KNIME for AWS Users
Make your AWS AI and data work auditable, governed, and accessible across your organization.
Put AWS data and AI in the hands of the people asking the questions, with a full audit trail
Put AWS data directly in the hands of analysts, domain experts, and compliance teams without writing code
Document every AI pipeline visually so every step is inspectable and auditable
Connect AWS to your full data and AI landscape for a unified view
Why KNIME Workflows for AWS Users
AI workflows you can actually audit
- Document every AI pipeline visually, with inputs, transformations, model calls, and outputs visible at the workflow level
- Walk auditors and regulators through what your AI did and why, step by step
- Meet transparency and documentation obligations under frameworks like the EU AI Act, GDPR, and sector-specific regulations
- Build, deploy, and monitor AI agents with logic that stays visible in the workflow instead of buried in prompt chains
Make AWS data and AI accessible across your organization
- Let analysts, domain experts, and compliance teams build workflows visually, without writing SageMaker notebooks or Glue jobs
- Give data engineers and data scientists the flexibility to code in Python, R, and SQL inside the same workflows
- Package workflows as REST APIs, scheduled automations, or interactive data apps for business users, so requests stop coming back as ad-hoc tickets
- Take pressure off your engineering backlog while keeping every workflow documented and governed by default
One trusted view across AWS and the rest of your data
- Combine data from S3, Redshift, DynamoDB, EMR, and other AWS services with over 300 other connectors, including ERP systems, legacy databases, SaaS APIs, and flat files
- Give every team a consistent view to make decisions from, without forcing all data into one system
- Replace scattered scripts, Lambdas, and notebooks with documented workflows that live in one place
- Cut the time analysts spend reconciling data from separate sources
Choose the best AI model for each job
- Connect natively to AWS Bedrock, along with Anthropic Claude, OpenAI ChatGPT, Google Gemini, Mistral, IBM watsonx, and local models via GPT4All
- Use AWS ML services including Amazon Comprehend, Amazon Personalize, and Amazon Translate inside the same workflows
- Match the model to the task based on performance, procurement rules, legal review, or data residency
- Switch providers as the market or your internal policies evolve, without rebuilding workflows around them
Connect with AWS
KNIME Analytics Platform is such a fantastic end-to-end open source platform, and it enables users to connect almost all AWS services. So the users can quickly build sophisticated, end-to-end production ready workflows in the cloud.
James Yi, Senior Solutions Architect at Amazon Web Services
