You are not buying a CV pile.
Hiring by resume means you carry the risk that the person on paper is not the person who shows up. We carry that risk instead, because we are accountable for the delivery, not for the seat being filled.
Model
How we work, and why
Most engineering suppliers sell you people. We sell you delivery. That difference is the whole model, and everything below is what falls out of it.
What bytehive is
A remote software engineering team, founded in 2019 and registered in Virginia Beach, Virginia. Twelve people, distributed across Europe and the US East Coast, who take product engineering work end to end: a technical lead who owns architecture and delivery, plus engineers who ship. More than fifty client projects behind us, nineteen of them told in full as case studies, and clients who kept us for years rather than sprints.
We sell capacity, not names
One delivery unit is one full-time stream of senior-grade delivery capacity, with the technical leadership already included. You size an engagement in units. Two full-time developers' worth of work is two units. What a unit never becomes is your staffing problem.
How each unit is composed is our call: one senior engineer, or a junior carrying the hours with a lead behind them, or a specialist rotated in for the weeks when the work matches something we have built before. You get the output either way, and the composition changes underneath you without a renegotiation.
The alternative
What you are not buying
You are not buying management overhead.
The technical lead is inside the unit price. Somebody already owns sprint planning, stack decisions, developer blockers and the conversation with you. On all but one project in our portfolio, the delivery process was ours to run, not yours to supervise.
You are not buying one person's calendar.
A new client rarely brings us a problem nobody here has built before. Whoever carried the similar build joins the planning, so the experience transfers to your project without waiting for that person to be free.
You are not buying a black box.
We work alongside your engineers, in your repositories, in your standups if you want us there. Embedded, not thrown over a wall.
Commercials
How you pay for it
Three models, all the same underlying number expressed differently, so they cannot contradict each other:
Monthly, per unit.
The default for ongoing embedded work. You reserve N units, we hold the capacity.
Hourly, time and materials.
For a defined project. Parallel workstreams agreed with you bill as parallel units. We take this when there is enough work to keep the capacity busy, because half-filled capacity serves neither of us.
Fixed price.
For limited, tightly scoped work we have discussed properly. We take it when the scope is real and we hold the line on it, which is the only way fixed price is honest.
Invoicing runs in US dollars through Bytehive Technologies LLC.
Evidence
Vetting, without the theatre
We do not send CVs, and we do not put engineers through per-developer panel interviews. The unit is staffed dynamically, so a CV would be a promise about a seat we may fill differently next month. What we offer instead is better evidence:
A technical conversation with the lead who would own your delivery.
Not a salesperson, not a pre-sales engineer. The person accountable for the work.
A scoped pilot at our normal rate.
A real piece of your backlog, delivered, before anybody signs anything long.
The work itself.
Nineteen case studies on this site, and a public Upwork profile where the hours and the client reviews are logged by the platform rather than by us.
If your procurement process has a hard gate that needs a named profile, we will provide one for the engagement's lead.
AI in practice
How we actually use AI
We build with AI, we build AI products, and we set client teams up to work this way themselves. Those are three different things and we keep them separate:
How we build.
Coding tools, in-repo skills and agents in every repository. It makes us faster, and we price accordingly rather than pretending the last three years did not happen. What matters more is that the same team built this portfolio's hardest applications by hand before any of that existed, so the speed rests on fundamentals rather than on a model.
Products we build with AI in them.
Applications where the model is part of the product rather than part of our toolchain. The same engineering standards apply, and the parts that have to be exactly right are still built to be exactly right.
Teams we set up to work this way.
Tooling, in-repo skills and the working habits, handed to your engineers so the practice stays after we leave.