eeko systems
Private AI infrastructure for companies that host their own models.
Private model deployment, RAG systems, on-prem inference and GPU planning for teams that cannot send data to an external API.
The platform runs a compute control plane that places dedicated LLM inference across RunPod, CoreWeave Kubernetes and private bare metal. It reconciles against desired state, restarts failed workloads and scales to zero when idle.
Regulated industries
Financial services, healthcare, legal and insurance teams that need the model inside their own network, with audit logging, SSO, MFA and SCIM for compliance review.
Controlling inference cost
An OpenAI-compatible gateway meters usage per token, applies budgets per team and bills through Stripe. Spend is attributed to a team and a workload.
Changing GPU providers
Provider adapters and traffic splitting support canary and blue-green rollouts, and migration between providers without application changes.
- Background
Regulated teams could not use public AI APIs because of data residency and compliance requirements.
- Build
Private deployment, retrieval and the surrounding operations tooling, with SOC 2 and HIPAA controls included in the design.
- Now
Runs dedicated inference with capacity reservations, autoscaling, automatic recovery and a hash-chained audit log.