Connect AI to your Retail systems without losing control
Centralize access, permissions and auditing of each AI integration with your inventory, POS and CRM, without exposing sensitive customer data.A single pane of glass for your entire AI infrastructure
Register the MCP servers that connect your inventory, point-of-sale or CRM systems, and monitor their health from a single place, without depending on configurations scattered by store or system.
What Rootlenses MCP gives your Retail operation
Your AI integrations, working in every store
Monitor the status and connectivity of MCP servers connected to your inventory, POS or CRM, with real-time health checks.
Define who can use each AI tool, and how
Manage users, roles, and API Keys so that only authorized personnel, and the right integrations, access inventory, sales, or customer data.
Your customers' data, processed without leaving your control
Process sensitive transaction and customer information locally, reducing the risk of exposure without sacrificing the automation offered by AI.
Every AI action, with registration and backup
Consult the input, output, status and origin of each execution to audit how the AI interacts with your inventory, your sales or your promotions.
Detect failures before they affect your operation
Monitor the health of your integrations in real time and diagnose connection outages or errors before they impact your stores or sales channels.
Strengthen the security of your Retail data without slowing down your AI adoption
From dispersed integrations to a governed AI infrastructure
Register:
Connect MCP instances to your inventory, POS or CRM using their URL and Master API Key.
Configure:
Define the available tools, their fields, credentials, models and usage limits.
Control:
Generate API Keys and configure users, roles and permissions for each store or team.
Monitor:
Monitor the health of the instances and review each execution from Audit.
Before and after: the impact of automating your recruitment
With MCP
Separately managed servers and credentials in each store
AI Tools without common inventory
Dispersed access between systems
Little visibility on what AI does with your data
Manual diagnosis of integration failures
AI integrations fragmented by system
With MCP
Centralized management of the entire network
Central MCP tools catalog
API Keys, users, roles and defined permissions
Audit with input, output, status and origin
Health checks and instance monitoring
Common layer to connect models, agents, and systems