Engineering services

Production AI Engineering

Build the evaluation, integration and operating foundations for dependable AI delivery.

Discuss your requirements
An engineering team collaborating around a table
Service Overview

What we deliver

RDMI engineers data pipelines, model services and agent workflows with testing, observability and cost controls. We define release criteria with your team, evaluate failure behavior and prepare operating procedures so system performance can be assessed after launch.

Key Features

Core capabilities

AI Platform Engineering

Build model APIs, data pipelines, job orchestration, environments, and deployment paths.

Monitoring & Evals

Track quality, latency, cost, failures, drift, user feedback, and business metrics.

Security Controls

Implement access control, privacy, secrets, audit logs, and policy-aware AI interactions.

Release Reliability

Use CI/CD, rollback plans, test suites, load testing, and incident runbooks.

Our Process

How we deliver results

01

Production Audit

Review architecture, data, deployment, security, and observability gaps.

02

Engineering Plan

Define the platform components required for the target AI workflow.

03

Implementation

Build, test, deploy, and monitor the production AI system.

04

Operate

Create runbooks, feedback loops, and improvement cadences for ongoing reliability.

Build a clear case for Production AI Engineering.

Define the workflow, the performance baseline and the outcome you want to improve. We will help shape a scope that your team can evaluate.

Production AI Engineering - RDMI Services