This Quality Control template helps you track inspections, monitor batch statuses, and manage defect severity securely. It brings your entire manufacturing QA process into a single, structured system without the chaos of spreadsheets.
The database organizes your data into dedicated tables for Products, Batches, and individual Test Results. When an inspector logs a new test—like a pH level or weight check—it connects directly back to the specific production batch automatically.
Tracking critical defect rates and test results in Google Sheets quickly becomes a liability. Rows get accidentally overwritten, test photos get lost in messy cells, and maintaining a clear audit trail as your volume scales is nearly impossible.
Instead of relying on fragile VLOOKUPs to connect a failed test log to a specific production batch, a structured database links everything naturally. One table equals one object, keeping your data entirely organized and app-ready.
Every column enforces strict formatting, meaning pass/fail statuses stay consistent and inspector files are properly logged in attachment fields. This is exactly what Softr Databases are designed for, preventing data contamination on your shop floor.
You can instantly standardize how Test Results are recorded by categorizing them by defect severity natively. Teams can attach photos directly to the record, keeping visual proof tied cleanly to the inspection.
It also allows managers to automatically calculate the total number of quality checks performed on a given batch using simple math rollups. You get a reliable, production-ready QA system from day one.
Manage system users including inspectors and managers with roles and avatars
Maintain details of manufactured items with technical specs and safety sheets
Monitor production runs with release statuses and linked quality check counts
Record detailed inspection outcomes including defect severity and media evidence
This flexible database provides immediate structure for any team managing physical production, lab testing, or manufacturing standards.
You can easily customize this database to fit your exact manufacturing tolerances. Simply edit the select fields to add custom test types, or adjust the defect severity levels to match your internal operational standards.
If you're currently tracking QA data elsewhere, you can seamlessly pull it in. Just upload a CSV to map your existing products and previous batch histories directly into these structured tables instantly.
When your operations grow, you can build an app on top of this data to serve as a secure inspector portal. This gives line workers a clean interface on their tablets to log test results without seeing the entire backend database.
Using granular users and permissions, you can ensure that inspectors only edit their own assigned tests while managers approve final batches. A well-structured database makes launching these custom operational apps completely effortless.
A quality control database is a structured system used to track product inspections, manufacturing batches, and individual test results. It replaces scattered spreadsheets by natively linking specific defects or test outcomes directly to the items being produced.
A no-code database lets production teams build a reliable tracking system instantly without waiting on IT or custom developers. It provides a production-ready infrastructure where field types are strictly enforced, eliminating the data entry errors common in raw spreadsheets.
Managing test results is far more efficient with native AI automation. You can use highly configurable Database AI agents to automatically summarize inspector notes or extract precise defect data into new columns. These agents run directly inside your database natively, processing information the moment an inspector logs a new test.
Yes, you can easily turn this database into a custom portal for your inspectors and floor managers. The application layer connects securely to your data, allowing you to set up specific access controls so field workers only see their assigned batches.
Yes, this template is completely free to copy and start using immediately. Databases are included natively in our free plan to help you get started easily. When your operations expand, higher-tier plans offer increased record limits to support higher production volumes.
Google Sheets lacks strict structure, meaning users can accidentally overwrite critical test results, type text in number fields, or break fragile formulas linking tests to batches. Furthermore, trying to manage attachments like defect photos or safety sheets is incredibly messy in a spreadsheet cell compared to a fully relational database.