AI becomes more valuable as workflow data grows — response times, delivery reliability, project readiness, and operational patterns. Aarvi monetizes software intelligence, not confidential customer data resale. Insights use Aarvi transaction data or explicitly integrated customer data.
AarvI AI
Contextual guidance across commerce and operations workflows — helping teams ask better questions and move from signal to next action.
Ask Aarvi works with the capabilities your organization enabled. It recommends paths and drafts — humans still publish RFQs, award suppliers, and issue POs.
- In-workflow assistance for buyers and operators
- Prioritization support without inventing facts
- Works with the capabilities your organization enabled
Supplier intelligence
Compare suppliers using performance signals grounded in platform activity — response time, delivery reliability, and related indicators when available.
Scores are never invented. When data is thin, Aarvi says so — rather than manufacturing confidence.
- Based on Aarvi activity or integrated data — never invented scores
- Supports sourcing decisions alongside price and lead time
- Premium intelligence as organizations deepen usage
Project intelligence
Surface procurement bottlenecks, material readiness risk, and coordination gaps across multi-supplier projects.
EPCs and owners see where categories are late across partners — grounded in orders and shipments, not a dashboard of placeholders.
- Material readiness and delivery risk context
- Help EPCs and owners see cross-supplier status
- Complements project delivery tracking
Operations analytics
Portfolio health, availability, and trends when Connected Operations is enabled — assisting investigation without replacing SCADA analytics.
Optional by design. When an issue needs parts, intelligence can point back to warranty, inventory, contracts, or suppliers on the same network.
- Optional — tied to connected sites and alerts
- Complements OEM and SCADA tooling
- Can connect operational need back to commerce
How it works
- Step 1
Run real workflows
RFQs, orders, projects, and optional ops create the context AI needs.
- Step 2
Ground insights in activity
Use platform and integrated data — never fabricated supplier scores.
- Step 3
Assist decisions
Help teams compare, prioritize, and act — humans remain in control.
- Step 4
Protect privacy
Network effect does not mean sharing confidential customer data.