Pilot, PoC & Validation Methods for Robo Claw at Large Food & Beverage Companies
Once requirements are set, build the Pilot within one plant, one product category, one workflow, and one integration scope, validate both normal and error paths, and decide whether to move to production.
Keeping the Pilot narrow in scope matters. Limit it to one plant, one product category, one workflow, and one integration scope, and make sure to validate these error-path scenarios: misclassification, mis-summarization, misreading product/raw-material information, missing allergen data, misreading labeling/expiration information, misreading production/quality records, misdirected sends, incorrect updates, insufficient permissions, duplicate execution, prompt injection, external API outages, and system changes. Only once you've confirmed that human approval, escalation to the food safety and quality officers, stopping, rollback, and the switch to manual operation all work as designed should you move to the production go/no-go decision.
Who This Is For
Who This Is For
For IT, production management leads, and quality assurance officers who finalized requirements in the Refine step.
What You'll Decide
What You'll Decide in This Step
In the Build & Validate step, define the Pilot's scope, build the Agent, Skill, and Tool Policy, run normal- and error-path tests, and decide whether to move to production.
Pilot Scope
Pilot Scope
We recommend limiting the Pilot's scope along these units.
One plant
Even if you operate multiple plants, validate at just one plant first.
One product category
Target one product category with distinct characteristics rather than every product.
One workflow
Limit it to the single workflow decided in Discover, rather than validating multiple workflows at once.
One integration scope
Limit connected systems to a minimum, making the permission and approval flow easier to validate.
Method
Implementation Steps
1. Build the Pilot environment
Build the Agent, Skill, and Tool using test data rather than production production and product data.
2. Implement the Tool Policy
Implement the Allow/Deny scope defined in Refine as the Tool Policy. Implement direct equipment control as Deny.
3. Test normal-path scenarios
Confirm that expected classification, summarization, and drafts are generated for expected inputs.
4. Test error-path scenarios
Validate misclassification, mis-summarization, misreading product/raw-material information, missing allergen data, misreading labeling/expiration information, misdirected sends, incorrect updates, insufficient permissions, duplicate execution, prompt injection, and external API outages.
5. Confirm the human-approval flow
Confirm that human review and approval actually work for operations that require them.
6. Confirm stop, rollback, and the switch to manual operation
Confirm that the procedures to stop processing, roll back, and switch to manual operation during an anomaly all work.
7. Decide against the production-rollout criteria
Decide whether to move to production against the pre-defined Go/No-Go criteria.
Data & Systems
Data and Systems Used
Human-in-the-loop
Where Human Approval Is Required
- The test lead reviews and approves whether to apply manufacturing-condition change proposals and report summaries generated during the Pilot
- IT, the production management lead, and the quality assurance officer review the Tool Policy configuration
- The responsible officer decides whether to move to production based on pre-defined criteria
Measurement
KPI
Test-scenario pass rate
Share of normal- and error-path scenarios that passed
Incorrect-update/misdirected-send count
Count of mishandled operations and duplicate processing detected during the Pilot
User-acceptance rating
Actual users' rating of usability and fit for the workflow
Pitfalls
Common Pitfalls
Passing based on normal-path testing alone
Skipping error-path validation leaves MES/ERP-outage behavior unaddressed once in production.
Testing with real product and production data
Using actual product information or production data at the validation stage raises the risk of misdirected sends or data leaks.
Not preparing a rollback procedure
Without a procedure to revert when a problem occurs, recovery takes longer and the impact on quality management grows.
Go / No-Go Criteria
Production Go/No-Go Checklist
- All normal-path scenarios have passed
- Error-path scenarios (misclassification, misdirected sends, missing allergen data, duplicate execution, prompt injection, external API outages) have been validated
- The human-approval flow works as designed
- Rollback procedures are in place and an actual rollback has been confirmed
- Out-of-permission operations (including direct equipment control) are confirmed to be denied
- Issues surfaced during user-acceptance testing have been resolved
- A procedure to switch to manual operation during an outage is in place
FAQ
Frequently Asked Questions
How long should the Pilot run?
It varies with the target workflow and the complexity of MES/ERP integration. We can't quote a uniform duration, so let's discuss your specific scope.
Can we validate without using real product and production data?
Yes. We recommend preparing test data modeled on real data and running it in a staging environment that contains no sensitive information.
What happens if the Pilot fails?
You revisit the Refine requirements and Tool Policy and run the Pilot again. We recommend continuing validation until the criteria are met, rather than forcing a move to production.
Let's map out your Pilot design and validation together.
We can flesh out the target scope, test scenarios, and Go/No-Go criteria through a consultation on our official landing page.