Build faster for your clients.Protect the work that earned you the gig.
How Codira helps a software company ramp onto new client codebases faster, protect margin on fixed-bid work, and keep ai-generated bugs from landing in client demos.
For agencies, dev shops, and consultancies billing on client engagements — where every hour your team spends fighting ai output instead of shipping is a margin hit you can’t pass through.
The problem.What makes agency work different.
You don’t have one product, one codebase, one team that knows it inside-out. You have a portfolio of engagements, each with its own stack, its own inherited debt, its own deadline you’re billing against. The economics are unforgiving in different ways than a SaaS company’s.
Every project is a new codebase
Margin pressure squeezes every hour
Quality bugs are reputational
Hiring is hard, juniors take time
Built for engineers who ship for clients,not for vibes.
Codira is a native desktop app for macOS and Windows, built around a team of ten specialized ai agents — instead of asking one model to be good at everything, each phase of building hands off to the agent optimized for it: planning, implementation, code review, security scan, test generation, codebase Q&A, failure diagnosis, design review.
On top of that, six deterministic checks run on every patch. These aren’t more ai deciding if the code is OK — they’re TypeScript parsers that catch the failure modes ai patches silently ship: dropped exports, hallucinated imports, placeholder code that looks finished but does nothing, mass rewrites disguised as small edits.
For an agency, the most important word in that paragraph is silently. Bugs you can’t see are bugs the client finds. Codira’s job is to make sure they don’t leave your shop.
Day to day.What changes for a client engagement.
Five concrete shifts your team will feel on the next project you start.
/explain, gets a 5-section guided tour: stack, architecture, entry points, conventions, suggested follow-ups. The first billable hour turns into a real understanding instead of a Tuesday-of-week-2 still-grepping-for-where-auth-lives./plan: ordered steps, the files to change and what success looks like, reviewed before code is written. Every hour that saves is margin on fixed-bid work, or another billable hour on hourly contracts. Your call.An illustration.The math, with your numbers.
The agency math is different from a product company’s. Hours saved aren’t just labor-cost savings — they’re either margin you keep (fixed-bid) or revenue you bill (hourly). If Codira saved each engineer one hour a day at a $150/hr billable rate, here’s how it would add up. Swap in your own figures.
Comparing tools.What matters most for client work.
Agency engineers need specific things: ramp onto unfamiliar codebases fast, catch bugs before the client demo, train juniors without senior bandwidth being the bottleneck. Here’s what Codira does, and the question to put to anything you’re weighing it against.
| For client work… | Codira | Ask the alternative |
|---|---|---|
| Onboarding to new codebases | /explain — five-part guided tour, file:line refs | How does it help someone new to the code? |
| Patch verification | 6 deterministic guards + Reviewer agent | What checks a patch before it lands? |
| Runtime checks | UAT auto-fires after every apply, looks for errors in the running app | What runs after a change is applied? |
| Failure analysis | Root cause + 2-3 fix candidates | Does a failure come with a cause, or just a retry? |
| Multi-agent architecture | 10 specialized agents, each with one job | Is one model doing every job? |
| Platform | Native desktop app for macOS and Windows | Does it run where your team works? |
Honesty.What Codira is not.
We’d rather you know up front than feel surprised mid-engagement.
Not white-label.
Not a senior-engineer replacement.
Not zero-friction.
Not for unsupervised junior delivery.
No Linux yet.
How to try it.Pilot on your next engagement.
The fastest way to know if Codira fits your shop is to put it to work on the next new client codebase that lands. Pick one engineer, one engagement, two sprints. Track these four numbers against your baseline:
First-meaningful-commit time
Margin per engagement
Bug escape rate
Junior ramp time
If the math doesn’t pencil for your shop, you walk away with two sprints of real data and we wish you well. If it does, you stay — and your next engagement starts faster than the last one.