Operate  ProcurAiQ · Manufacturing & Industrials · Direct/Indirect Procurement

AI-first procurement intelligence — you decide, the AI does the data heavy-lifting.

ProcurAiQ classifies every line of spend, watches the commodity markets, models should-cost and predicts supplier risk on one Neo4j knowledge graph — then assembles the whole negotiation brief in minutes. The category manager keeps the decision; the AI does the work that used to take days across 35 spreadsheets.

● Deployed & running in the cloudTwelve modules on one knowledge graphDeploy as SaaS or in your own cloud
The problem

Category managers are data-rich, but insight-starved.

Spend lives in ERPs, spreadsheets and email. By the time it's compiled it's stale — so the cheapest invoice often wins, even when it is the most expensive supplier on true cost.

01
Manual spend analysisNo single source of truth — spend is fragmented across ERPs and spreadsheets, and a large share of a category manager's time disappears into gathering and reconciling data instead of negotiating.
02
Volatile commoditiesBy the time price data is found and compiled, the commodity market has already moved — and index-triggered contract reviews quietly pass by unactioned.
03
Opaque should-costPrice-only sourcing ranks on invoice price per tonne and is blind to quality-driven downstream cost — yield loss, campaign-life premiums, slopping, emergency relines — so the cheapest supplier can cost multiples more.
04
Supplier risk found too lateFinancial, ESG and operational supplier problems surface only after they hit the supply chain — not the 6–12 months ahead that would let you act.
How ProcurAiQ works

One disciplined loop, from raw spend to a defensible award.

The Amplinth loop, tuned to procurement — every answer cited back to the graph, every action human-checkpointed.

01

Connect

Ingest ERP transactions, supplier records, commodity indices, contracts & quality data onto a Neo4j graph.

02

Reason

Classify spend, forecast prices, predict supplier failure & trace risk with Neo4j GDS. No black box.

03

Recommend

QATC-adjusted rankings, price-review-eligible contracts & a fully-assembled negotiation brief, with citations.

04

Act

The category manager approves classifications, sets targets, selects suppliers and awards — gate-ruled.

05

Prove

Append-only audit of every AI step; QATC & savings ledger.

Capabilities

Twelve modules, one graph — and a governed agent layer on top.

Category, Spend, Market, Supplier, Cost, Contract, Risk, Simulator, ESG, Quality, Decision and Reporting share one Neo4j substrate and one BFF — so its signature analytic, QATC, propagates across all of them.

Classify spend automatically

The Category service runs a BERT-based classifier that maps every transaction to a multi-level taxonomy, while the Spend service lands a real-time spend cube and flags anomalies, duplicate invoices and off-contract maverick spend — human override always supported.

Monitor commodity markets

The Market service tracks commodity indices and price history, forecasts across 1/3/6/12-month horizons, and raises commodity alerts when a movement crosses a level that should trigger a contract or price review — with news, sentiment and regulatory signals per category.

Model should-cost & QATC true cost

The Cost service builds index-linked should-cost and clean-sheet models, flags quotes above fair price and decomposes the gap. BPID / QATC — Quality-Adjusted Total Cost — exposes the hidden downstream cost price-only tools can't see and re-weights every supplier scorecard around it.

Predict supplier risk on the graph

The Supplier service computes 360° scorecards, scans financial health and ESG daily via D&B / Experian / EcoVadis connectors, and discovers qualified alternatives. Neo4j GDS — PageRank, centrality, shortest-path — traces how a shock propagates and flags single points of failure and concentration risk.

Prepare negotiations end-to-end

The insights service composes an RFQ skeleton, supplier letters, stakeholder memos and a full negotiation pack — assembling market evidence, cost breakdowns, alternatives and contract clauses into one brief, in minutes rather than days.

A grounded, governed AI assistant

A planner with ~40 grounded handlers streams cited, confidence-tiered answers from the tenant's own graph. An ethics guard refuses unethical questions and a no-data guard returns a plain "not available" rather than inventing a number — every step on an append-only audit trail.

Outcomes

The platform is deployed and running — the impact figures are honest about their maturity.

ProcurAiQ's BFF, ~20 services and 12+ micro-frontends are wired and running in the cloud today. The headline impact numbers below are targets or modelled worked cases, not realized client results — and are labelled as such.

5–15%
Procurement cost savings identified
Target · proposal "The Impact"
50%
Sourcing cycle-time reduction
Target · proposal
~10 min
Negotiation-brief assembly vs 2–3 days manual
Modelled · worked example
3.0×
Cheapest invoice supplier's true cost (QATC) — ranking flips #1 → #4
Modelled · worked QATC case
The QATC story
The cheapest supplier on the invoice can be the most expensive on true cost.
In a worked refractory case, QATC decomposed 67% of hidden downstream cost and flipped the ranking from #1 (cheapest invoice) to #4 (true cost). Built on real procurement data plus explicitly simulated production-correlation data — a worked case, not a realized client benchmark. Client anonymised.

Maturity: platform deployment is Realized (verified in code — services, BFF route table and micro-frontends are wired). Savings, cycle-time, classification accuracy and supplier-failure-warning figures are Target or Modelled until a cleared client baseline exists.

Deployment & trust

Connect → Customize → Operate.

Connect ProcurAiQ to your ERP transactions, supplier records, commodity feeds and contracts. Customize the taxonomy, QATC hidden-cost dimensions and scorecard weights to your categories — the platform is reusable; the domain model is what we tailor. Operate the loop in production, where every classified transaction and approved award sharpens the graph.

Neo4j knowledge graphAppend-only audit trailEthics & no-data guardsHuman-in-the-loopRBAC · multi-tenantISO 27001 · target
SaaS
Amplinth SaaS on AWSFully managed — fastest path to value.
VPC
Your own cloud / VPCYour spend, supplier and contract data never leave your control.
Any cloud / regionAzure, GCP, AWS — data residency by default.
Why Amplinth

AI is the preparation. You are the decision.

Industry-deep

QATC / Beyond-Price Intelligence prices suppliers on true total cost — a defensible, manufacturing-specific analytic that generic spend dashboards can't claim, propagated across all twelve modules.

Governed & explainable

A planner with ~40 grounded handlers, citations and confidence tiers, an ethics guard, a no-data guard that refuses to hallucinate numbers, and an append-only AI-step audit trail — governance made concrete in code.

The category manager keeps the decision

Every classification, award and action is human-checkpointed and bounded by co-pilot gate rulesets and approval chains — the right posture for conservative, audit-heavy industrial buyers.

See ProcurAiQ on your hardest category

Price every supplier on true total cost.

Book a demo on a real category — we'll show you the QATC ranking flip, the graph-native risk story, and a negotiation brief assembled in minutes, with the EVA case behind it.