It started with a conversation
between friends.
Not on a trading floor. Not in front of VCs. On WhatsApp, when a friend sent us a PDF and asked: "Does this sound reasonable?"
A friend asked. We took a look.
We're a group of senior software engineers. We build complex AI systems, cloud architectures, SaaS platforms — that's our day job. AI isn't a buzzword to us, it's the tool we work with every single day.
Not long ago, a close friend reached out. He'd gotten a quote from a software development firm — roughly $92,000 to build a platform he'd described to us in a couple of sentences. He asked, modestly: "Does this look reasonable?"
We opened the PDF. Went through it in twenty minutes.
What we found in twenty minutes
A line item for an "AI module" worth about $22,000 — that was, in practice, a call to OpenAI's API. Real cost: roughly $55 a month.
An architecture designed for 500,000 concurrent users — for a product meant to serve an audience of about 500 people.
Three months of "research and discovery" that fully overlapped with the build phase — billed twice.
A proposal written in dense, deliberately technical language, with one purpose: making the client feel like they can't ask questions.
We told our friend: "Don't sign it. This is 40% over market."
He saved about $37,000. That same week.
Then more friends showed up.
Word got around. More friends sent us quotes. Then friends of friends. And every single time, without exception, one of two things happened: we found real padding — or we asked questions the client had no idea they needed to ask.
Questions like: "How many concurrent users do you actually expect?" or "Why does this quote include three months of DevOps for an app that could run on Cloudflare Workers for free?" — questions a senior engineer asks by default, but a non-technical founder doesn't even know exist.
We realized there was a structural problem here. Not "bad" vendors — an information asymmetry. The client doesn't know what to ask. The vendor knows exactly what not to answer.
Then came 2024–2025.
The AI tools we work with every day completely changed the cost of producing code. An MVP that cost roughly $54,000 in 2022 costs about $9,500–$16,000 today. That's not an anecdote. That's the reality we live in.
But software vendors? They didn't pass those savings to their clients. Some even raised prices — "because demand for AI experts is high." Clients were paying 2022 prices for code written in a fraction of the time with Cursor.
At that point we saw something very clear: a massive gap between what development actually costs and what clients are charged. A gap sitting there, out in the open, waiting for someone to build a business on it.
That's how CODEFAIR was born.
We saw a real business opportunity here: a large gap between real market pricing and what clients pay — and, on the other side, an audience that needed exactly the knowledge we have. The equation was simple — we just wanted to build it the right way from the start.
The first check — whether the price is fair and the technical plan actually solves the problem — stays completely free, no commitment, exactly like what we'd want someone to do for our friend. If you want someone to walk you through the findings on a call, that's a small, fixed fee you know upfront. And if you want us to represent you with the vendor through signing — that's also a fixed fee by project size, not a percentage, no surprises.
So yes — we do this to make money too. We're not ashamed of that. But the check that actually tells you whether your proposal is fair stays free — because that's what was missing when our friend sent us that PDF, and for anyone in that same spot today.
Who we actually are
Not consultants. Not middlemen. Engineers who build real products — and know exactly what they cost to build.
We build complex systems
Cloud architectures, SaaS products, AI engines, B2B platforms — that's our day job. We don't analyze quotes from the outside — we know the real costs from the inside.
We work with AI every day
Cursor, Claude, Codex, Copilot — these are our tools. We know exactly how many hours each one saves, and what that means for the cost of your project.
We know the US development market
Hourly rates, pricing norms, cloud platform costs — we live inside this market. When a quote strays from the norm, we spot it within minutes.
Simon Mira
Senior software engineer with 10+ years of experience building technology products. Co-Founder of AutoDida — an active business automation platform in Israel.
"The moment I realized this needed to be a real product was when the fifth friend in a row reached out with an inflated quote. I understood it wasn't a coincidence — it's a pattern. CODEFAIR is my chance to close that gap."
Our approach
An independent check on the price and the technical plan — the way we'd do it for a friend about to sign.
Two checks — price and plan
Knowing the price is high isn't enough. We also check whether the proposed technical solution actually solves the problem you described, or whether they're building you something overengineered that sets up another failed project. The check leans on real engineering knowledge and current US market data.
Zero conflict of interest — none
We don't build software, don't take vendor commissions, and don't refer you to "partners." A fixed fee, known upfront — you're our only client, so there's no reason for us to soften or inflate the picture.
Questions you didn't know to ask
Sometimes the padding isn't in the pricing — it's in the assumptions. "How many users, really?" "Why native and not a PWA?" "What exactly does maintenance cover?" — questions an engineer asks by default, that a regular consultant doesn't know to raise.
Full directness
We don't try to impress you with jargon. We tell you what we found, what it's costing you, and what to do about it. If the proposal you got is fair — we'll tell you that too, and we won't charge you a cent.
Got a quote?
Send it our way. We'll look at it the way we looked at our friend's.
Completely free. No padding found — you pay nothing.
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