AI Governance with KModels Enterprise

AI is spreading faster than your controls

Teams connect to different AI providers on their own, each with its own keys, SDKs and contracts, so nobody has a complete view of which models are used, by whom, and for what.
Customer, financial and operational data can reach unapproved model endpoints, and there is no consistent audit trail to show compliance, internal audit or regulators what was sent where.
Per-token pricing makes AI spend hard to predict: without limits by team, user or application, costs surface only at the end of the period. And when a provider slows down or goes offline, every application built on it stops.

Data centre aisle with server racks, representing governed AI infrastructure

From scattered AI usage to one governed AI infrastructure

Before KAPTO

Every team integrates its own AI providers, SDKs and API keys
Per-token AI costs surface only at invoice time, with end-of-period surprises
Replacing a model means code changes, test cycles and downtime
One provider or site outage stops the applications built on it
Traffic peaks hit provider rate limits and overload shared infrastructure
No single view of AI performance, usage and cost across teams and applications
Sensitive data can reach unapproved models, and audit evidence is pieced together by hand

With KAPTO

All applications reach AI models through one gateway, with one API and no code rewrites
Budgets and limits at every level, from organisation and team down to user or application and key pair, with alerts before they are reached
Models are swapped transparently behind the gateway, with zero downtime for applications
Automatic fallback to backup models, on the same site or off-site, keeps operations running
Request and token throttling protects both model providers and your infrastructure
Technical, usage and economic dashboards and reports across teams and applications
PII masking, guardrails and immutable audit logs on every AI interaction

Predictable costs, uninterrupted AI operations

Control spend at every level, change models without downtime and keep full technical and economic visibility across teams and applications.

No end-of-period cost surprises

Budgets and limits per organisation, team, user or application, and key pair keep per-token spend under control.

Swap models with zero downtime

Replace or upgrade models and providers behind the gateway without code changes or service interruptions.

Resilient on-site and off-site

Automatic fallback to backup models or deployments, on the same site or off-site, keeps operations running.

Full technical and economic visibility

Dashboards and reports on performance, usage and costs across teams, applications and key pairs.

See how KModels Enterprise governs AI across your company

Connect once:

Your applications point to the KModels gateway, deployed on-premise or in your private cloud, instead of individual providers. It exposes an OpenAI-compatible API, so teams change only the endpoint, not their code.

Set access and guardrails:

Approved models are configured centrally and access is managed through your existing SSO. Personal data is masked, secrets are redacted and content rules are enforced before any request leaves the gateway.

Control costs at every level:

Budgets and spending limits are set per organisation, team, user or application, and key pair. Alerts warn before a limit is reached and over-budget requests are stopped at the gateway, so per-token pricing never turns into an end-of-period surprise.

Swap models with zero downtime:

Applications call a functional model name, not a specific provider. You can replace or upgrade the model behind it transparently, without code changes and without interrupting the applications that use it.

Fall back automatically, on-site or off-site:

Fallback chains redirect requests to backup models or deployments, on the same site or off-site, when a provider is slow, rate-limited or unavailable, so operations keep running.

Throttle models and infrastructure:

Request and token rate limits are enforced per model, deployment, team and key, with load-, latency- and cost-based routing that protects both provider quotas and your own infrastructure.

Report on performance, usage and costs:

Dashboards and reports cover technical metrics such as latency, errors and throughput, usage by team, user and application, and economic data with cost attribution down to the key pair.

Audit every interaction:

Immutable audit logs record AI interactions and administrative actions, with configurable retention and export to your existing monitoring and log tools.

One gateway to govern every AI model in your company