AI procurement software that reads every bid before you do
Describe what you need and VEXORS drafts the request. Publish it and AI matches the right suppliers. When bids land, every one is scored with written reasoning and an award recommendation. You stay the decision-maker, with the reading done.
No card to start. Your first request goes out in minutes.
- Free to start, no card
- Your data stays yours
- Suppliers respond free
What is AI procurement software?
AI procurement software applies machine intelligence to the slow parts of sourcing: writing the request, finding the right suppliers, and evaluating the bids. On VEXORS, AI drafts a structured RFQ, RFP or RFI from a plain-language brief, matches suppliers to your request by meaning rather than keyword, then scores every submitted bid against the specification: price, compliance, method, and certifications, with the reasoning written out and an award recommendation attached. The decision stays yours; the reading, ranking, and first draft do not.
Drafting that starts from a sentence
Tell the drafter what you are buying in plain language and get back a structured request (line items, terms, questionnaire) ready to edit rather than a blank form. Pre-publish insights flag gaps before suppliers ever see them.
Scoring with the reasoning written out
Fifty bids evaluated, compared and scored in seconds, on the specification, the method, and the certifications, not just the price. Every score comes with written reasoning and an award recommendation you can challenge before you decide.
Matching by meaning, not keywords
Semantic matching reads what your request actually asks for and surfaces suppliers whose real capabilities fit (including ones you have never worked with), so discovery is not limited to whoever you already know.
How AI procurement actually works on VEXORS
From a brief to a structured request
Most requests start as a sentence, not a specification. Tell the drafter what you need to buy, in plain language, and it returns a real request object: line items with quantities and units, commercial terms, and a supplier questionnaire, sized to an RFQ, RFP, or RFI. You edit and approve every field before anything goes out; the AI produces a first draft, never a published request. For a construction package, the same drafting step can start from an imported BoQ, so a plain brief and a spreadsheet both land in the same structured shape.
- Drafts structured RFQs, RFPs, and RFIs from a plain-language brief
- Sizes the questionnaire and terms to the request type automatically
- Starts from an imported BoQ for construction packages, not just a brief
- Nothing publishes until you review and approve every field
What the AI reads, step by step
Everything starts from structure. When you brief the drafter in plain language, it produces a real request object (line items with quantities and units, commercial terms, a supplier questionnaire), not a paragraph of suggestions. You edit and approve; nothing publishes itself. Before publishing, pre-publish insights read the request the way a skeptical supplier would and flag what is missing: an ambiguous specification, a deadline that contradicts the delivery date, a questionnaire that never asks about the certification your terms demand.
- Flags gaps in your request before you publish it
- Checks BoQ quantities and units against the line item description
- Compares your questionnaire against the certifications your terms actually require
- Catches a deadline that contradicts the delivery date before bidders see it
Finding suppliers who were never on your list
Most invitations still go to whoever the team already knows, which caps competition at the size of a contact list. Semantic matching reads what the request actually asks for (the trade, the specification, the certifications) and ranks suppliers by fit rather than by a matching keyword, so a request for fire-rated cable tray surfaces a certified fabricator even if the word 'cable' never appears in their profile. Matches include suppliers already in your own list and ones you have never worked with, each shown with why it matched, so the decision to invite stays yours.
- Matches suppliers to requests semantically, beyond keyword search
- Ranks matches by fit to the specification, not by profile keywords
- Surfaces suppliers outside your existing list alongside your own
- Shows why each supplier matched before you decide who to invite
A quality check before the bid is even sent
Every bid a subcontractor or supplier submits on VEXORS can be checked before it goes in, not after. The Bid Quality Coach reads the draft bid against the request and flags what must be fixed: a required questionnaire answer left blank, a section delivery date missing, a price entered against a line with no quantity, a currency that does not match the request. It also flags what to confirm: a line priced at zero or left unbid, an answer too thin to score well, or a tender amended since the bid was last saved. A check costs 2 AI credits; re-checking an unchanged bid is free, so a supplier can fix and recheck until the bid is actually ready.
- Must-fix flags: missing required answers, a blank delivery date, a price with no quantity
- Confirm flags: zero-priced lines, thin answers, a tender amended since saving
- 2 AI credits a check; re-checking an unchanged bid costs nothing
- Runs before submission, so fewer bids arrive with gaps to level
Levelled, scored, and recommended, with the reasons attached
Before any bid is ranked, items a bidder left unpriced are counted and priced back in at your estimate or the median of the other bids, so a bid that looks cheapest on the day it lands does not win by default. On every item with at least three prices, each rate is checked against the median of the rest, and a rate far out of line is flagged with its ratio. The AI then scores every bid against your commercial and technical criteria, at the weights you set, with the reasoning written beside each score, and recommends an award with its reasons stated. The award itself stays a human decision, with named approvals on the record.
- Scores every bid with written reasoning and a recommendation
- Answers questions across submitted bids with AI-generated insights
- Summarizes your spend into plain-language narratives
- Rate check flags an outlier price against the median before you award
Why the reasoning holds up
None of this is a black box. Here is what makes the scores stable, and where the human stays in charge.
Then it reads the bids the same way
When bids arrive, the scoring engine reads each one against that same structure: every line priced or not, terms accepted or deviated, each questionnaire answer, each certification claim. Because every bid answers the same request, the AI is comparing answers, not guessing at intent across five differently-formatted documents. That structural grounding is why the scores are stable and why the written reasoning can cite specifics instead of vibes.
The time math that justifies the category
Consider what evaluation costs without it. A sourcing manager reading eight real bids (pricing sheets, method statements, questionnaire answers) spends the better part of a week extracting, normalizing, and tabulating before any actual judgment happens. Most of that week is not decision-making; it is data entry performed on other people's formatting choices. It is also where transcription errors enter the record silently, at the exact point where accuracy matters most.
On VEXORS the extraction step does not exist (bids arrive structured), and the reading pass runs in seconds regardless of bid count. Fifty bids get the same depth of reading as five, which changes behavior upstream: teams stop capping invitations at three suppliers because evaluation effort no longer scales with participation. More competition per request, at zero marginal reading cost, is the quiet compounding benefit.
Governance: what the AI is not allowed to do
The award is a human act, always. The AI recommends and states its reasons; you can reject the recommendation, and both the recommendation and your decision live on the timestamped record. This is a design position, not a limitation: accountability for spending money cannot be delegated to a model. The AI genuinely does not know what you know: the off-platform history, the strategic context, the thing that went wrong with a supplier in March.
Cost governance is equally explicit. AI usage draws on plan credits (every tier includes them, every tier can top up), so there is no surprise invoice and no separate 'AI module' to license. And because every AI output is written to the record alongside the human decision, an auditor can always distinguish what the machine suggested from what the buyer decided.
Manual sourcing vs AI-assisted sourcing
Writing the request
- Manual process
- Blank document, hours, copied from the last one
- VEXORS
- AI draft from a plain-language brief, minutes to edit
Finding suppliers
- Manual process
- Whoever the team already knows
- VEXORS
- Known list + semantic matching across the network
Reading the bids
- Manual process
- Days of extraction into a spreadsheet
- VEXORS
- Seconds, scored with written reasoning per bid
Comparing
- Manual process
- Hand-built table, transcription errors
- VEXORS
- Side-by-side comparison built from structured bids
Deciding
- Manual process
- Gut feel dressed as diligence
- VEXORS
- Recommendation with stated reasons; you decide
Defending it later
- Manual process
- Reconstructing emails months after
- VEXORS
- Timestamped record of every step, one click
Checking the BoQ before you publish
- Manual process
- Sent as drafted, gaps found by bidders' questions
- VEXORS
- Pre-publish insights flag gaps before anyone bids
Catching a bad bid before submission
- Manual process
- Found during evaluation, or not at all
- VEXORS
- Bid Quality Coach flags it before the supplier sends it
Who gets the most out of it
Lean procurement teams
One or two people carrying real purchase volume. The AI absorbs the reading and drafting load that otherwise caps how many requests a small team can run properly.
Operations and finance leaders
Owners of spend without a procurement department. Drafting from a brief and scored comparisons make professional sourcing possible without hiring for it.
High-bid-volume categories
Construction packages, trading, MRO: anywhere ten-plus bids per request is normal and evaluation effort was the bottleneck on competition.
Audit-heavy environments
Teams answering to boards, clients, or regulators. Every AI output and human decision is on the record, so the paper trail writes itself.
AI at every step, you at the wheel
Brief the drafter
Describe the need in plain language. The AI drafts the structured request; you refine and approve it.
Publish and match
Invite your own suppliers and let semantic matching surface new ones that fit the request.
Score every bid
Each bid gets a score, written reasoning, and a comparison against the rest, in seconds, not afternoons.
Decide with a recommendation
Review the award recommendation and its reasons, award, and rate the supplier to strengthen the network.
Importing a BoQ, splitting it into trade packages, levelling bids against it and technical questionnaires are part of the Scale plan. Drafting, supplier matching and AI evaluation of RFQs, RFPs and RFIs run on every plan, with the AI credits each plan includes.
AI procurement software FAQ
Get the free RFQ/RFP/RFI template
A reusable sourcing template for RFQ, RFP, and RFI requests, with line items, evaluation criteria, and supplier instructions. Enter your email and download it.
Go deeper on the AI layer
- Bid evaluation softwareThe evaluation layer on its own: identical-scope comparison, AI scores, and the defensible award record.
- How AI bid scoring worksA plain-language walkthrough of what the scoring reads, how it ranks, and where the reasoning comes from.
- Every VEXORS featureThe full platform tour: requests, bids, awards, trust scores, and the AI woven through all of it.
- Plans and AI creditsEvery plan ships with AI credits from day one. See what Explore, Grow, and Scale include, and what a top-up costs.