AI Engine

When reliable systems, oversight, and control matter most

CloudFactory’s AI Engine helps organizations confidently operate AI in production by delivering continuous monitoring, infrastructure optimization, and governance enforcement.

Essential in environments where reliability, compliance, and performance are critical.

Operational management

Model monitoring & observability

Risk management & incident response

Scalable infrastructure & cost optimization

Governance & compliance

AI Trust Gap

“Without a robust MLOps strategy, cost‑savings from AI maintenance are counteracted.”*

40%

"46% of models never make it to production, and 40% of those that do degrade within the first year."

(Dataiku, 2025)

12%

“A lack of AI governance can lead to costly failures … only 12 % have a dedicated AI governance framework.”

(Gartner)

Lack of operational oversight: results in undetected performance degradation and unreliable AI in production
No centralized monitoring: makes it difficult to track model health, usage, and failures at scale
Inefficient infrastructure management: drives up costs and limits the ability to scale AI workloads efficiently
Weak governance controls: lead to non-compliance with internal policies and external regulations
Siloed AI operations: slow response times, hinder retraining, and delay value realization from deployed models

*Atlan, 2024

Common AI needs

What we’re hearing from
clients

“I need to create an AI model, but my internal team doesn't have the capability or capacity to do so.”

“I need to detect model drift while my models are running to keep them relevant.”

“I need peace of mind and reduced downtime from AI failures.”

“I need to maximize performance while controlling infrastructure and operating costs.”

“I need to operate my AI with confidence, knowing my company meets internal policies and external regulations.”

Meeting you where you are

An enterprise-ready AI platform service

Built for complex, high-impact sectors, the AI Engine delivers the operational control and visibility required when model reliability, uptime, and governance are mission-critical.

Real-time tracking
Performance, accuracy, and drift

Security & Compliance
Compliance with industry standards

Operation flexibility
Cloud and on-prem environments

Realtime operations
Monitor, govern, and retrain

Proactive risk management
Before issues arise

Scalable infrastructure
Dynamic scaling, multi-tenant hosting

Face issues with real-time tracking of AI model performance, accuracy and drift.
Optimize AI models and workloads for cost and efficiency
Operate AI models within regulatory and ethical guidelines
Prevent failures that could impact business outcomes
Keep AI systems running accurately and securely
Detect and address issues before they scale
Ensure continuous alignment with business and ethical goals

Outcome:

Reliable, efficient, and compliant AI operations, built for the real world.

AI Engine