AI-CHATBOT / ENTERPRISE AI
Reduce Vendor Dependence with an AI Platform You Can Control
Give your organization more options for how its AI platform is deployed, reviewed, and developed. With source code access and flexible infrastructure choices, your team can plan for greater long-term control.
Plan Your AI Platform StrategyBuild an AI foundation around your organization’s priorities.
YOUR AI PLATFORM. YOUR ORGANIZATION'S CHOICES.
More Control Over Your AI
Build a foundation your team can understand and extend
YOUR AI STRATEGY
Keep your options open.
Plan for source code access, deployment, and model choice.
A stronger foundation for your organization’s AI future.
Conceptual illustration, not a product screenshot.
THE OPPORTUNITY
Give your organization more control over its AI investment
As AI becomes part of daily operations, organizations need to think about how their platforms will be supported, customized, and maintained over time.
Source code access, deployment choices, and flexible model options can help your organization reduce dependence on a single provider’s infrastructure or product roadmap.
With the appropriate license and technical resources, your team can inspect the platform, develop custom capabilities, and plan how the technology operates within your environment.
Illustrative AI platform ownership workflow
Receive the platform
Source code access
AI agents and components
Deployment resources
Configure your environment
Choose infrastructure
Connect approved systems
Apply your policies
Develop over time
Customize workflows
Choose supported models
Build team capabilities
KEY BENEFITS
Create more choices for your organization
Build an AI strategy that gives your team visibility, flexibility, and a path for long-term development.
Source Code Access
Give your technical team the ability to inspect the platform’s underlying software.
Customization
Adapt agents, workflows, and integrations to support your organization’s needs.
Deployment Choice
Choose a managed environment or discuss deployment on your own infrastructure.
Model Flexibility
Consider supported AI models from different providers or compatible self-hosted models.
SOURCE CODE ACCESS
Understand and extend the platform behind your AI
A Full Code License gives your organization access to the source code under the terms of its license agreement.
Inspect the code
Review the platform’s components and architecture as part of your technical and security processes.
Focus: visibility.
Extend capabilities
Develop or adapt features, agents, and integrations to support your organization’s workflows.
Focus: customization.
Plan for continuity
Develop internal capabilities and make informed decisions about the platform’s future.
Focus: long-term planning.
PLATFORM CAPABILITIES
Work with the components that support your AI
The licensed platform can include access to the components your organization uses to build and operate AI experiences.
AI Agents
Configure and extend agents for the roles and workflows your organization supports.
System Connectors
Work with integration components that connect compatible applications and information sources.
Policy and Access Controls
Review platform components that support permissions, policies, and governance.
User Interfaces
Adapt supported user and administrative interfaces to your organization’s needs.
Deployment Resources
Use applicable configuration and deployment resources to operate the platform.
Documentation and Training
Build your team’s understanding of how to operate and extend the environment.
DEPLOYMENT CHOICES
Choose where your AI platform operates
Select a deployment approach that aligns with your organization’s infrastructure and operational resources.
Hosted Environment
Use managed cloud hosting while discussing source code licensing and your long-term plans.
Cloud or On-Premises
Deploy in your own cloud account or data center based on your organization’s requirements.
Air-Gapped Environment
Plan a disconnected deployment using compatible locally hosted models and components where needed.
AI MODEL FLEXIBILITY
Choose models that fit your use cases
Your organization can consider supported AI models based on capabilities, cost, performance, and data requirements.
Commercial Models
Work with supported models from different providers when external services fit your policies.
Self-Hosted Models
Consider compatible locally hosted models when your deployment requires additional control.
Adjust Over Time
Revisit model choices as your organization’s needs and available technology change.
BUILD YOUR TEAM'S CAPABILITY
Keep important platform knowledge within your organization
Technology independence also depends on the people who understand, operate, and maintain the platform.
Knowledge Transfer
Help your team understand the platform, architecture, and operating procedures.
Documentation
Provide resources that support administration, troubleshooting, and future development.
Ongoing Support Choices
Decide what your team will manage internally and where additional support is useful.
PLAN FOR THE LONG TERM
Make informed decisions about your AI environment
Reducing vendor dependence involves planning for the technology and services your organization will need over time.
Licensing
Review the rights, deliverables, and terms associated with your source code license.
Infrastructure
Plan the cloud, servers, network, storage, and operating resources needed for your deployment.
Updates and Maintenance
Define who will apply updates, manage security, and maintain the platform over time.
Connected Services
Review dependencies on AI model providers, integrations, and other third-party services.
Team Responsibilities
Identify the internal skills and external support your organization may need.
Future Changes
Plan how your organization can adapt its deployment and AI strategy as needs evolve.
GETTING STARTED
Plan an AI platform strategy with your team in mind
Begin with your organization’s goals, resources, and expectations for long-term platform control.
Identify your AI goals, technical resources, security needs, and deployment preferences.
Review source code licensing, infrastructure, model choices, and support requirements.
Define how your team will deploy, operate, customize, and support the platform.
FREQUENTLY ASKED QUESTIONS
Questions about reducing vendor dependence
What does reduced vendor dependence mean?
It means giving your organization more options for how its AI platform is inspected, deployed, customized, maintained, and supported.
Does source code access mean we can modify the platform?
A Full Code License provides rights to inspect, modify, and extend the licensed platform under the terms of the applicable agreement.
Can we deploy the platform on our own infrastructure?
Yes. Deployment in your own cloud or on-premises infrastructure can be discussed based on your technology and security requirements.
Can we use managed hosting and still receive source code?
A source code license can be discussed alongside a managed hosted deployment. The applicable terms and services should be reviewed for your organization.
Can we choose which AI models to use?
The platform supports multiple model options. Supported commercial and self-hosted models can be reviewed based on your deployment and use cases.
Will our platform have any outside dependencies?
That depends on your architecture. Cloud infrastructure, model providers, integrations, updates, and other services may be supplied by third parties. These dependencies should be reviewed during planning.
Can our team manage the platform independently?
Your team can plan to operate and extend the platform with the appropriate license, infrastructure, documentation, and technical capabilities.
How can our organization get started?
Begin by discussing your goals, deployment requirements, source code licensing, and the capabilities your team wants to manage internally.
LET'S GET STARTED
Build an AI foundation with more options for your organization
Explore how source code access, deployment choices, and model flexibility can support your long-term AI strategy.
Discuss Your AI Platform StrategyWe can discuss your AI goals, licensing, infrastructure, security requirements, and support options.