Industry
Industrial manufacturing
Industrial Procurement · AI-native operations
From purchase request to supplier decision, in one controlled workflow
Averon Industries sources from hundreds of European suppliers. NICKSON TECH designed Quorio — a procurement platform where AI reads the documents and people make the call.
Manufacturing · EU
Document AI + human review
Request → RFQ → Award
5 quotes comparedNormalized in minutes, reviewed by a buyer
Market
European Union
Product
Procurement operations platform
Services
Business analysis · Product · Engineering
Focus
Request-to-award workflow
The challenge
Procurement decisions were buried in documents
Averon's procurement teams work across email, spreadsheets, PDFs and a basic PO module. The real cost is not missing software — it is the manual work of turning unstructured supplier documents into a decision someone can defend.
01
Every quote arrives in a different shape
Each supplier structures price, lead time, payment and delivery terms their own way. Specialists re-key them into a comparison spreadsheet by hand.
02
Reading is the bottleneck
Long proposals and contracts are read line by line to find the terms that matter, the deviations, and the information that is missing.
03
Spec compliance is checked manually
Whether an offer actually meets the requested specification is verified by cross-reading two documents — and gaps surface late, forcing rework.
04
Approvals live in email
Routing to category management, finance and compliance happens over email. Status is opaque, and the audit trail is reconstructed after the fact.
The solution
One workflow from request to award
Quorio runs the whole path in one place. AI is embedded where it removes manual effort — reading documents, normalizing quotes, checking specs, flagging risk — while every recommendation stays inspectable and every decision stays with a person.
01
Request
A purchase request opens with its specification attached.
02
RFQ
Suppliers are invited; quotes arrive as PDFs and sheets.
03
Extract
AI reads each document into structured, evidence-linked fields.
04
Compare
Quotes are normalized with spec-match and risk flags.
05
Decide
A cited recommendation; the buyer makes the call.
06
Award & audit
Approvals route by role; the trail is captured, not rebuilt.
Quorio · the product
Every supplier quote, normalized side by side
Price alone is misleading once lead time, Incoterms and payment terms differ. Quorio maps every quote to one model, marks spec compliance and supply risk, and drafts a recommendation — each claim linked back to the source line it came from.
Swipe the screen to explore the full comparison
One comparison model
Totals are currency-normalized, lead times use a common unit, and terms are standardized so the comparison is real, not cosmetic.
Spec & risk, in view
Meets, partial or miss against the requested spec; low, medium or high supply risk — with the reason attached, not implied.
Recommendation with evidence
The AI proposes the strongest balanced option and cites every source, so a buyer can agree, override, or dig in.
Swipe to see the source and extracted fields
Inspectable AI
AI reads the documents. People stay in control.
Nothing enters the comparison automatically. Quorio extracts each quote into structured fields and shows its work, so the buyer confirms before it counts.
- Evidence by default. Every field links to the page and line it came from — one click away from the source.
- Confidence, not certainty. High, medium and low confidence are shown, so attention goes where it is needed.
- Missing information, surfaced early. A missing certificate or unconfirmed coating is flagged before comparison, not after.
- A human checkpoint. The buyer confirms or corrects every field before a quote joins the decision.
Quorio · the product
Leadership sees where value is won or lost
Because every request runs through one workflow, the numbers are a by-product of the work — cycle time, spend by category, and supplier performance, current instead of reconstructed at quarter-end.
Swipe to explore the analytics
On the move
Approvals move with the decision
An award needs finance and compliance sign-off. Instead of chasing email, approvers get the recommendation, the numbers that matter, and a link to the full evidence — wherever they are.
Role-based routing. Category management, finance and compliance approve in sequence, each with the context they need.
The recommendation travels with the request. Amount, spec match and supply risk are on the same screen as the decision.
Every action is recorded. Approvals and holds land straight in the audit trail.
Responsible AI & key decisions
AI you can question
The platform's value is not autonomy — it is judgement, made faster and more defensible. A few decisions kept it that way.
Source
Every AI output points back to the exact document it read.
Confidence
Uncertainty is shown, so review effort goes where it counts.
Human checkpoint
Nothing becomes a record — or an action — without a person.
Audit trail
Who saw what, and why the choice was made, is captured.
Decision 01
AI proposes, the record is human-confirmed
ProblemAutomated extraction is only useful if it can be trusted.
DecisionExtracted values enter as proposals with evidence and confidence; a person promotes them to the record.
WhyKeeps AI genuinely useful while every downstream number stays auditable.
Decision 02
A microservices architecture that scales by domain
ProblemDocument AI, quote comparison and approvals have very different load and release rhythms — coupling them slows delivery and scaling.
DecisionIndependent TypeScript services (document ingestion & extraction, sourcing & comparison, approvals, analytics, audit) communicating over an event-driven message bus, each deployed on its own.
WhyHeavy document-AI processing scales separately from the rest, teams ship services independently, and a fault in one is isolated from the others.
Decision 03
EU data residency by design
ProblemSupplier quotes and contracts are commercially sensitive.
DecisionDocuments and data stay in an EU region; Quorio integrates with the ERP of record rather than replacing it.
WhyRespects data-handling expectations and avoids a risky rip-and-replace.
Decision 04
Deliberately not autonomous agents
ProblemAn agent that negotiates or awards on its own is a liability, not a feature.
DecisionNo auto-award and no silent actions; the platform accelerates the people who are accountable.
WhyProcurement decisions must remain defensible and owned by a person.
Impact
Faster decisions Averon can defend
The platform is designed to change how a sourcing decision is made — less manual assembly, fewer late surprises, and a clear record of why each supplier was chosen.
Minutes
Comparison, not re-keying
Quotes are normalized and compared as they arrive, instead of assembled by hand over days.
Earlier
Gaps surface up front
Missing certificates and spec deviations are flagged before comparison, not discovered mid-decision.
One trail
Audit-ready by default
The reason behind each award is captured as the work happens, not reconstructed later.
Less
Person-dependent
Sourcing knowledge lives in the workflow, so decisions hold up when the expert is away.
Outcomes describe the operational change the platform is designed to create for Averon Industries. Figures shown inside product screens are illustrative demonstration data, not verified client results.
Team & technology
Built by a focused product team
Product & Business Analyst· procurement discovery, product scope1
Solution Architect· data model, AI review flow, integrations1
UX/UI Designer· product design system, workflows1
Frontend Engineers· comparison, review, analytics UI2
Backend Engineers· sourcing, approvals, audit modules2
AI / ML Engineer· document extraction, spec & risk logic1
QA Engineer· workflow & extraction accuracy testing1
Core technology
TypeScriptNext.js / ReactNestJS microservicesPostgreSQLRedisKafka · event busDocument AI + LLM extractionS3 · EU regionSSO / SAMLDocker · Kubernetes · AWS
Delivery approach
1
Discovery & Product Canon. Map the sourcing workflow and fix the shared model before building.
2
Extraction & comparison core. The evidence-linked review and normalized comparison first.
3
Approvals, audit & analytics. Role-based routing, the captured trail, and leadership visibility.
Work with NICKSON TECH
Have an operation buried in documents?
We combine business analysis, product thinking and engineering to turn manual, document-heavy workflows into software people can trust. Let's talk about yours.
or email info@nickson.tech