# MLOps, LLMOps & Inference

> Deploy, serve and scale models reliably. We build the delivery pipeline for models and prompts: CI/CD, model registry, feature and prompt versioning, monitoring and drift detection, and high-throughput self-hosted inference on GPUs when you need privacy or cost control.

Source: https://aibyos.com/services/llmops

▤ Capability

# MLOps, LLMOps & Inference

Deploy, serve and scale models reliably.

[Discuss MLOps / LLMOps](https://aibyos.com/contact)

We build the delivery pipeline for models and prompts: CI/CD, model registry, feature and prompt versioning, monitoring and drift detection, and high-throughput self-hosted inference on GPUs when you need privacy or cost control.

## Typical use cases

### Self-hosted LLM inference

**Challenge.** Data can’t leave your environment, or API costs are too high at volume.

**What we build.** Open models served with vLLM/TGI on autoscaling GPU clusters, with batching, quantisation and an OpenAI-compatible API.

### ML platform modernisation

**Challenge.** Models are deployed by hand from notebooks.

**What we build.** A standard path from experiment to production: pipelines, registry, automated deployment and monitoring.

### Monitoring & drift detection

**Challenge.** Model quality silently degrades in production.

**What we build.** Data and prediction monitoring with alerting and retraining triggers.

## What you get

-   CI/CD for models & prompts
-   Serving infrastructure
-   Monitoring & alerting
-   Cost & capacity plan

## Typical stack

-   vLLM / TGI / Triton
-   Kubernetes + KServe
-   MLflow
-   SageMaker / Azure ML / Vertex AI
-   Databricks
-   Prometheus / Grafana

Examples

## Use cases with MLOps / LLMOps.

[Manufacturing & Logistics Visual defect detection on the line Detect defects consistently from camera images at production speed. _Image & Vision__MLOps / LLMOps_ Open →](https://aibyos.com/use-cases/inspection) [SaaS & Technology Move from API to self-hosted model Cut inference cost and keep data private with a fine-tuned open model. _Fine-tuning__MLOps / LLMOps_ Open →](https://aibyos.com/use-cases/self-hosted) [SaaS & Technology Ticket routing without per-call LLM costs Millions of support messages classified by a distilled in-house model instead of a large LLM API. _AI Research__Fine-tuning__MLOps / LLMOps_ Open →](https://aibyos.com/use-cases/distill-saas)