InRiva AI
InRiva AI's Glide is an AI-powered operational intelligence platform for supply chain, distribution, and fulfillment operations. It continuously analyzes orders, shipments, inventory, and workflows across existing ERP, OMS, WMS, TMS, and CRM systems to detect emerging risks and recommend next-best actions in approximately 30 seconds, without requiring system replacements.
- Logistics & Supply Chain
- Artificial Intelligence
- Data & Analytics
- Enterprise Software
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
As supply chain and fulfillment operations scale, spreadsheets and manual reviews create blind spots faster than teams can staff against them. The complexity of coordinating orders, shipments, inventory, and workflows across multiple systems outruns available headcount, leaving emerging issues undetected until they reach customers, revenue, or service levels.
Solution
Glide is an AI-powered operational intelligence layer that sits across the systems companies already run on, including ERP, OMS, WMS, TMS, CRM, and data warehouses. It continuously analyzes operational activity in real time to detect risk, surface inefficiency, and recommend the next best action. Emerging issues are classified by severity and business impact so teams can prioritize what matters instead of wading through noise. Recommended actions are routed to the right person in the tools they already use, and every outcome improves future recommendations. Glide is measured by operational outcomes such as risk reduction, speed, cost, and customer experience, not as an AI experiment.
Target Audience
Primary customers are operations leaders in supply chain, distribution, and fulfillment organizations who need to reduce operational risk, improve speed, control costs, and enhance customer experience without adding headcount or replacing existing systems.
Features
- Continuous real-time analysis of orders, shipments, inventory, and workflows across ERP, OMS, WMS, TMS, CRM, and data warehouse systems
- Prioritized risk classification by severity and business impact to focus teams on high-value issues
- Next-best-action recommendations routed to the appropriate person within existing tools
- Learning loop that refines recommendations based on outcomes from every action taken
- Layered architecture that requires no rip-and-replace of existing systems
- Approximately 30-second turnaround from emerging risk detection to prioritized recommendation