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New KNIME Release Helps Enterprises Scale GenAI While Reducing Risk

Data workers can now access all latest AI advancements and a customizable suite of controls to manage GenAI risk

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KNIME, one of the leading open-source data science and AI companies, is announcing a new release to help enterprises securely scale their use of GenAI. The new GenAI features allow organizations to access more AI models, govern which AI models are being used by their data science teams, and ensure no leakage of sensitive data.

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“Governing data science processes is – or at least should have been – on people’s radars for years. The risks presented by GenAI are helping people realize that”

The risk factor attached to GenAI is currently one of the most acute blockers to widespread GenAI adoption. Forty-four percent of organizations have already admitted to experiencing negative consequences from GenAI-related risks.And 27% have resorted to simply banning GenAI usage outright to manage that risk.2 GenAI is set to be the transformative technology of our decade and companies are in a race to adopt it. But the fear-based reaction to back away from GenAI is a clear sign that people need tools to manage the risk.

That’s why KNIME’s latest release offers access to the latest and greatest in GenAI technology with a customizable set of internal controls, ranging from dedicated model routing, to PII anonymization, to access management, and more.

With KNIME, companies no longer have to resort to outright bans, but can use GenAI securely and according to their own risk assessment and internal policies. Every company wants to build GenAI into their work, reap efficiencies, and move their pilot projects into production. With this release of KNIME Analytics Platform and KNIME Business Hub, they can do just that.

“Governing data science processes is – or at least should have been – on people’s radars for years. The risks presented by GenAI are helping people realize that,” said Michael Berthold, founder and CEO of KNIME. “KNIME was built from the beginning to help with the continuous, safe deployment of data science processes in mind, so it was straightforward for us to add a customizable set of controls around GenAI. KNIME provides a single environment for data scientists that balances innovation and control by giving data workers access to as much new GenAI functionality as possible while allowing them to control risk by putting the right governance mechanisms in place.”

Now KNIME users can access all the latest GenAI advancements and technologies in KNIME. Users can connect to the latest models from commercial AI providers such as OpenAI, Azure OpenAI Service, and Databricks. They can also access the most recent advancements in local LLMs, such as Llama 3, to work with the latest models on their local machines. They can connect to local and remote Hugging Face Text Embedding Inference servers to access a wide range of open-source embedding models for tasks like semantic search and feature extraction. They can also easily connect to protected Hugging Face Inference Endpoints to quickly spin up many GenAI models for experimentation. Users can now also split documents for retrieval augmented generation (RAG) in a single step to save time.

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KNIME now also provides a GenAI Gateway that allows IT to centrally configure which GenAI providers and nodes can be accessed and used by team members. This centralized management of GenAI providers and models enhances governance and security, allowing IT to control model accessibility in alignment with enterprise policies.

Users can now make working with data and LLMs safe with new Presidio and Giskard integrations. KNIME’s new capabilities based on Microsoft Presidio help protect personally identifiable information (PII) when sharing data with external LLM providers. These capabilities can detect and anonymize sensitive information such as names, phone numbers, and credit card numbers in text data to prevent them being sent out to GenAI tooling, addressing key concerns around data privacy and compliance in GenAI usage. Additionally, a new Giskard-based extension helps users spot issues in end-to-end machine learning workflows and helps them evaluate robustness and bias for more reliable deployments.

This KNIME release allows organizations to confidently productionize their GenAI use cases – with all the latest advancements in GenAI technologies and a comprehensive set of controls to manage risk. All of these features support KNIME’s commitment to making data science and analytics intuitive and accessible to everyone.

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[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

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