Introduction
This article provides an in-depth examination of the architecture for Leena AI’s enterprise Agentic AI. It demonstrates how different layers and components interconnect to deliver AI Colleagues with human-like agency.
Below is a comprehensive description of the Leena AI “Agentic AI Architecture” diagram, breaking down each component and illustrating how they interact to form a cohesive enterprise AI solution.
The Architecture Highlights:
- Collaborate: Channels where users interact with the Agentic AI systems
- Orchestrator: Central planning and coordination engine
- AI Colleagues: Specialized AI agents based on roles or applications
- Studios – AOPs, Skills, Knowledge: To ground the Agentic system in Enterprise Specific Business Processes/Applications/Knowledge
- Permissions & Access Controls: A Security layer ensuring compliance and role-based access
- Observability and Governance: Oversight, governance, and continuous improvement
- Security & Compliance: Adherence to industry standards like HIPAA, GDPR, SOC2, etc.
1. Collaborate – Touchpoints
Positioned at the top of the diagram are multiple touchpoints through which users and systems can interact with the AI Colleagues:
- Web Chat
- Voice
- SMS
- Messaging Apps (e.g., Microsoft Teams, Slack, Zoom, WhatsApp)
- API, MCP, A2A (for invoking agents on different types of triggers), and interoperability
- Intranet (internal company portals)
These touchpoints represent the diverse channels through which employees, customers, or partners engage with AI Colleagues. The architecture is channel-agnostic, meaning any new channel can be integrated with minimal overhead.
2. Orchestrator
Every task/request/prompt comes to the Orchestrator. Its job is to break down complex tasks into smaller doable tasks and call the right AI Colleagues to do them.
The orchestrator leverages Leena AI’s proprietary WorkLM (fine-tuned GPT 5.2 on 10M+ proprietary synthetic data). It is essential to note that we are not a model company and will continue to fine-tune all our latest models to deliver the best results for our customers.
The reason we fine-tune these LLMs is that consumer-grade LLMs don’t understand general business processes; for eg, a Purchase Requisition (PR) is almost always required before a Purchase Order (PO) can be issued in enterprises – this general business info is fine-tuned by us in these LLMs.
3. AI Colleagues
Positioned below the Orchestrator are AI Colleagues: think of AI Colleagues as an Individual Contributor Job role with human-like agency in the back office. Each AI Colleague operates as a persistent digital worker within your organization, equipped with domain expertise and the ability to execute complex business processes in enterprise applications.
What Makes an AI Colleague?
Each AI Colleague is defined by:
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- Identity & Role: A clear job description and scope of responsibilities (e.g., IT Helpdesk Agent, Accounts Payable Analyst, HR Operations Specialist). Each AI Colleague is also assigned a Human Manager who gets to resolve exceptions/grey areas/edge cases that the AI Colleague cannot handle directly.
- Agent Operating Procedures (AOPs): AOPs ground AI Colleagues in your company’s specific business processes. They are similar to how SOPs guide human employees
- WorkBench: The Workbench is AI Colleagues’ list of things to do. It is a central scheduling and execution management system that enables organisations to automate business processes on predetermined schedules. Rather than requiring manual triggers for every automation, Workbench allows you to set up recurring or one-time executions of your Agent Operating Protocols (AOPs), ensuring critical business processes run consistently without human intervention.
- Skills: Skills are probably the most fundamental building blocks that enable AI Colleagues to perform specific tasks and operations in multiple enterprise applications. Think of skills as individual capabilities that can be combined and orchestrated within Agent Operating Protocols (AOPs) to create comprehensive business process automation.
- Memory + Context Graph: Memory has a few important components:
- Via Memory, AI Colleagues have access to enterprise knowledge & industry knowledge needed to complete their responsibilities.
- As AI Colleagues continue to interact with people and enterprise systems in order to complete complex business processes, they keep creating a Context Graph with decision traces of all kinds of exceptions and precedences that they come across.
- Further to this, AI Colleagues also form user-specific memory over time to personalise their relationships with humans.
- Escalation Protocols: Defined pathways for handling exceptions and seeking human intervention when needed
Agent Operating Procedures (AOPs): The Bridge Between Process and Execution
AOPs are to agents what SOPs are to humans. They ground AI Colleagues in your company’s actual business processes without requiring complex, resource-intensive workflow programming. Either upload your existing SOPs or write AOPs in simple English.
Unlike traditional automation that requires hardcoded workflows, AOPs allow you to:
- Describe processes naturally: Use your existing SOPs, business process flow diagrams, or even plain text descriptions
- Adapt dynamically: AI Colleagues interpret and follow these procedures at runtime, handling variations and exceptions intelligently
- Iterate quickly: Business users can create and modify AOPs without technical expertise, dramatically reducing time-to-automation
For example, a Purchase Order creation agent doesn’t need a rigidly programmed workflow; it follows your company’s specific PR creation, approval, and PO creation AOP, adapting to different scenarios as they arise.
Skills
Skills allow AI Colleagues to go do things in enterprise applications. The AI Colleague Studio includes 5,000+ pre-built skills across 1,000+ enterprise applications (Workday, SAP, ServiceNow, Salesforce, Oracle, UKG, etc.), which can be configured by the customer in minutes.
Apart from the application-specific skills that you turn on, every AI Colleague comes with foundational skills like:
- Browser Use (navigating interfaces) allows AI Colleagues to log in to applications and do things just like a human would. This is used when APIs/MCPs are not available.
- Coding and data analysis
- Document processing and comparison
- Intelligent decision-making
- Code creator
- & Many more
Memory + Context Graph
Memory has a few important components:
Memory: AI Colleagues have access to enterprise knowledge & industry knowledge needed to complete their responsibilities. Leena AI Knowledge Management (KM) integrates seamlessly with:
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- Enterprise knowledge management apps: SharePoint, ServiceNow KM, Box, Google Drive, Dropbox, Confluence
- Data lakes: Snowflake, Databricks, Azure S3
- Web scraping: Any website you want to incorporate into your company’s knowledge base
Context Graph – As AI Colleagues continue to interact with people and enterprise systems in order to complete complex business processes, they keep creating a Context Graph with decision traces of all kinds of exceptions and precedences that they come across. All interactions & their decision traces that AI Colleagues have with human colleagues, customers, vendors, other agents, or their human manager are stored in the context graph. The AI colleague always explicitly asks about the decision/exception/precedence and its reason to be able to create a robust context graph, which it can refer to in the future to make better and faster decisions on top of the instructions provided in the AOP. In the future, we will start extracting the context graph from various sources like Slack, Teams, Emails, logs, tickets, etc.
4. Studios for AOPs, Skills, and Knowledge
The AOP (Agent Operating Procedure) Studio revolutionizes how organizations create and manage automated business processes. Unlike traditional workflow builders that require technical expertise and rigid programming, the AOP Studio enables business users to define processes in natural language.
How It Works
Business users can create AOPs by:
- Uploading existing SOPs in various formats (PDF, DOCX, flow diagrams)
- Describing processes conversationally in plain text
- Referencing company-specific procedures and business rules
From Minutes to Live
What traditionally took days or weeks of technical workflow configuration now happens in minutes:
- No coding required: Business users author and modify AOPs directly
- Rapid iteration: Edit and republish AOPs as business processes evolve
- Version control: Full audit trails and the ability to roll back changes
- Testing capabilities: Validate AOPs before going live with simulation modes
Intelligent Skill Binding
The AOP Studio automatically connects process steps to the right capabilities:
- Pre-built Skills from the Workflow Studio (500+ templates)
- Custom API integrations
- Default Skills like computer use, coding, and data processing
- Agent-to-Agent/MCP collaboration for cross-functional processes
Workflow Studio: Enterprise-Specific Skills
Skills are the atomic units of work that AI Colleagues execute. The Workflow Studio is where enterprise-specific deterministic workflows are configured and managed.
Comprehensive Template Library
The Workflow Builder comes pre-loaded with:
- 5,000+ pre-built workflow templates across common business functions
- 1,000+ enterprise application integrations: Workday, SAP, ServiceNow, Salesforce, Oracle, UKG, Coupa, BambooHR, and more
- Customizable templates that customers can adapt to their specific business processes
This extensive library ensures you can get AI Colleagues up and running quickly while grounding them in your company’s actual business processes and systems.
Knowledge Management: Enterprise Memory
The Knowledge Agent provides AI Colleagues with access to your organization’s collective intelligence—the structured and unstructured knowledge that makes them truly context-aware.
Universal Knowledge Integration
Leena AI Knowledge Management (KM) integrates seamlessly with:
- Enterprise knowledge management apps: SharePoint, ServiceNow KM, Box, Google Drive, Dropbox, Confluence
- Data lakes: Snowflake, Databricks, Azure S3
- Web scraping: Any website you want to incorporate into your company’s knowledge base
Optimized for Speed and Security
Rather than querying external systems at runtime (which can be slow), Leena AI KM:
- Syncs and indexes all enterprise knowledge centrally
- Pre-processes content to make information instantly available to agents. Read more about pre-processing here
- Maintains security groups from all knowledge sources, ensuring permission-appropriate access
Provides fast retrieval at inference time for real-time agent decision-making
5. Permissions & Access Controls
In the center, bridging the Domain-Specific Modules, there is a robust Permissions & Access Controls layer. This ensures:
- Role-Based Access: Only authorized individuals or systems can view or modify specific data.
- Security & Compliance: The system respects regulations like ISO 27001, HIPAA, GDPR, and SOC2, maintaining data privacy and integrity.
- Multi-Tenant Architecture: If the platform is deployed for multiple departments or organizations, each tenant’s data and workflows are securely isolated.
6. Observability and Governance – Responsible AI
Leena AI’s Responsible AI framework governs continuous service improvement and ensures ethical, compliant use of AI. It includes:
- Transparency Dashboard: Shows how decisions are made, providing traceability and explainability for AI-driven actions
- Knowledge Health Dashboard: When you integrate your Enterprise Knowledge into Leena AI KM, the Knowledge Health Dashboard will highlight issues in your Knowledge, like overlapping knowledge, stale knowledge, absent security groups, etc. This is extremely important to avoid Garbage-in/Garbage-out.
- Analytics: Monitors system performance, user interactions, and AI Colleagues’ accuracy. It may also track key performance indicators (KPIs) and usage metrics.
- Helpdesk Insights: Analyzes user queries, identifies trends, and recommends improvements to workflows or the Knowledge Base.
This layer helps organizations comply with internal governance policies and external regulations while maintaining user trust.
7. Security & Compliance
Leena AI is used by over 500+ enterprises globally and has various industry certifications and compliance with many regulations:
- HIPAA: Ensuring healthcare data privacy
- GDPR: European data protection requirements
- SOC2: Service Organization Control for data security and privacy
- ISO 27001: International standard for information security management.
Other standards or certifications may be relevant depending on the specific industry or geographical location. The system is designed to be private and compliant, with data encryption, secure data handling, and audit trails.
Conclusion
Leena AI’s Agentic AI Architecture is designed to provide an end-to-end solution for enterprise-grade AI services. By combining a central Orchestrator, specialized Colleagues, Studios for Skills and AOPs, Knowledge Base, and out-of-the-box integrations, organizations can automate complex processes across different domains while maintaining strict security, compliance, and ethical standards. The incorporation of a Responsible AI framework ensures transparency, accountability, and continuous improvement—key factors for successful AI adoption in modern enterprises. Learn More here!
Frequently Asked Questions (FAQs) about Agentic AI
What is the core agentic definition when we talk about AI?
In the context of AI, the ‘agentic definition’ refers to an AI system’s capacity for agency. This means the AI can perceive its environment, make independent decisions, and take autonomous actions to achieve specific goals. It’s about AI moving beyond passive responses to become an active participant in processes.
Can you give a simple Agentic AI definition? What is Agentic AI in essence?
Essentially, Agentic AI is an advanced form of artificial intelligence that doesn’t just answer questions or provide information, but actively performs tasks and completes actions on behalf of users. The Agentic AI definition emphasizes its ability to combine knowledge with action to get things done across various enterprise systems.
How does Agentic AI differ from generative AI?
While both are advanced AI, Agentic AI is primarily focused on action and task completion within enterprise systems, guided by specific workflows and goals. Generative AI, on the other hand, excels at creating new content (text, images, code). An Agentic AI system might use generative AI capabilities as one of its tools, but its core purpose is to act as an intelligent agent that executes tasks.
What is an agentic workflow, and how do agentic AI workflows help businesses?
An agentic workflow is a defined sequence of steps, decisions, and actions that an Agentic AI system follows to complete a specific business process. These agentic AI workflows help businesses by automating complex, often multi-system tasks (like employee onboarding or IT support resolution), ensuring consistency, improving efficiency, and freeing up human employees for more strategic work.
What are Agentic AI frameworks, and why are they important for deploying Agentic AI?
Agentic AI frameworks refer to the comprehensive architecture and underlying structure that enable Agentic AI to operate effectively, reliably, and securely within an enterprise. This framework typically includes components like an orchestrator, specialized agents, a workflow studio, knowledge management systems, integration layers, and robust security and permission controls. They are important because they provide the necessary foundation for scalable, manageable, and future-proof Agentic AI solutions.
What are the key benefits of implementing Agentic AI in an enterprise?
Implementing Agentic AI offers several key benefits, including:
- Enhanced employee experience by providing a single, intelligent point of contact for tasks and information, reducing confusion from too many apps.
- Increased productivity by automating routine tasks and handling complex cross-system use cases.
- Improved operational efficiency by streamlining processes across various departments like HR, IT, and Finance.
- Reliable and trusted assistance, as enterprise-grade Agentic AI is designed to avoid hallucinations and follow strict data permissions.
How do agentic AI workflows specifically improve the employee experience?
Agentic AI workflows improve the employee experience by making interactions with company systems seamless and intuitive. Instead of employees needing to know which system to use for a specific task (e.g., requesting leave, resolving an IT issue), the Agentic AI, guided by its workflows, handles these processes behind the scenes. This means employees get their tasks done quickly and easily, reducing frustration and allowing them to focus on their core responsibilities.
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