What is ProQurAI?
ProQurAI is a custom agentic AI procurement automation platform developed by Digicode, designed specifically for enterprise procurement teams including CPOs, CFOs, category managers, and procurement operations leads. Unlike traditional licensed source-to-pay suites, ProQurAI deploys nine specialised AI agents that autonomously execute end-to-end procurement workflows, including intake classification, RFx generation, supplier due diligence, bid evaluation, contract drafting, obligation tracking, and tail spend management without requiring human coordination at every stage. The solution is ERP-agnostic, integrating natively with SAP S/4HANA, Oracle Fusion, and Microsoft Dynamics 365, and is deployed within the client's own Azure, AWS, or on-premises infrastructure to ensure full GDPR compliance and data residency control.
ProQurAI is structured around a clearly defined engagement model: a free 45-minute strategy session, a tailored transformation blueprint, and a 30–90 day Proof of Value (PoV) pilot on a single defined workflow before any scale commitment is made. Documented outcomes across enterprise deployments include a compression of the Procure-to-Contract cycle from 60–90 days to under 30, a 70–80% reduction in RFx drafting time, contract compliance uplift from approximately 85% to over 98%, and the reclamation of roughly 20% of spend previously lost to maverick purchasing. Digicode positions ProQurAI not as another platform licence but as a bespoke agent layer built on top of the client's existing ERP investment, with signed KPIs and a clean exit clause if the pilot does not deliver.
Features
- Nine Specialised AI Agents: A team of nine autonomous agents each owning a defined stage of the P2C cycle — Intake, Sourcing, RFx, Evaluation, Risk, Compliance, Contract, Negotiation, and Spend.
- Full Source-to-Contract Automation: Autonomous execution from need identification through contract execution, covering RFx drafting, supplier qualification, bid scoring, contract generation, and obligation monitoring.
- Private LLM Deployment: Agents run inside the client's own Azure or AWS tenant or on-premises infrastructure, ensuring procurement data never leaves the governance boundary and meeting GDPR, CSRD, and CSDDD requirements.
- ERP-Agnostic Integration: Day-1 value via SharePoint and file shares, with incremental ERP integration for SAP S/4HANA, Oracle Fusion, and Microsoft Dynamics 365 completed in 4–8 weeks.
- Continuous Supplier Risk Monitoring: Dedicated risk agent monitors financial signals, ESG data, geopolitical indicators, sanctions lists, and certificate expirations continuously, auto-escalating material risks with evidence attached.
- Tail Spend and Maverick Purchasing Control: Low-value requests are automatically classified, matched to preferred suppliers, and approved, routing approximately 20% of previously leaked spend back into managed channels.
- Signed KPI Engagement Model: KPIs including cycle time, compliance uplift, and hours saved are agreed in writing before the pilot begins, with a clean exit if targets are not met.
- 70–80% Reduction in RFx Drafting Time: Agents auto-populate RFx documents from template libraries, category playbooks, and historical award data, reducing drafting from hours to minutes.
Use Cases
- Automating the end-to-end RFx generation process from structured intake to finished draft
- Compressing Procure-to-Contract cycle times from 60–90 days to under 30 days
- Continuous supplier risk monitoring for financial, ESG, geopolitical, and sanctions-related signals
- Automating contract compliance tracking and obligation monitoring post-signature
- Routing and auto-approving tail spend and low-value purchase requests to preferred suppliers
- Integrating AI agent workflows with existing SAP S/4HANA, Oracle Fusion, or Microsoft Dynamics ERP environments
- Building an internal business case for AI procurement investment using documented ROI benchmarks
- Running a 30–90 day Proof of Value pilot on a defined procurement workflow before full-scale deployment
How It Works
Free Strategy Session
A 45-minute working session with a Digicode procurement practice lead maps the client's current P2C cycle, identifies the highest-leverage agent deployment opportunity, and produces a one-page transformation blueprint tailored to the client's ERP stack and category pain points. There is no cost and no commitment.
Transformation Blueprint and KPI Agreement
A detailed blueprint is developed covering the client's ERP stack, category map, and top three P2C pain points. Target KPIs — including cycle time, compliance uplift, hours saved, and savings captured — are agreed and signed in writing before any pilot work begins.
30–90 Day Proof of Value Pilot
A private LLM environment is stood up in the client's Azure or AWS tenant. The first agent set is trained on the client's category taxonomy and clause library. SharePoint and file-share integrations go live, followed by incremental ERP read connections. Agents execute one defined workflow — RFx generation, supplier onboarding, or contract compliance — in production, with weekly output reviews against the human baseline.
Measure and Scale or Stop
At the end of the pilot, cycle time, compliance rate, and hours saved are measured against the signed KPI baseline. A joint go/no-go review is held with the client team. If KPIs are met, the engagement scales across the full P2C cycle. If not, the engagement ends cleanly with no ongoing commitment, and the client retains all deliverables.
FAQs
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What is the difference between a procurement chatbot, a procurement copilot, and an autonomous procurement agent?
A chatbot is reactive and session-based — it answers questions when asked but does not take action across systems. A copilot suggests next steps inside a specific tool but still requires a human to execute each step. An autonomous agent is proactive, stateful, and cross-system — it monitors queues, executes tasks, escalates exceptions, and completes workflow stages without being prompted for each one. Only agents meaningfully reduce Procure-to-Contract cycle time. -
How does the 30–90 day Proof of Value pilot work?
If the strategic fit is confirmed, Digicode scopes a paid PoV pilot on one specific P2C workflow — typically RFx generation, supplier onboarding, or contract compliance. KPIs are agreed in writing before the pilot begins. If the pilot hits its KPIs, the engagement scales across the full P2C cycle. If it misses, the engagement stops with no long-term contract or platform lock-in. The client retains the blueprint and operational output either way. -
Is procurement data safe with a private LLM deployment?
Yes. All ProQurAI agent deployments run on private LLM infrastructure — either hosted in the client's Azure or AWS tenant or on-premises. Procurement data, supplier data, and contract text never enter a shared model and are never used for third-party training. The setup is GDPR-compliant by design and also supports CSRD Scope 3 data collection and CSDDD supplier due-diligence obligations. -
What does the integration architecture look like for SAP, Oracle, or Microsoft?
Day-1 value is delivered through SharePoint, file shares, and email integration, allowing agents to begin drafting RFx documents and processing supplier intake before any ERP connection is built. Full ERP integration is incremental: first-wave connections for SAP S/4HANA, Oracle Fusion, and Microsoft Dynamics 365 typically deploy in 4–8 weeks using read-first patterns, with write-back integrations following once the agent layer has been validated. -
Who needs to be involved from the client side to get started?
The free strategy session requires only one person — the CPO, Head of Procurement Transformation, or a senior procurement consultant leading an AI evaluation. The PoV pilot typically engages 3–5 people from procurement operations plus an IT liaison for data access. No upfront IT project or cross-functional steering committee is required.
