Architecture Analysis

Architecture Audit

A deep-dive technical review of your AI infrastructure — we find what is broken, wasted, and holding back your systems.

Audit Scope

What We Audit

🔍

System Architecture Review

We review your AI system end-to-end — data pipelines, model choices, inference infrastructure, monitoring. We identify bottlenecks, inefficiencies, and risks.

🧠

Model Audit

We examine your models — training data, validation approach, failure modes, latency profile. We tell you what works and where it fails.

📊

Data Strategy Review

We assess your data. Is it organized effectively? Are labeling practices sound? Can the data support its intended uses?

⚙️

Infrastructure Assessment

We review your deployment infrastructure — cost efficiency, scalability, reliability, monitoring. What is working? What needs to change?

What This Is Not: This is not a sales pitch. We will not recommend "solutions" we sell. We give you honest feedback on what we see.

Deep Analysis

What We Analyze

We ask hard questions. We look for inefficiencies, risks, and missed opportunities.

Data Flow

  • QWhere does data come from?
  • QHow is it transformed?
  • QWhat quality checks exist?
  • QWhat data is lost or filtered?

Model Usage

  • QWhy this model for this problem?
  • QWhat training data was used?
  • QHow is performance validated?
  • QWhat happens when the model fails?

Failure Modes

  • QWhat edge cases are untested?
  • QWhat happens at latency limits?
  • QHow does the system degrade?
  • QWhat is your recovery strategy?

Infrastructure

  • QWhat is your cost footprint?
  • QHow scalable is the system?
  • QWhat are your monitoring gaps?
  • QHow is performance optimized?

Cost Efficiency

  • QAre you overspending on compute?
  • QCould you use smaller models?
  • QAre there latency-cost tradeoffs?
  • QWhat optimisations are missed?

Risk Assessment

  • QWhat are your data risks?
  • QWhat are your model risks?
  • QWhat are your operational risks?
  • QHow exposed are you to failure?
Deliverables

What You Receive

01

Written Report

A comprehensive technical report documenting our findings, analysis, and observations. Clear. Honest. Actionable.

02

System Diagrams

Visual representations of your architecture. Where data flows. Where models fit. Where risks exist.

03

Recommendations

Specific, prioritised recommendations. What to fix first. What to monitor. What to optimise.

04

Risk Assessment

Clear documentation of risks we identified. What could fail. What the impact would be. How to mitigate.

05

Cost Analysis

Breakdown of your infrastructure costs. Where money is well-spent. Where you are overspending.

06

Follow-up Session

We review the report with your team. Answer questions. Clarify recommendations. Ensure alignment.

Timeline: A typical audit takes 2–4 weeks depending on system complexity. We review your systems, talk to your team, and deliver findings.

Ideal Clients

Who This Is For

Funded Startups

You have built something. You want expert feedback before scaling. You need confidence in your architecture.

Scaling Teams

Your system is growing. You want to identify bottlenecks and risks before they become crises.

CTO-Led Organisations

You are responsible for technical risk. You want independent assessment of your AI systems.

Enterprises Adopting AI

You are deploying AI at scale. You need validation that your architecture is sound and secure.

Not For: If you do not yet have an AI system, this audit is premature. Contact us when you have systems to review.

Get Started

Request an Architecture Audit

Tell us about your systems. We will schedule a call to understand scope and timeline.

Or email directly at genjecx@gmail.com