Quickstart Guide
Start using DeepRails Monitor to observe how users interact with your generative AI application in production, and surface quality issues before they escalate.
Getting started with DeepRails Monitor takes only a few minutes. It involves 3 simple steps:
Create a Monitor
Go to your Krino Console and create a new Monitor for your workflow. Define its purpose and select the Guardrail metrics you want to track. You can also create and manage Monitors using our API.
Integrate DeepRails in your code
Integrate DeepRails into your application using our RESTful API or Python SDK.
Analyze Monitor Activity in Krino Console
Go to the Krino Console to view activity logs for your Monitor. Explore logged runs, quality metrics, and performance patterns directly from the dashboard.
Get started with DeepRails Monitor
Get Access to DeepRails
To get started, you’ll need access to the DeepRails Krino Console and API.
- If your organization already uses DeepRails, ask your admin to invite you.
- If not, create your account or contact our team to get setup with a new account.
Get Your API Key
Visit the Krino Console
Go to your organization’s Krino Console and select API Keys.

Select Create API Key

Give your key a distinct name and click Create Key

Install the DeepRails Client
- Open a Python notebook or any environment where you want to install DeepRails
- Install the python client via
pip install deeprails
- Next, run the following code to setup DeepRails client. Replace
DEEPRAILS_API_KEY
with your API Key.
- Open a Python notebook or any environment where you want to install DeepRails
- Install the python client via
pip install deeprails
- Next, run the following code to setup DeepRails client. Replace
DEEPRAILS_API_KEY
with your API Key.
Create Your Monitor
Go to your Krino Console and create a new Monitor for your workflow. Define its purpose and select the Guardrail metrics you want to track.
Alternatively, you can create a Monitor programmatically using the Python SDK:
Make sure to save the monitor_id
. You’ll need it when logging events associated with this Monitor.
Log Your First Event
After setting up the Monitor, run the following code in your Python environment. Replace the placeholders with your actual data.
Explore Results in Krino Console
Once your evaluations are logged:
- Open your Krino Console
- Navigate to the Monitor you created
- View incoming events and track trends across prompt, model, and metric performance
- Investigate anomalies, regressions, or drops in quality with detailed Guardrail feedback.