5 Steps to Getting Started with Domo.AI and Amazon Bedrock
With Domo’s intuitive data tools and Amazon Bedrock’s AI capabilities, you can ask questions, build custom workflows, and create detailed reports—all while ensuring your data remains secure and scalable.
When data is the backbone of your business, finding fast and effective ways to turn that data into insights is crucial. That’s where the partnership between Domo and Amazon Web Services (AWS) shines.
With Domo’s intuitive data tools and Amazon Bedrock’s AI capabilities, you can ask questions, build custom workflows, and create detailed reports—all while ensuring your data remains secure and scalable. Our partnership helps your team make more confident and thoughtful decisions driven by data.
Just looking for a quick guide to getting started with Domo.AI and Amazon Bedrock? Jump ahead to our five-step process shown below.
How Domo and Amazon Bedrock elevate your AI capabilities
Domo.AI, powered by Amazon Bedrock, blends flexibility and security. Together, they allow businesses to explore data by using AI without the usual technical roadblocks. With the Domo AI Service Layer and Amazon Bedrock’s foundation models, you can choose the right AI tool for the job—whether answering questions, generating reports, or building automations.
Here’s why Domo chose Amazon Bedrock:
Model choice: Amazon Bedrock allows Domo to select and use various models such as Anthropic, AI21 Labs, Cohere, Meta, or Stability AI. This variety means we can pick the best model for each task, optimizing performance for every use case.
Security, compliance, and global infrastructure: With Amazon Bedrock, Domo makes sure data stays within the AWS hosting environment. We stop model providers from accessing or training on customer data. AWS also provides enterprise-grade security and compliance, safeguarding your data as your teams use generative AI tools.
Cost efficiency: Amazon Bedrock provides Domo serverless access to high-quality large language models (LLMs). This means Domo can experiment with and test various AI models—without the hefty price tag usually linked to implementing and maintaining LLMs. As a result, we can better allocate our resources and make our operations even more efficient.
Getting started with Domo.AI and Amazon Bedrock in 5 simple steps
Unlocking the power of AI in your organization might be easier than you think. We pulled together five simple steps to get you started with Domo.AI and Amazon Bedrock.
If you’d like to explore the solution’s architecture and data flow, you can check out our co-written article on the AWS Machine Learning blog.
Now, let’s take a look at how to get you up and running:
1. Check your permissions
First, we want to make sure your user role has the appropriate permissions to create or modify Amazon Bedrock resources. AWS requires permissions to access Amazon Bedrock models, so confirm that your identity-based policies are set up correctly.
2. Explore Amazon Bedrock models
Amazon Bedrock lets you access a variety of high-performing foundation models from top providers like AI21 Labs, Anthropic, Cohere, and Stability AI. To get started:
- Head to the Amazon Bedrock Console.
- Choose Model Access from the navigation pane.
- Review the end-user licensing agreement (EULA).
- Enable the models you’d like to use in your account.
3. Start experimenting
You have a few ways to interact with Amazon Bedrock models, depending on your setup:
- Use the Amazon Bedrock console to explore models in a playground environment.
- Programmatically access models using the Amazon Bedrock API and SDKs.
- Use the Amazon Bedrock Command Line Interface (CLI) for command-line access.
The console is clear and straightforward, making it easy for most users to get started. You can test models, ask questions, and see how they perform with your data.
4. Integrate with Domo.AI
Once you’ve selected your models and you’re ready to go, it’s time to integrate them into Domo.AI through the AI Service Layer. With this integration, your team can produce AI-powered insights within Domo’s platform—which makes taking action more manageable and less cumbersome.
Here are a few examples of actions you can take:
- Build AI-powered workflows that allow your team to ask your data questions in everyday language without needing to know code.
- Implement custom AI applications for department-specific purposes, such as generating financial forecasts or predicting likely customer behavior.
- Set up automated reports to communicate AI-powered insights across your organization.
5. Measure and analyze performance
You’ll want to track your models’ performance as your teams start using Domo.AI with Amazon Bedrock. You can monitor key metrics in Domo’s AI Service Layer, including cost, speed, and accuracy. Knowing these metrics can help you fine-tune your AI applications and ensure they deliver the desired results without wasting resources.
Want to dig into the technical details?
For those who want more technical details, be sure to check out the blog we co-wrote with AWS, Exploring Data Using AI Chat at Domo with Amazon Bedrock. You’ll get a comprehensive look at how the Domo.AI and Amazon Bedrock solution works and deeper insight into how our technologies complement each other.
If you want to get the full technical breakdown and explore the partnership in action, read the full AWS blog here. Understanding how this collaboration can bring value to your organization’s data strategy is the perfect next step.