Public Sector & Procurement
Tender Documents
Extract requirements, criteria and deadlines from public tender documents to accelerate bid/no-bid and response.
The Challenge
Tender documents are long, multi-file bundles — specification of services, suitability criteria, award criteria, contract conditions and forms — written in formal legal language. Requirements, knockout criteria and weightings are scattered, and deadlines and submission formalities are easy to miss.
Industries
Any supplier bidding to the public sector — IT, software, services, construction, manufacturing.
Who Uses It
Bid managers, sales/pre-sales, legal/compliance, public-sector account teams.
BASE Schema
Contracting authority — Text
Procedure type — Enumeration (open, restricted, negotiated, competitive dialogue, innovation partnership)
Threshold / estimated value — Number
Submission deadline — Date
Suitability criteria — Table
Award criteria & weighting — Table
Mandatory documents (EEE, certificates) — Table
Contract terms (EVB-IT etc.) — Text
Bidder-question deadline — Date
Recommended pipeline settings — Checkbox detection, Context (internal bid/no-bid criteria)
OPTIONAL Validation
Deadline and formalia completeness; knockout-criteria check vs. own capabilities; weighting sums to 100%; mandatory-document checklist; flag potentially rügewürdige clauses.
Frequently ASked Questions
How can AI help analyse public tender documents?
It extracts the requirements, suitability and award criteria, deadlines and mandatory documents into a structured compliance matrix, so bid teams decide and respond far faster.
Can document AI build a compliance matrix from a specification of services?
Yes — each requirement is captured and traceable, forming the backbone of a bid-by-criterion compliance matrix.
How does tender-document automation improve bid/no-bid decisions?
By surfacing knockout criteria, deadlines and weightings instantly, it lets lean teams qualify opportunities in minutes instead of days.
See more use cases.
Get inspired by further sample data schemas.