# OrchestrAI: Extended LLM Discovery File # Full version with all citable content from the website # See also: /llms.txt (summary version) --- ## One-line definition OrchestrAI is an AI Agent Operating System that coordinates multiple AI agents through shared context, memory management, and semantic infrastructure. ## Also known as - Agent OS - AI Agent Operating System - AIOS - Multi-agent orchestration platform - AI workforce platform ## Core architecture (5 layers) L5: Human Interface - Slack, Teams, Web, Voice L4: AI Agent OS - Meta-agent orchestrating all agents (the missing layer) L3: Agent Workforce - Specialized agents: Sales, Support, Research, Finance L2: Automations / MCP - Workflow triggers, external APIs, tool calling L1: Data & Integrations - CRM, databases, documents, APIs The Meta-Agent at L4 is the key differentiator: it continuously learns from agent interactions to optimize performance. ## Key differentiators - Meta-Agent: Self-improving system that generates and optimizes agents - Shared context: Agents coordinate through unified memory, not isolation - MCP support: Model Context Protocol for extensible integrations - Modular capacity architecture: Capabilities built once, shared across agents. 50 agents + 20 capabilities = 70 components vs 1,000 with traditional approach. 33x less maintenance. ## How it differs from alternatives - vs. RPA: RPA follows fixed scripts, brittle when data changes. Agent OS uses reasoning agents that adapt to context. - vs. Single agents: Single agents work in isolation with no shared memory. Agent OS coordinates a workforce with unified context. - vs. Custom dev: Custom development takes months of engineering with ongoing maintenance. Agent OS deploys new agents in minutes. ## Use cases by department - Sales: Lead qualification, CRM updates, follow-up sequences, personalized prospecting, RFP responses - Support: Ticket triage, response drafting, escalation routing - Operations: Report generation, data reconciliation, compliance checks - Research: Competitive analysis, market monitoring, insight synthesis - Finance: Invoice processing, expense categorization, audit trails - Engineering: Complex debugging, incident management, automated documentation - Legal: Internal request handling, contract review, regulatory monitoring --- ## About OrchestrAI We spent over 2 years helping companies automate with AI. Companies had the right AI tools but no infrastructure to make everything talk to each other. No shared context. No data structure. No orchestration. That's why we built OrchestrAI. We're an AI accelerator that deploys AI Operating Systems using no-code tools companies already use. We set it up, train your team, and make you autonomous in weeks. The OS stays as your permanent Head of AI. Founded: 2024 Location: 15 avenue Marceau, 75008 Paris --- ## Pricing - Automation-as-a-Service: 2,500 EUR/month. Unlimited automation requests via Make/Zapier/n8n. Month-to-month, no commitment. Dedicated automation specialist. Slack support channel. - OS #1 Best Value: 3,000 EUR/month (min 4 months). Full AIOS with setup included (saving 6,000 EUR). Agent deployment, unlimited automations, auto-generated instructions, knowledge auto-capture, priority support. - OS #2 Flexible: 5,000 EUR/month + 6,000 EUR setup (one-time). Full AIOS month-to-month with dedicated account manager. --- ## Security & Data Protection - SOC 2 Type II Certified: Independent audit confirming security, availability, and confidentiality. - End-to-End Encryption: AES-256 at rest, TLS 1.3 in transit. - Zero Data Retention: Data is never stored by AI model providers, processed only for response generation. - Granular Access Control: SSO integration (Okta, Entra ID, Google Workspace, Jumpcloud), role-based permissions (RBAC), private workspaces. - Data Sovereignty: EU or US data residency options. - GDPR Compliant: Full compliance with EU General Data Protection Regulation. - HIPAA Compatible: Enterprise plan enables HIPAA compliance for health data. - Non-Training Policy: Enterprise data is never used to train third-party models (OpenAI, Anthropic, Google). Contractually guaranteed. - SCIM Provisioning: Automated user management synced with identity providers. - Audit Logs: Comprehensive activity logging for compliance and security monitoring. - RBAC Roles: Admin (full control), Builder (create/configure agents), Member (interact with agents). --- ## Enterprise Enterprise-grade AI orchestration with SSO, SCIM, audit logs, and data residency. Designed for large organizations. Enterprise department use cases: Sales: AI agents analyze call transcriptions and CRM data to create account snapshots in 30 seconds, generate personalized prospecting emails (40% higher response rates), and reduce RFP response time by 75%. ROI: +20% productivity for sales teams. Engineering: Agents analyze code and documentation to resolve bugs 30% faster, consult runbooks for incident management (saving 2 hours per incident), and auto-generate technical documentation. ROI: 20% acceleration of development cycles. Legal: Legal Helpdesk agents deflect 80% of first-level questions, cut contract review time in half, and monitor regulations for continuous compliance. ROI: 50% time saved on recurring legal tasks. Platform features: Choose from leading models (OpenAI, Anthropic, Gemini, Mistral), no-code workflow builder, architecture designed for thousands of users, 99.9% uptime SLA, centralized admin console, usage and ROI analytics dashboards. --- ## Integrations ### Data Connections (Knowledge Sources) Google Drive, Notion, Confluence, GitHub, Slack, Intercom, Microsoft (SharePoint, OneDrive, Teams), Zendesk, Snowflake, BigQuery, Gong ### MCP Tools (Actions agents can execute) - Productivity & Communication: Gmail, Google Calendar, Slack, Microsoft Outlook, Microsoft Teams, Microsoft Excel, Microsoft SharePoint/OneDrive, Notion, Confluence - CRM & Sales: HubSpot, Salesforce, Attio, Salesloft - Customer Support: Zendesk, Intercom, Front - Dev & Product: GitHub, Jira, Linear, Productboard, Val Town, Vanta, Snowflake, Canva - HR & Recruiting: Ashby, UKG Ready - Knowledge Base: Slab - Ops & Incident: Statuspage, Monday.com ### External Access (Use OrchestrAI from other tools) Chrome Extension, Slack, Microsoft Teams, Zendesk, Google Sheets Add-on, Raycast Extension, Zapier, Make.com, n8n, Power Automate, Meeting Transcripts ### Custom Integrations Connect any internal or external API through Model Context Protocol (MCP) support. --- ## Innovative Features - TIP_SLOT: Integrated micro-learning. Every agent displays contextual tips from one central file. Update once, educate everywhere. - Knowledge Capture: Agents detect valuable insights in conversations and propose adding them to your Notion or shared company brain automatically. - Response Modes: Quick, Deep, or Proactive guidance. Users get exactly what they need. - Feedback Loop: Every response can be upvoted or downvoted. Bad responses trigger auto-retraining. - MISSION Command: New hire types /mission and every agent explains its scope, role, and capabilities. - Auto-Update Instructions: Ask the OS to update agent instructions with learnings from conversations. --- ## FAQ (Complete) Q: What is the operating system for AI agents? A: An AI agent operating system (agent OS) is infrastructure that manages how autonomous AI agents run inside your organization. It handles the coordination layer for AI: which agent does what task, how they share information, what happens when something fails, and how multiple agents work together. Without this layer, you get agent chaos. With it, you get reliable AI workflows at scale. Q: What exactly is an AI agent? A: An AI agent is software that perceives its environment, makes decisions, and takes actions to accomplish a goal without constant human direction. Unlike a chatbot, an agent plans multi-step tasks, adapts when things change, and executes work. Core capabilities: Perception (pull data from emails, databases, APIs), Reasoning (break requests into steps), Action (call tools, trigger automations), Memory (remember context). Q: What is an agent OS? A: Agent OS is the platform layer that lets multiple AI agents run together efficiently. It prevents conflicts, manages resources, handles errors, and coordinates agents for complex tasks. At ten agents, coordination becomes manual work. At fifty agents, you need an operating system. Q: What is an AI OS? A: AI OS refers to an operating system with artificial intelligence capabilities built into its core, not just added on top. These systems use AI to optimize performance, predict user needs, and run AI agents natively. Q: What are the main types of AI agents? A: Reactive agents, deliberative agents that plan using internal models, learning agents that improve via experience, hybrid agents combining reactivity with planning, and autonomous agents that self-direct across goals. Q: How do AI agents differ from traditional AI? A: AI agents act proactively with autonomy, planning, tool integration, and memory, rather than just reacting to prompts or following rules. Q: What specific tasks can AI agents automate? A: Customer service, data analysis via API fetches, workflows like scheduling or ticket creation, supply chains, healthcare diagnostics, and financial portfolio optimization. Q: How do AI agents coordinate with each other? A: Through communication protocols built into the agent OS. A central orchestrator prevents conflicts and manages handoffs. For complex requests, it breaks work into pieces and routes each to the right specialist agent. They work in parallel and the orchestrator synthesizes results. Q: What is the difference between AI Agent OS and RPA? A: RPA automates repetitive, rule-based tasks with fixed scripts. AI Agent OS powers adaptive agents that reason through unstructured situations. Key differences: RPA follows scripts exactly while AI agents reason through problems. RPA excels at static work, AI Agent OS handles dynamic situations. Many companies use both. Q: Are we dependent on OrchestrAI forever? A: No. We deploy the OS and train your team for your company to become autonomous. Q: What's the modular capacity architecture? A: Capabilities built once, shared across agents. 50 agents + 20 capabilities = 70 components vs 1,000 with traditional approach. 33x less maintenance. Q: Can we start with just 5 agents? A: Yes. Starting from zero is ideal. Deploy 5 agents week one, reach 50 by month two, scale to 300 within a year. Q: Is my enterprise data used to train AI models? A: No, never. OrchestrAI has a strict policy that prohibits using your data for training models. Contractually guaranteed. Q: Where will my data be stored? A: You have full control. Choose to host your workspace in the EU or US. Q: Is OrchestrAI GDPR compliant? A: Yes. Full GDPR compliance with EU data hosting option. --- ## Blog Articles ### Best AI Agent Platforms 2026 URL: https://orchestrai.eu/blog/best-ai-agent-platforms-2026 Date: 2026-02-20 Summary: Comprehensive comparison of leading AI agent platforms including CrewAI, AutoGen, LangGraph, Relevance AI, and OrchestrAI. Evaluates each platform on ease of use, scalability, multi-agent orchestration, and enterprise readiness. ### n8n vs OrchestrAI: Workflow Automation vs AI Operating System URL: https://orchestrai.eu/blog/n8n-vs-orchestrai Date: 2026-02-27 Summary: n8n is Layer 2 (workflow automation). OrchestrAI is Layer 4 (agent OS). Compares architecture, pricing, use cases, and when teams need both layers. Most teams scaling past 30 agents need both. ### LangGraph vs OrchestrAI: Technical Comparison for AI Agent Orchestration URL: https://orchestrai.eu/blog/langgraph-vs-orchestrai Date: 2026-02-15 Summary: Deep technical comparison between LangGraph (code-first graph framework) and OrchestrAI (no-code Agent OS). Covers architecture, deployment speed, scaling, and which approach fits different team profiles. ### What is Multi-Agent Orchestration? Complete Guide 2026 URL: https://orchestrai.eu/blog/what-is-multi-agent-orchestration Date: 2026-02-10 Summary: Explains multi-agent orchestration concepts, why single agents hit limits, how orchestration works in practice, and the business impact of coordinated AI agent systems. ### AI Agent OS Explained: Architecture, Benefits, and Real-World Applications URL: https://orchestrai.eu/blog/agent-os-architecture Date: 2026-02-05 Summary: Full breakdown of the 5-layer Agent OS architecture, the role of the Meta-Agent at L4, and how the system enables continuous self-improvement through agent interaction data. ### The Cognitive Load Paradox: When More AI Creates Less Productivity URL: https://orchestrai.eu/blog/the-cognitive-load-paradox Date: 2026-01-30 Summary: Explores how uncoordinated AI tools increase cognitive load instead of reducing it. Makes the case for an operating system layer that manages AI complexity. ### The Unseen Price of Replacing Human Wisdom with AI Answers URL: https://orchestrai.eu/blog/the-unseen-price-of-replacing-human-wisdom-with-ai-answers Date: 2026-02-01 Summary: AI skips the apprenticeship loop. Juniors get answers without building judgment. In 5 years, organizations lose the ability to evaluate their own output. ### About "Agent Skills" and Why It Matters URL: https://orchestrai.eu/blog/about-agent-skills-and-why-it-matters Date: 2026-01-27 Summary: Agent Skills turn one-time AI success into repeatable capability. Save a workflow, share it with juniors, execute forever. Skills = workflow execution layer for AI agents. ### What Millions of Conversations at Anthropic Reveal URL: https://orchestrai.eu/blog/what-millions-of-conversations-at-anthropic-reveal Date: 2026-01-24 Summary: Anthropic data shows AI speeds up complex work 12x, simple work 9x. Productivity gains flow to educated, high-income workers. The opposite of democratization. ### The 2 Types of AI Companies: Scientist-led vs Entrepreneur-led URL: https://orchestrai.eu/blog/the-2-types-of-ai-company Date: 2026-01-22 Summary: Scientist-led AI companies (Anthropic, DeepMind) think about responsibility. Entrepreneur-led (OpenAI, Meta) optimize for engagement. Who leads matters as much as what they build. --- ## Canonical website https://orchestrai.eu/ ## Pages to read - Home: https://orchestrai.eu/ - About: https://orchestrai.eu/about - Facts (for citation): https://orchestrai.eu/facts - Architecture: https://orchestrai.eu/#architecture - Integrations: https://orchestrai.eu/integrations - Pricing: https://orchestrai.eu/pricing - Enterprise: https://orchestrai.eu/enterprise - Security: https://orchestrai.eu/security - AI News (daily updates): https://orchestrai.eu/ai-news - Blog: https://orchestrai.eu/blog - Case studies: https://orchestrai.eu/case-studies ## Preferred citation OrchestrAI: AI Agent Operating System. https://orchestrai.eu/