This template replaces messy sheets with a structured system to track every quality test, batch result, and product spec. It helps you catch defects early and maintain flawless production standards.
It connects your Products, Batches, and Test Results in a clean, logical flow. When an inspector adds a new test with attached photos, it automatically links to the exact batch and calculates total tests for that specific run.
Managing product inspections in spreadsheets quickly turns into a chaotic mess of broken formulas and disorganized photo attachments. When multiple inspectors update rows simultaneously, data gets overwritten and critical defects easily slip through the cracks.
In a database, your test data is strictly organized and enforced. Dropdowns for defect severity and pass/fail statuses stay consistent without manual data entry errors.
Instead of copying product details across hundreds of rows, you link records instantly. You can easily attach inspection photos and safety sheets directly to the specific batch record.
This clear, relational structure is exactly what Softr Databases are built to handle. Every object—from the inspector to the final batch result—has its own dedicated home.
Log specific test results like visual inspections or pH levels, automatically linking them to the assigned inspector and targeted production batch.
Roll up test metrics instantly to see if a batch should be released or quarantined without writing complex pivot tables. Add AI field actions to automatically summarize inspector notes or analyze defect trends based on incoming test data.
Manage inspectors and managers with roles, contact details and test records
Catalog of manufactured items with specifications, safety sheets and batches
Track specific production runs, release status and aggregate quality checks
Log individual quality checks with defect severity analysis and photo evidence
This template is designed for manufacturing and production teams who need reliable, scalable inspection tracking.
Start by customizing the database to fit your operational standards. You can easily tweak the test type dropdowns or add new columns for specific machinery metrics.
If you already have historical test data, import it via CSV in seconds. You can seamlessly bring in your existing product catalog and past batch records to start fresh immediately.
When your team needs field access, you can build an app directly on top of this structured data. Create a custom portal where inspectors only see the batches assigned to them on shift.
Controlling users and permissions ensures that only managers can approve a batch for release, while inspectors simply log the results. A well-organized database is the perfect foundation for completely tailored internal tools.
A quality control database is a structured system that tracks product inspections, test results, and batch statuses in real time. It ensures all safety checks and defect logs are highly organized, easily searchable, and tightly monitored.
No-code databases give operational teams the flexibility to set up production-ready tracking systems instantly, without relying on developers. They provide strict data structures and reliable automated workflows that are impossible to maintain in fragile spreadsheets.
With the Softr AI Database co-builder, you can quickly generate new test tables or custom filter views just by describing what you need. You can also configure Database AI agents to automatically categorize defect severity or summarize lengthy inspection notes whenever a new test is logged on the line.
Yes, you can easily use Softr's interface builder to create a custom mobile-friendly portal for your floor inspectors. You can set specific permissions so inspectors only log data, while managers see the high-level dashboard of all quarantine or released batches.
Yes, this template is entirely free to copy and start using right away. Databases are included in Softr's free plan, with higher-tier plans offering expanded record limits as your production volume scales.
Spreadsheets force you to cram distinct objects like products, batches, and individual tests into flat rows, causing messy duplication and potential errors. A database uses relational structures, allowing you to link multiple distinct test results perfectly to a single production batch without broken VLOOKUPs.