Architecture

Tech Audit & Architecture

Deep review of codebase, performance, security & system design.

What's included

  • Codebase review
  • Performance analysis
  • Security assessment
  • Architecture evaluation
  • Database review
  • Dependency audit
  • Written report with findings
Tech Audit & Architecture — service offered by Dharmendra Singh Yadav

Know What You're Working With

Whether you've inherited a codebase, you're about to make a large investment in an existing product, or you're just not sure why things keep breaking, a proper technical audit gives you a clear picture of where things stand and what needs attention.

What I Look At

Code quality and maintainability. Architecture decisions and whether they still make sense for where the product is today. Database design and query performance. Security vulnerabilities and common misconfigurations. Third-party dependencies and their update status. Infrastructure and deployment setup. Test coverage and whether tests actually catch the right things.

Performance Audit

If your application is slow, I find out why. This means profiling actual requests, analysing database queries, reviewing caching strategy, and checking frontend performance metrics. I give you specific issues with specific fixes, not generic recommendations.

Security Audit

I check for common vulnerabilities — injection flaws, authentication issues, exposed sensitive data, misconfigured permissions, outdated dependencies with known CVEs — and anything specific to your application's threat model.

The Deliverable

You get a written report that's actually readable — not 200 pages of auto-generated scanner output. It lists findings by severity, explains the risk of each one, and gives concrete recommendations for how to fix it. I walk you through it so nothing gets misunderstood.

Frequently asked

Code quality and structure, architecture and scaling limits, security posture, performance, test coverage, dependency health, and how deployable the system actually is. The output is a prioritised list with effort estimates.

One to two weeks for a typical codebase. Large or unusually tangled systems take longer, and knowing that early is itself part of the finding.

Rarely, and never as a first recommendation. Full rewrites fail more often than they succeed. Incremental improvement with clear boundaries almost always delivers more value with far less risk.

That is the usual case, and being unfamiliar with it is an advantage — it surfaces the assumptions the original team stopped noticing.

Let's talk.

Building production-grade SaaS, AI agents and mobile apps end-to-end.

Hiring for a senior role or have an interesting problem to solve? Drop a note — I read every message.