Inference Engine

When the cost of AI errors is too high to risk

CloudFactory’s Inference Engine helps organizations maintain trust in their AI predictions by continuously validating, correcting, and evaluating model outputs, especially in use cases where the cost of inference error is high.

Inference validation

Inference error handling

Inference evaluation

AI Trust Gap

“An AI trust gap may be holding CEOs back”*

56%

cite inaccuracy of output as the biggest issue

(McKinsey, 2023; IBM Newsroom 2024)

3%

of firms are mitigating for inaccuracy

(Dr Cooper, 2024)

Confidence issues - Lack of confidence in model predictions drives poor use case outcomes
Poor visibility -Limited visibility into inference quality leads to trouble identifying when models fail
Business impact - Model errors result in costs in delays, reputational risk, or regulatory failure
Sub-par framework - Unstructured evaluation frameworks result in inconsistent, ad hoc analysis of model outputs
Inefficient processes - Slow or non-existent error correction lets errors persist or go uncorrected

*PWC

Common AI needs

What we’re hearing from
clients

“I need to know when my model is wrong—before my users do.”

“I need to continuously evaluate my model's performance to ensure consistent quality.”

“I need to correct inference mistakes quickly—especially in high-risk workflows.”

“I need to prove my model meets internal compliance and external regulatory standards.”

“I need to trust that my AI is reliable, explainable, and ready to scale.”

Meeting you where you are

An enterprise ready AI platform service

Designed for high-stakes environments that need oversight when reliable predictions are non-negotiable

Continuous validation
Inference visibility and reporting

Security & compliance
Accuracy and auditability standards

Reliable outputs
Mission-critical use cases

Adaptive correction
Learn from past errors

Inference scoring
Accuracy, fairness, and relevance

A/B testing
Inference strategy comparison

Solves trust and reliability issues in AI predictions.
Improves safety and compliance at the point of inference.
Validates, evaluates, and corrects model outputs continuously and in near real-time.
Supports a variety of model types (LLM, VLM, CV, and NLP).
Integrates with your infrastructure with customizable response times.

Outcome:

Production-ready AI that operates with confidence, integrity, and oversight— no matter the use case.

Inference Engine