Why Avanest

Promises you can hold us to.

Every studio says it is experienced, passionate and quality-driven. None of that is checkable. These are commitments specific enough that you would know if we broke one.

You own all of it

Source code, infrastructure config and documentation transfer to you on final payment. We keep no licence and reuse none of it elsewhere. You should be able to leave.

Ownership terms

A price before anyone writes code

Fixed price per phase, agreed up front, with a decision point at every phase boundary. No hourly meter, no invoice that surprises you.

How pricing works

Your data never trains a model

We use provider configurations that exclude your inputs from training, and we tell you in writing which providers touch what. If it cannot leave your infrastructure, we design for self-hosted models.

Data handling

We will talk you out of it

A lot of work pitched as AI is better served by a database query or better-designed software. We say so, even when saying so costs us the project.

When we decline work

The people who scope it build it

No account managers, no handoff to a delivery team you have not met, no subcontracting. The person on your first call is the person writing the code.

What happens next

Measured, not demoed

Every AI feature ships with an evaluation set — real inputs with known-good outputs, run on every change. That is how we can tell you what it gets wrong instead of showing you three examples that work.

How we evaluate

Six disciplines, one team

Web, mobile, desktop, ERP and SaaS under one roof. Nobody is coordinating three vendors and arbitrating whose fault the integration is.

What we build

We are still there after launch

Model providers deprecate versions and real usage drifts from what you tested. We monitor and maintain, or hand over the tooling to do it yourselves — documented either way.

The Operate stage

Speed & cost

Fast and efficient, for reasons we can show you.

Every studio claims to be quick and good value. Rather than give you a multiple nobody can verify, here is the actual mechanism — check it against how your last project went.

Where the speed comes from

AI does the mechanical work

Scaffolding, test coverage, migrations, documentation, refactors across hundreds of files. Work that used to consume weeks of billable time now takes hours, so more of your budget goes to the parts that need judgement.

No coordination tax

One small senior team covering design, backend, frontend and infrastructure. Nothing waits on a handoff between agencies, and nobody is arbitrating whose fault the integration is.

Working software in weeks

You see it running early rather than reading a document about it. Most timeline is lost to building the wrong thing carefully — seeing it early is what prevents that.

Decisions do not queue

The person who scoped your project is the person writing the code. A question gets answered the same day instead of being routed through an account manager.

Where your money goes

No overhead layer

No account managers, no sales engineers, no bench to keep busy. A far higher share of what you pay is someone building your product.

You can stop at any phase

Fixed price per phase with a decision point at each boundary. Your exposure is the current phase, not the whole project — which is a very different risk profile from a twelve-month contract.

The second year costs less

Evaluation sets and clean boundaries around model calls mean changes stay cheap. Systems nobody dares touch are the genuinely expensive kind, and they do not look expensive on day one.

No lock-in, no licence fees

You own the code and infrastructure outright. Nothing is rented from us, and you are not paying anyone to keep the lights on afterwards.

What actually moves the number

Most attempts to control software cost target the wrong things. These are the levers that genuinely change what a project costs, and we will point you at them before you ask:

Narrow the first phase to the single most valuable thing, and let the rest follow evidence.
Bring your data in whatever state it is in — cleaning it up first is usually wasted effort until we know what the system needs.
Use your existing infrastructure and vendors where they work. We have no incentive to migrate you.
Take the handover. If your team can run it after launch, do not pay us a retainer to do it.

We will not be the lowest quote you receive. We will tell you before you spend anything whether the budget you have can build the thing you want.

The alternatives

We are not always the right answer.

You have four realistic options and each wins in different circumstances. If one of the others fits your situation better, take it.

Option	Best when	The cost of it
Hire in-house	This is permanent core capability, and you can absorb three to six months of recruiting before anything ships.	Slowest to start, highest fixed cost, hardest to reverse.
A large consultancy	You need scale, formal procurement, or coverage across many workstreams at once.	The people who sell it are rarely the people who build it, and you pay for the structure around them.
A freelancer	The task is narrow, well specified, and you can manage it technically yourself.	One person is a single point of failure, and breadth across design, backend and ops is rare.
A small studio like us	The problem is not fully defined yet, AI is genuinely part of it, and you want a senior team that owns the outcome end to end.	We are not the cheapest, and we do not scale to twenty parallel workstreams.

Test one of these on us.

Bring the problem and push on whichever commitment matters most to you. If we cannot back it up in a conversation, none of it was worth writing down.

Worth reading first: who we work best with, and who should hire someone else.

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