How is Glivent different from ChatGPT, Claude and Gemini?

How Glivent is different

ChatGPT, Claude, Gemini and Codex provide capable cloud AI tools. Depending on the product and plan, they can use skills, connect to software, schedule work and take actions.

A tool can provide the capability without providing the finished business process. Someone still has to decide what starts the work, what information is required, which systems the tool can access, what must be checked and when staff need to step in. Glivent designs and implements that process, then maintains and supports it after launch.

What sending business data to a cloud AI tool means

When staff use a cloud AI model, the information needed for the task leaves the business environment and is processed on the provider's infrastructure. Depending on the product, plan and settings, that information may be retained in service logs, stored or processed in another country, or handled by other service providers involved in delivering the platform.

A business plan may exclude customer content from model training. That is useful, but training is only one question. The business should also know:

• what information staff and connected systems can send;
• how long prompts, files and outputs are retained;
• where the information is stored and processed;
• which other providers or integrations can handle it;
• how access, deletion, security incidents and service outages are managed.

This does not make every cloud AI business product unsafe. Major providers offer encryption, access controls, retention options and enterprise agreements. It does mean the business relies on the selected provider, plan, contract and configuration. The business has less direct control than it would if the model task ran inside its own environment. See the guides on AI data location and reviewing an AI provider's data processing agreement for the checks that matter.

Keep suitable sensitive processing onsite with Private AI

Every Glive System runs through a dedicated Glive Pod on the client's premises. Where the task and model are suitable, Private AI can process sensitive information on the Pod without sending that information to a public cloud model provider.

This gives the business clearer control over where that AI processing takes place and reduces unnecessary exposure to third parties.

Remove sensitive details before using a cloud model

Some tasks are better suited to a cloud model. With Hybrid AI, Glivent can remove identifying or sensitive details on the Glive Pod before anything is sent to the cloud provider. The cloud model receives only the information it needs for that step, and the result returns to the business process for the required checks and approvals.

For example, a workflow could remove a person's name, contact details and account number before sending the remaining document text to a cloud model for classification. What can be removed depends on the task and the result the business needs.

Glivent can use ChatGPT, Claude, Gemini or another approved provider for a specific task. The cloud model is one part of the business process rather than the system that controls the whole process.

What cloud AI tools can do

Cloud AI tools are not limited to answering prompts. They can run scheduled tasks, use saved skills, work with connected systems and complete multi-step jobs. Codex can read, edit and run code within the access it receives. These tools can support both one-off work and automation.

The business still owns the setup around the tool. It must decide what the tool can access, build the process, set approval points, test unusual cases, monitor costs and maintain the setup as models and connected systems change.

Keep recurring work consistent

A general agent may choose different action paths when its instructions or context change. That flexibility is useful for open-ended work. It is less suitable when a business process must follow the same approved sequence each time.

Glivent keeps the business rules outside the AI task. Required information, approval limits and staff handoffs stay fixed even when the wording of an AI output changes. If the system cannot complete a step with enough confidence, it sends the case to the right person instead of making up a new path.

Costs and provider dependence

Business subscriptions and APIs use different pricing models. Production workflows may incur charges for model input, output, reasoning, stored context and connected tools. Providers can also change prices, rate limits and model availability.

The client pays any approved third-party API charges. These charges can be modest for a tightly defined workflow, but the actual amount depends on the model, volume and information processed. Glivent limits unnecessary usage and considers total cost when deciding where each step should run.

Suitable work can run locally. Cloud steps can use approved limits and, where the task supports it, a tested fallback route. A workflow may switch to another tested provider, use a local step or pause safely for staff review. This reduces dependence on one provider but does not guarantee that every workflow will always be available.

When a cloud AI tool is enough

A business may only need ChatGPT, Claude or Gemini when staff want help drafting, researching or analysing information and can review each result themselves. Codex may be enough when a capable developer wants help with a codebase and can control its permissions and review its work.

Glivent is better suited when the work repeats, crosses business systems, involves sensitive information or needs clear ownership and support.