Model catalog and one API
Expose selected models and providers through a consistent integration point without tying every app to one endpoint.
AI infrastructure for business
One gateway for AI models. Full control over usage.
Manage access, model selection, and cost without changing every application separately.
We design and implement an LLM Gateway as the central layer between your applications and model providers. Teams use a consistent API, while you see traffic, costs, limits, and quality in one place.
An LLM Gateway is a central access point for AI models. It lets you assign keys and permissions to teams, route requests to suitable models, apply limits and fallback, and measure usage, cost, and latency across connected applications.
Control, routing, and optimization in one layer
Keys and permissions
Separate access for applications, teams, and projects. Keys can be rotated or disabled without changing the whole environment.
Budgets and limits
Set cost and request limits, with alerts before agreed thresholds are reached.
Routing and resilience
Choose models by task, balance traffic, and configure retries and fallback when a provider is unavailable.
Protection and usage policies
Add rules for connected flows, such as sensitive-data filtering, allowed models, and logging policies.
Analytics and optimization
Track cost, tokens, latency, and errors, then review model choices, caching, and limits using real usage data.
Charts that help you manage AI
We report cost, volume, latency, errors, and budget utilization by application, team, project, and model. The final metrics are tailored to your goals.
The charts illustrate the types of reports available after implementation. They do not show real client data or guaranteed savings.
From traffic mapping to controlled production
AI usage audit
Identify applications, models, keys, request volume, costs, and data requirements.
Policy design and pilot
Define access, budgets, routing, fallback, and quality and cost measures.
Integration and rollout
Connect applications in stages and test failures, limits, and visibility in the dashboard.
Ongoing optimization
Review reports, update the model catalog, and adapt rules to actual traffic.
The Gateway covers only applications and flows connected to this layer. It does not automatically capture employees' private use of other AI tools.
FAQ
Do we need to replace existing AI applications?
No. Existing applications can usually be connected to a shared access point in stages. The amount of change depends on their current API and key-management approach.
Can the Gateway use several model providers?
Yes. Selected models from different providers can be exposed with routing rules, limits, and fallback. The exact catalog depends on your contracts and requirements.
How are costs controlled?
We attribute usage to projects, applications, or teams, set budgets and alerts, and report cost, volume, and trends. Optimization recommendations are based on data from the pilot.
Do the charts on this page show real results?
No. They use illustrative data to show a possible reporting layout. Real charts are created only after integration with a client's systems.