200+
Highly Qualified Engineers
Real projects. Real ROI — 2,300+ projects delivered across 71+ countries.Explore Now
Real projects. Real ROI — 2,300+ projects delivered across 71+ countries.Explore Now
Applications built with AI usually work on the surface. It hides code, security, architecture, and performance issues underneath. Dev Technosys offers AI code audit services that uncover these risks before they become costly production issues. Our AI code review services give you a clear view of what needs fixing and what is ready to scale.
200+
Highly Qualified Engineers
16+ Years
Software Engineering Experience
2900+
Projects Delivered & Audited
35+ Industries
Domain Experience
71+ Countries
Global Client Delivery
CMMI Level 3
Process-Certified Delivery
ISO 9001:2015
Quality Management Certified
AI/ML Expertise
Model & Code Assessment
Security-First
AI Code & Architecture Reviews
NDA Protected
Confidential Audit Engagements
An AI-built app audit is a structured technical review of an application. AI coding tools, AI app builders, or AI/ML technologies are used in its development. AI application audit services inspect the code, architecture, AI workflows, data, integrations, security, performance, and scalability. Its main purpose is to find out the problems before they become costly problems.
Based on an AI consulting services company's experience, applications that are created by AI can be launched quickly. However, after app deployment, hidden costs, security, and AI-quality issues can be costly. With an AI application code audit, businesses can find these gaps easily and fix them.
Identify insecure code from AI generation, out-of-date dependencies, access control weaknesses, duplicate logic, and technical debt before they impact your application.
Validate model accuracy, quality of responses, hallucinations, API performance, data pipelines, and AI workflow through measurable technical benchmarks.
Look for wasteful API calls, inefficiencies in model utilization, wasted infrastructure, and architecture problems that could drive up your application’s operational costs.
Tailored app audits that find code, AI, security, data, and performance bugs – or combine them all to perform full application assessments.
Analysis of vulnerabilities, access control holes, secrets exposure, unsafe inputs, and dependency risks in the AI-generated code.
SECURITY
Assess application structure, code organization, AI workflows, databases, APIs, and scalability for long-term maintainability.
ARCHITECTURE
Test the performance of your model on accuracy, hallucinations, latency, consistency, drift, and output quality.
AI QUALITY
Review data quality, preprocessing, labeling, embeddings, retrieval, validation, and AI data pipelines for reliability.
DATA
Examine connections with LLMs, APIs, databases, cloud platforms, third-party tools, and internal systems.
INTEGRATION
Check the security, rate limiting, deployment, infrastructure, error handling, monitoring, and performance of growing loads on your API.
INFRASTRUCTURE
Identify unnecessary model calls, token waste, inefficient prompts, infrastructure overhead, and other avoidable AI expenses.
COST
FULL AI APPLICATION ASSESSMENT
Tell us how your AI-built application was developed and what concerns you have. We’ll identify the audit areas that deserve attention first.
Request an Audit →Our AI code audit services focus on the dimensions that will decide success. It doesn’t matter if your AI-based application is secure, reliable, scalable, and ready to be used by real-world users.
DIMENSION · CODE QUALITY
Structure of code, code duplication, maintainability, error handling, tests, dependencies, and technical debt that is introduced via AI-driven coding.
DIMENSION · SECURITY
Authentication, authorization, leaked credentials, API security, data access, prompt injection, insecure outputs, and other security issues of AI applications.
DIMENSION · AI PERFORMANCE
Accuracy of the model, hallucinations, response consistency, latency, behavior on edge cases, evaluation of models, and performance on real-world data.
DIMENSION · DATA
Data validation, preprocessing, labeling, embeddings, retrieval, data leakage, synchronization, and pipeline performance affecting AI outputs.
DIMENSION · ARCHITECTURE
Code organization, APIs, databases, orchestration of AI, third-party services, scalability, fault-tolerance, and maintainability of the codebase.
DIMENSION · COST & SCALE
API calls, token usage, choice of the model, caching, utilization of infrastructure, response time, and cost-efficiency as the application usage increases.
The five-stage non-disruptive process that helps to audit AI apps for code quality, security, performance, scalability, and AI reliability. According to reliable AI development companies, production changes are not introduced without your permission.
Learn about your application, AI-generated parts, business logic, technology stack, integrations, and development process.
Check the code generated by the AI, architecture, APIs, dependencies, database schema, and other development-related technical aspects.
Evaluate the AI model, prompt engineering, workflow, training data, outputs, data management, and AI-generated code reliability.
Find out any vulnerabilities and risks, such as insecure code generated by the AI, data exposure, compliance gaps, dependency issues, etc.
Provide you with an audit report with all findings, risk levels, recommendations, and an action plan to improve your AI app.
We get involved at all stages, be it validating a new AI application before launch or fixing issues with a stalled product in production.
Talk About Your Case Study →Validation of a new AI product before launch
Auditing applications developed using AI code generators
Due Diligence before an acquisition or investment
Savings on LLM / Inference costs
Fixing accuracy drift in production models
Security assessment before deploying to enterprise
Migration of vendor (for example, moving from one LLM provider to another)
Preparation to scale by 10×
We adapt the audit to your data sensitivity, AI use case, integrations, security requirements, and operational risks according to industry needs.
Being a trusted AI development company, we audit AI-built applications across the models, code, data, integrations, and infrastructure that power them.
Audit scope
AI MODELS
AI FRAMEWORKS
CODE & DATA
INFRA & DEPLOYMENT
Hire AI developers to build an AI app security audit that identifies code quality issues, security gaps, weak architecture decisions, and compliance risks. We significantly audit AI-built apps throughout its codebase, architecture, security controls, data handling, and compliance readiness.
Request an AI App Audit →AI-generated code quality & vulnerabilities
AssessedArchitecture flaws & scalability risks
AssessedPrompt injection & jailbreak resistance
AssessedSensitive data exposure through AI outputs
FlaggedPII handling in prompts, logs & embeddings
AssessedOWASP Top 10 for LLM Applications
AssessedAuthentication, authorization & AI endpoint security
AssessedAPI keys, secrets & credential exposure
FlaggedGDPR & HIPAA readiness
AssessedThird-party AI model & API dependencies
Reviewed
AI software code audit helps identify AI-generated code errors, insecure patterns, duplicated logic, and technical weaknesses. These difficulties are detected before expensive production problems are created.
Before attackers reach them, AI software code audit detects prompt injection, data leakage, exposed secrets, weak access controls, and other AI-specific security gaps.
AI-generated code audit finds inefficient queries, unnecessary model calls, memory issues, and architectural bottlenecks. These can slow down the application as usage increases.
AI app architecture audit replaces sensitive AI-generated code with cleaner and more maintainable services. This will make developments in future easier and reduce repeated fixes.
AI-generated application audit genuinely understands where your application stands against relevant privacy, security, and regulatory requirements. It also documents the gaps very clearly.
With an AI-built application audit, businesses get a practical action plan showing what to fix first. It also shows why it matters and where your development team should focus next.
Our main motive is to build production software, so our audits focus on real code, real risks, and fixes your team can act on.
Experts who understand AI-generated code and application risks.
Reviewing code, architecture, APIs, AI integrations, and security.
Recommendations based on your app—not a specific AI vendor.
Clear findings ranked by technical and business impact.
Still have questions? Our AI audit team can answer them on a short call.
AI application code review services can uncover serious issues before they become expensive redevelopments, no matter whether the app:
It is particularly useful when the team lacks visibility into code quality, architecture, security, or AI integrations.
Yes, we can discover problems in AI-generated code by reviewing code for:
Auditing can be helpful in separating code that works today. It also helps find code that is safe, reliable, and suitable for continued development.
You receive documented findings with their technical impact, priority, and recommended next steps. Your team can use the report internally or work with us on remediation. This gives you a practical path from identifying problems to improving the application's stability and security.
Yes, an AI software security audit can help businesses identify technical weaknesses. These issues include:
However, an AI application security assessment cannot predict every future failure, but it can reduce known technical risks before launch.
Yes, we can audit your app built by another development team. This is because auditing doesn’t require the original development team. We simply go through the existing codebase, architecture, integrations, security controls, and technical documentation. All these can give you an objective assessment of the application's current condition.
Discover how our clients have achieved success, watch their authentic video testimonials and see the results for yourself
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