Don't get locked into a single model.
KRNL proposes a common layer to operate with different AI models, such as ChatGPT, Claude, Gemini, or local models, while keeping control over data, agents, workflows, and knowledge.
ChatGPT
OK
Claude
OK
Gemini
OK
Local models
OK
Operating Core
Agents
Automations
Dashboards
End user
The problem
When AI depends on one vendor,
the business loses control.
Being tied to one vendor is not just a technical problem. It affects costs, visibility, and your company's ability to change course.
Price changes
A vendor can change rates, limits, or terms and affect the business's entire AI operation.
Black box
Each vendor stores context and data its own way: switching models means rebuilding the operation from scratch.
Lost context
Knowledge stays tied to tools, personal accounts, or configurations that are hard to migrate.
Multi-model layer
A single place to operate multiple AI brains.
KRNL lets you choose the right model for each task without redesigning the operation or losing context.
Available models
KRNL view
ChatGPT
OpenAI
Switch the model without reconfiguring agents, policies, or workflows.
Conceptual operating example · does not reflect real metrics
Data sovereignty
Context doesn't live with the vendor.
It lives in your organization.
KRNL keeps knowledge, documents, agents, and workflows within the client's infrastructure, with portable databases and its own traceability independent of any LLM.
Your own portable knowledge bases
Persistent context independent of the model
Your own traceability, not tied to the vendor
Installation on the client's servers or cloud
Controlled export and migration at all times
Knowledge Vault
Documents
Vector databases
Agents
Workflows
Logs & auditing
ImmutableEverything connected to KRNL · Not to OpenAI, Google, or Anthropic
Portability
Switch the model. Keep the operation.
With KRNL, switching vendors or models doesn't mean rebuilding. Your operation stays intact.
Without KRNL
Each area uses separate, isolated tools
Context ends up scattered across personal accounts
Switching models means rebuilding everything
Each vendor imposes its own rules and limits
With KRNL
RecommendedModels connected to a single operating layer
Agents, workflows, and context remain intact
Traceability is preserved when switching models
The business keeps full control and visibility
Operational independence
Independence isn't just choosing models.
It's controlling the entire operation.
KRNL gives you real independence over the models, data, agents, and costs of your AI operation.
Models
Choose the right LLM for each task: accuracy, cost, confidentiality, or specific context.
Data
Keep documents, vectors, and context within your infrastructure. Nothing leaves the perimeter.
Agents
Keep agents, workflows, and expertise even if you switch vendors or the underlying model.
Costs
Observe consumption, usage, and efficiency per area, agent, or model. Optimize without surprises.
Take back control of your AI strategy.
KRNL makes it possible to operate enterprise AI without depending on a single vendor, tool, or isolated account.