It enables business and technical teams to publish their own agents securely — with full governance, visibility, and customization — while ensuring a consistent enterprise experience.
Business Context
For large organizations adopting Generative AI at scale, centralization is critical.AI Store provides a single, compliant catalog where every agent can be created, versioned, and shared based on enterprise policies. It simplifies:
- Deployment and configuration of AI assistants across business units.
- Management of models, prompts, and behaviors.
- Control of access, branding, and publication workflows.
Key Capabilities
Create and publish enterprise-grade AI agents within a governed catalog.
Assign categories such as Marketing, Human Resources, or Engineering to structure your internal AI marketplace.
Assign categories such as Marketing, Human Resources, or Engineering to structure your internal AI marketplace.
Customize each agent’s prompt, greeting message, and fallback response directly from the Store interface — no code required.
Manage model selection, user experience, and feature visibility for each agent.
Enable or disable vision, image, or text models depending on the business use case.
Enable or disable vision, image, or text models depending on the business use case.
Access usage analytics for every agent — including message count, tokens consumed, and cost tracking — to monitor adoption and optimize performance.
Learning Journey
1
Video 1 — Creating and Configuring an AI Agent
Objective of the use case:
Learn how to create, configure, and publish your first AI agent in the AI Store.What you’ll see:
- Browsing available agents by category (e.g., Marketing, HR, Engineering).
- Creating a new agent with a name, category, description, and custom image.
- Accessing the agent’s configuration panel with advanced options.
- Editing the prompt, welcome message, and fallback response.
- Customizing model selection and user interface settings.
- Adding warning or policy messages at the start of each conversation.
- Testing prompt changes (e.g., “speak in old English”) to validate agent behavior.
- Managing responses: reactions, statistics, and regeneration.
- Exploring model options for text, vision, and image generation.
- Reviewing analytics on token usage, cost, and consumption.
- Using the embed feature to integrate the chat agent externally (website, intranet, etc.).
Teams can create specialized AI agents quickly, adjust their personality and scope, and publish them safely across departments — all under centralized governance.
Practical Applications
| Department | Use Case | Description |
|---|---|---|
| Marketing | Campaign Assistant | Publish branded assistants to help teams generate campaign content faster. |
| HR | Employee Support Agent | Provide internal assistance and automate HR FAQs securely. |
| IT / Engineering | Technical Troubleshooting Agent | Configure agents to assist employees with recurring IT issues. |
| Customer Support | Embedded Support Chat | Integrate support agents directly into client portals or partner websites. |
| Compliance | Policy Advisor | Centralize validated AI agents to ensure compliant responses organization-wide. |
Key Takeaways
- Centralized creation and publication of AI agents within a governed enterprise catalog.
- Full customization of prompts, greetings, and behaviors — without technical complexity.
- Usage analytics and cost tracking for transparent adoption monitoring.
- Seamless integration through embedded chat agents or internal workspace deployment.
- Consistent governance and branding across all AI-powered interactions.