Launching Soon
Copilot Conversational Agent
Turns plain English or Arabic procurement requests into intent, category, supplier, and sourcing actions in one conversational flow.
AI-Native · Built in Qatar · Serving the GCC
Seven AI agents. One procurement brain.
iProcure.ai is building a specialized agentic layer that turns sourcing from a fragmented manual process into one explainable workflow. Each agent owns a distinct job across discovery, activation, execution, negotiation, decisioning, and support.
What the agentic layer delivers
- 7specialized agents in one system
- 2 liveCopilot and data intelligence available now
- 5 buildingtoward a closed-loop workflow
- 1 goalfrom discovery to decision with clarity
Multi Agentic Services
Every agent owns a
specific job
Launching Soon
Data Agent
Continuously enriches supplier, product, category, pricing, and market data so the rest of the platform has trusted intelligence to work from.
Building now
Onboarding Agent
Guides suppliers and buyers through account setup, verification, category mapping, profile readiness, and first-use activation.
Building now
RFQ Generator Agent
Converts requirements into structured RFQs, recommends the best targets, and handles broadcast, reminders, and response tracking.
Building now
Negotiation Agent
Benchmarks offers, suggests trade-offs, and surfaces smarter counter-offer directions without removing buyer control.
Building now
Decision Agent
Ranks responses across price, delivery, fit, risk, and compliance with full rationale and explainable scoring.
Building now
Support Agent
Provides 24/7 bilingual support for onboarding, RFQs, account issues, and supplier or buyer questions across the journey.
Agentic Benefits
Use cases and buyer / supplier outcomes
| Agent | Primary use cases | Benefits for buyers | Benefits for suppliers |
|---|---|---|---|
| Data Agent | Supplier enrichment, category normalization, benchmark signals, product and service mapping | More relevant results, stronger pricing context, faster shortlisting | Better discoverability, better category fit, more relevant RFQ exposure |
| Copilot Conversational Agent | Natural-language sourcing, Arabic + English queries, shortlist creation, draft RFQ prompts | Less training, faster discovery, easier sourcing kickoff | Intent-driven visibility rather than only keyword matching |
| Onboarding Agent | Registration guidance, verification workflows, profile completion, readiness prompts | Cleaner supplier data and faster team activation | Shorter time to go live, lower friction, better profile completeness |
| RFQ Generator Agent | Requirement structuring, RFQ drafting, supplier targeting, reminders, quote tracking | Faster RFQ issuance and better response rates | Clearer briefs, structured requests, more actionable opportunities |
| Negotiation Agent | Benchmark-based trade-off suggestions, commercial scenario support, counter-offer logic | Smarter negotiations with evidence, not guesswork | Clearer negotiation context and stronger commercial positioning |
| Decision Agent | Quote ranking, explainable recommendations, risk flags, rationale for approvals | Faster approvals and stronger auditability | Quality suppliers can win on fit, reliability, and compliance, not only low price |
| Support Agent | Bilingual issue handling, onboarding help, RFQ support, account guidance | Less operational friction and faster help | Better adoption, easier platform participation, quicker resolution |
How the agents works
One sourcing session, multiple agents
1
Copilot understands the request
A buyer describes a need in English or Arabic. The system interprets intent, category, urgency, and commercial context.
2
Data Agent strengthens the match
The network is searched using structured categories, supplier signals, and benchmark data rather than only keyword text.
3
RFQ Generator activates the market
The requirement becomes a structured RFQ, delivered to high-probability suppliers with reminders and response tracking.
4
Negotiation and Decision guide the close
Quotes are benchmarked, ranked, and explained so the buyer can decide with control and confidence.
Why this matters
From fragmented tools to a closed-loop procurement workflow
The platform becomes more useful as supplier data improves, buyer interactions increase, and more RFQs flow through the network. That makes each agent better over time.
- Discovery becomes structured and conversational
- RFQ administration becomes automated and traceable
- Negotiation and ranking become explainable
- Support becomes always-on and bilingual
Reliese Phases
Live now, building next
Launching Soon
Copilot Conversational Agent + Data Agent
These two agents create the current intelligence layer: conversational discovery backed by structured data, supplier enrichment, and benchmark signals.
Building now
Onboarding, RFQ, Negotiation, Decision, and Support Agents
These layers extend the platform from discovery into activation, execution, optimization, decisioning, and always-on assistance.
Closed-loop goal
From requirement to recommendation in one explainable workflow
The end state is a system where buyers describe needs once, suppliers get routed intelligently, and decisions become faster without becoming opaque.