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TensorPeak Labs

Production operations

AI Infrastructure & MLOps

Deploy and operate AI systems with the observability, reliability, security, and cost controls needed for production.

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What this solves

From promising capability to an operating product.

Production AI needs an operating layer around the application. TensorPeak Labs builds that layer so teams can deploy confidently, understand system behavior, and improve it without guesswork.

  • Move AI workloads from experiments into repeatable production environments
  • See model quality, latency, failures, and spend in one operating picture
  • Scale infrastructure without locking the product to one model provider

Capabilities

The parts required to make it work.

01

AI deployment architecture and cloud infrastructure

02

Model gateways, provider routing, fallbacks, and cost controls

03

Evaluation pipelines, tracing, monitoring, and alerting

04

CI/CD, secrets, access control, and operational runbooks

Delivery approach

A clear sequence from uncertainty to operation.

  1. 01

    Assess

    Review workloads, providers, data boundaries, reliability needs, and existing infrastructure.

  2. 02

    Design

    Define deployment, routing, evaluation, observability, security, and recovery patterns.

  3. 03

    Automate

    Build repeatable environments, delivery pipelines, tests, dashboards, and alerts.

  4. 04

    Operate

    Measure production behavior and improve reliability, performance, quality, and cost.

FAQ

Questions about this service.

Can you improve an AI system that is already running?+

Yes. We can assess an existing system and improve its deployment, observability, reliability, evaluation, and cost controls.

Do we need Kubernetes for AI infrastructure?+

Not necessarily. We choose the simplest infrastructure that satisfies the workload, reliability, security, and scaling requirements.

Can the architecture support more than one model provider?+

Yes. Where it creates practical value, we can design model routing and fallback paths that reduce provider lock-in and improve resilience.

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Ready to explore ai infrastructure?

Bring us the workflow, product idea, or architecture question. We’ll help you find a practical path forward.

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