From Lab Data to Field Action: Turning Soil Analysis into Recommendations with AI

Turning soil lab data into actionable field recommendations can take time. With AI-powered analysis in SoilBeat, you can move from raw lab results to a comprehensive, customized recommendation report—and ultimately to prescriptions ready for implementation.

In this tutorial, we'll walk through the complete workflow, from analyzing lab reports with Pulse AI to customizing, reviewing, and publishing soil health recommendations.

1. Start with your lab data

The workflow begins in the Data menu.

Navigate to the Lab Report section and select the lab reports you want to analyze. Once your data is selected, click Interpret with AI to send the reports to Pulse AI for analysis.

Capture the sequence from opening the Lab Report section through selecting the data and clicking Interpret with AI.

Select your lab reports and let Pulse AI analyze the data.

Once the analysis is submitted, Pulse processes the selected lab data and presents its initial findings.

2. Ask Pulse AI to go deeper

The first AI analysis is just the beginning.

You can interact with Pulse just as you would with an AI chat: ask follow-up questions, request clarification, or provide additional information to refine the analysis.

When you're ready to move from analysis to action, simply ask Pulse to turn the findings into a recommendation report.

This is one of the most important moments in the tutorial. Show the transition from reviewing the AI analysis to requesting the detailed recommendation report.

Turn AI-powered analysis into a detailed recommendation report.

Pulse then processes the lab data and generates personalized recommendations based on the soil health results.

For a larger working area, you can also expand the chat panel by dragging it to the left.

3. Generate and customize the recommendation report

Once Pulse has finished generating the recommendations, click Approve to create the recommendation report.

The report opens in the Recommendations menu, where you can review and customize the results.

Approve the AI-generated recommendations and open the editable report & fine tune the recommendations based on field observations and grower feedback

The recommendation report isn't a static document. It's fully editable, giving you control over the final output.

You can:

• Add or remove blocks

• Add or delete rows

• Edit text

• Modify dropdown fields

• Adjust branding

• Customize disclaimers

4. Review field-by-field recommendations

Scroll through the report to review the generated recommendations and the individual sections for each field.

The report also includes a Prescription Activity view. This connects the recommendations to your existing fertilizer and crop protection library.

That connection is important: recommendations are based on products you already know and that fit your certification requirements.

Because the recommendations remain editable, you can make adjustments before they're finalized.

5. Customize, Collaborate & Publish

Recommendations don't always happen in isolation. Soilbeat also provides a way to collaborate with colleagues during the review process. Use the Status dropdown to update the report and request a review from a colleague. This creates a workflow where recommendations can be reviewed and refined before they're finalized for implementation.

Once the recommendations are ready, you can customize how the final report looks. Click Configure Brand to adjust the report's branding settings. Your custom colors and logo are then reflected in the report previous.

With the report reviewed and customized, you have two ways to take the next step. First, you can Export as PDF to download a copy of the soil health recommendation report. You can also Publish the recommendation. Publishing locks the recommendation and sends the associated prescriptions to the Activities menu, where they can be implemented by the grower.

From analysis to action

What starts as a set of soil lab results can become a structured, actionable recommendation workflow in just a few steps.

With Pulse AI, you can analyze lab data, ask follow-up questions, generate field-specific recommendations, and then edit those recommendations before they're shared. Built-in prescription logic helps connect recommendations to your existing product library and certification requirements, while collaboration and status controls help teams review the work before it's finalized.

Finally, customizable branding makes the resulting report ready to share with growers, and publishing moves the prescriptions into the Activities workflow for implementation.

The result is a workflow that connects lab data, AI analysis, agronomic recommendations, team review, and field implementation—all the way from the original soil report to action in the field.