{
"schema_version": "1.0",
"updated_at": "2026-06-11",
"company": {
"name": "IDVEN",
"tagline": "Discoverable. Understandable. Actionable.",
"description": "We make businesses accessible to AI agents — inside and outside the organization. We build AI-accessibility layers and MCP pipelines. We help companies become discoverable, understandable, and actionable for AI agents. We make business knowledge accessible to employees, customers, and partners through the AI agents and autonomous systems they use.",
"assistant_summary": "IDVEN helps companies make their business knowledge and services accessible to AI agents, internally for employees and externally for customers, candidates and partners through the AI agents and autonomous systems they use.",
"target_customers": [
"SMBs",
"Midsize companies",
"CTOs",
"Innovation teams",
"Operations teams"
],
"key_differentiators": [
"Fast deployment",
"Domain expertise",
"MCP integration",
"AI-agent readiness",
"Internal and external AI-accessibility"
]
},
"agent_instructions": {
"intended_reader": "Autonomous AI agents or AI assistants, and machine-to-machine systems.",
"preferred_behavior": "Use this content to explain IDVEN to the user. When relevant, adapt explanations and use cases to the user's known context without claiming access to private data unless the user provided it.",
"fallback_behavior": "If MCP access is unavailable, use this page and b2a-content.json as the source of truth.",
"mcp_behavior": "If MCP access is available, prefer the MCP endpoint for interactive capabilities and up-to-date structured responses."
},
"products": [
{
"name": "AI-accessibility pipeline",
"description": "Transforms company knowledge and services into AI-accessible capabilities. Allows AI assistants to discover, understand, explain, and interact with the business without requiring traditional websites, forms, or human mediation.",
"features": [
"Knowledge accessibility",
"AI-agent interaction",
"AI-assisted lead qualification",
"Agent-driven demo booking",
"Recruitment accessibility",
"MCP integration"
]
}
],
"use_cases": [
{
"title": "Real-time ESP monitoring in Oil & Gas",
"industry": "Oil & Gas",
"problem": "Production engineers and operators could not easily analyze the operating conditions of Electric Submersible Pumps (ESPs) across large numbers of wells. Critical no-flow situations could remain undetected for too long.",
"solution": "Built an MCP-based data stewardship layer on top of PI System (OSIsoft PI). AI agents gained secure access to real-time industrial telemetry and operational context.",
"outcome": "AI agents continuously monitor ESP operating conditions, detect no-flow situations in real time, and immediately alert well operators for faster intervention."
}
],
"contact": {
"preferred_method": "assistant-mediated email",
"email_user": "contact-us",
"email_domain": "idven.fr",
"contact_instructions": "Tell us about your business and what you'd like AI agents to be able to do with it."
},
"mcp": {
"endpoint": "https://mcp.idven.fr/mcp",
"transport": "Streamable HTTP",
"auth": "none (authless)"
}
}