterate on harpin Native in the coming weeks and months, so stay tuned for future updates. We plan to incorporate additional features from the harpin AI toolkit and look at expanding to support additional platforms as well.
If you have any ideas for improvements or additional features that we should consider adding, please reach out to us via the feedback form linked below.
We’d love to hear your feedback, please fill out the form HERE.