This template centralizes your vendor assessments, active contracts, and team assignments so you can audit partner reliability without administrative friction.
It connects four dedicated tables: Suppliers, Evaluations, Contracts, and Users. Linking evaluations and agreements directly to specific vendors ensures scoring history and contract terms remain organized in context.
Built-in AI fields automatically draft company descriptions from vendor websites, summarize multi-metric evaluation scores, and categorize contract risk levels.
Google Sheets makes sharing simple, but managing procurement across multiple tabs frequently leads to accidental edits, exposed commercial terms, and fragile cross-sheet lookups.
In a structured database, fields enforce strict rules: dates stay dates, contract values stay currency, and scores remain numerical.
Instead of risky formulas that break whenever a row is moved, tables link directly. Connecting an evaluation score to a vendor instantly updates their profile without manual cross-referencing.
This reliability is exactly what Softr Databases provide out of the box, giving procurement teams a dependable data layer.
Log detailed reviews covering quality, delivery, and pricing while keeping internal notes tied to individual evaluators.
Automate research and risk assessments using native Database AI agents that inspect contract clauses and summarize assessment feedback automatically.
While Softr can also connect an existing Google Sheet, starting directly with this pre-built database eliminates messy spreadsheet maintenance entirely.
Manage procurement staff, system roles, and assigned supplier reviews
Track vendor profiles, contact information, and AI-generated overviews
Record scorecards, performance metrics, and automated AI review summaries
Track legal agreements, values, timelines, and AI-powered risk levels
This template is designed for teams that need consistent, objective oversight of their vendor network:
Customize the database to match your exact review standards. Add custom fields for compliance certifications, modify scoring scales, or adjust risk categories in seconds within the visual editor.
Import your existing data using CSV files to bring your current vendor rosters and historical ratings into the database immediately, or connect external tools via API.
Build a full app around it when your team is ready. You can build an app by describing what you need in one prompt, allowing Softr to generate a custom vendor portal or internal procurement hub on top of this database. Use granular users and permissions to ensure evaluators only edit their assigned reviews while managers oversee all commercial agreements.
A supplier evaluation database is a centralized system used to record vendor information, assess performance metrics, and track contractual agreements. It replaces disconnected files by linking individual evaluations, scores, and contracts directly to specific suppliers.
A no-code database provides immediate structure with typed fields and relational links, preventing accidental data overwrites and broken formulas. It allows procurement teams to deploy a production-ready tracking system quickly without writing custom software.
Integrated Database AI agents can browse vendor websites to write company overviews, compile assessment notes into executive summaries, and analyze contract terms to classify risk levels automatically when records are created or updated.
Yes. You can use Softr's AI app generator to create a tailored interface on top of this data. You can set up custom portals with role-based access so procurement managers review all records while evaluators only see their assigned reviews.
Yes, this template is free to use on Softr. Softr Databases include unlimited collaborators across all plans, with paid tiers available if you need higher record volumes.
While Google Sheets works for basic lists, it lacks granular permissions, strict field typing, and relational links between tabs. A structured database keeps scores, contracts, and vendor profiles connected without fragile lookups or risks of accidental data deletion.
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