A structured diagnostic that pinpoints exactly what to fix in your code, architecture, and workflows before automation can deliver. You invest engineering effort where and when it actually unlocks output
Over 90% of developers use code-generation tools like ClaudeCode or Codex, yet fewer than 15% say the output consistently passes review on the first round. Without addressing the root cause, the conclusion is "this doesn't work for us" instead of "our codebase wasn't ready."
Inconsistent naming, tangled dependencies, sparse test coverage - these turn automation into a rework machine. Output that compiles but nobody wants to merge. Teams report 30-50% of generated PRs requiring non-trivial rework, often exceeding the time it takes to write the code manually.
Our engineers score your codebase against automation compatibility thresholds, across five dimensions:
Code Structure. How reliably generation tools can reproduce your naming and architectural patterns.
Dependency Complexity. How modular your dependency graph is for automated tooling.
Context Availability. Whether tribal knowledge - interface contracts, non-obvious decisions - is accessible to automated systems.
Integration Readiness. How your CI pipeline and review gates interact with generated output.
Test Coverage. How effectively your test suite can validate generated code.
Automation Compatibility Scorecard. Per-module ratings across all five dimensions - blockers, severity, and what "ready" looks like.
Prioritised Remediation Roadmap. Changes sequenced by automation impact, T-shirt sized (S/M/L) so your leads can slot them into sprint capacity directly.
90-Minute Technical Walkthrough. Live session with the engineers who ran the audit: findings, questions, and pressure-testing the roadmap against your priorities.
A brief discovery call to understand your stack, team structure, and automation goals. You grant read-only repository access.
For large codebases, we jointly identify the highest-priority modules.
Automated tooling runs static analysis on code structure, dependencies, and test coverage while engineers review documentation quality, CI workflows, and context availability in parallel.
Engineers consolidate findings into the scorecard, validate thresholds against your specific context, and build the prioritised remediation roadmap.
Every recommendation is pressure-tested by a second engineer for feasibility and sequencing.
The 90-minute live walkthrough with your team. We deliver the scorecard, roadmap, and all supporting analysis. Your team leaves with a clear, actionable plan.
The audit is built for teams with meaningful production codebases - typically 10+ engineers with at least a year of accumulated code. Smaller teams or very new codebases usually don't have enough structural complexity to warrant a formal assessment, though we're happy to discuss your situation on a scoping call.
Read-only access to the repositories in scope. We never write to your codebase, never copy code off your infrastructure, and work within whatever security and compliance requirements you have. If you require a specific access method (VPN, air-gapped environment, on-site), we accommodate it.
A code review tells you what's wrong with specific code. This tells you what to fix across your codebase to make automation work. We're measuring compatibility with how automated generation tools read, interpret, and produce code.
We support the major ecosystems: TypeScript/JavaScript, Python, Go, Java, Kotlin, Rust, C#, and Swift, across common frameworks (React, Next.js, Django, Spring, .NET, and others). If your stack includes something outside this list, raise it on the scoping call - we can confirm fit quickly.
No. The audit runs on read-only access against a snapshot of your current codebase. Your team continues shipping as normal. No branches locked, no merge freezes, no disruption.
Your senior engineers know the code - but they're optimising for human readability, not automation compatibility. These are different evaluation criteria. The five-dimension framework, the automation-specific thresholds, and the tooling that accelerates structural analysis across an entire codebase - that's what an external audit adds over a two-week internal effort.
You have a complete, actionable roadmap. Many teams take it and execute internally - the deliverables are designed to be self-contained. If you want Streamlogic to handle remediation engineering, we pick up exactly where the audit left off with full context already in place. Either path is a good outcome.
It's a fixed-fee engagement, scoped during the discovery call based on codebase size and complexity. No hourly billing, no open-ended retainers. We'll give you a firm number before you commit to anything.
Before Streamlogic stepped in, our media pipeline was already efficient. Now it's exceptional. Their team embedded a system that adapts, learns, and scales with our production flow. What used to take hours now takes minutes. What used to slip through cracks now comes out polished. We've seen a measurable lift in both output volume and content quality.
As a design-led studio, our work lives in the details - textures, lighting, growth patterns. Before Streamlogic, visualizing complex botanical installations meant hours of manual prep and rendering. They built us an automation layer that feels almost magical: it pulls data from our planning tools and generates near-final visuals in a fraction of the time. We gained headspace. Now my team spends more time designing, less time chasing files. And for the level of quality they delivered, the investment was fair and smart.
In the legal field, precision, security, and responsiveness are the baseline. What impressed us most about the team at Streamlogic was their discipline, structure, and proactive style of work.