Aquila is a software development studio. We build the hard parts of AI products — the data and model pipelines, the platform underneath them, and the interface people actually use — in TypeScript, Go, and Rust.
Teams we have built for
What we do
FIG 0.1
Retrieval, agents, evaluation harnesses, inference pipelines. The hard part is rarely the model call — it is grounding the thing in your data and proving that it works.
FIG 0.2
APIs, data infrastructure, dashboards, auth, billing. The platform work that has to exist before an AI feature can become a product you can sell and support.
FIG 0.3
We take a brief and return working software. Design happens inside the build rather than as a separate handover, so what gets specified is what gets shipped.
How we build
A prototype that works on a laptop and a system that holds up under real traffic are different pieces of engineering. The second one is what we get hired for.
01
We work out what actually needs building, what the model has to do, and what "working" will mean in numbers you can check afterwards.
02
Architecture, pipelines, and interface together. Design happens inside the build rather than arriving as a handover.
03
Evaluation harnesses, load testing, and instrumentation, so behaviour is measured rather than assumed before it reaches anyone.
04
Deploy it, watch it under real traffic, and keep iterating once real users are in front of it.
Selected work
BoostSRBoostSR runs the growth playbook for Amazon brands. It connects to a brand's listings, sales reports, search query data, and ads account, then turns that signal into listing creative and managed ad execution — so the people running the account spend their time on decisions rather than on assembling spreadsheets.
We built the platform end to end, and continue to develop it.
boost-sr.comBacked by
Design
Plenty of technically sound software looks unfinished, and it costs more than people think. Users read the interface as evidence of the system behind it — if the surface looks careless, they assume the engineering is too. We design as we build, because it is the same job.
Real products carry real tables, thousands of rows, and awkward edge cases. An interface that only looks good on an empty state has not really been designed.
Loading, empty, error, and permission states get the same attention as the screens that show well in a pitch. Those are the ones people live in.
No handover, no Figma file waiting to be interpreted. The person choosing the spacing is the person writing the component, so it ships as drawn.
Stack
Static types catch whole categories of bug before a customer sees them, and all three compile to something you can reason about under load. That matters more than usual in AI systems, where the model is already the unpredictable part.
Product surfaces, APIs, and AI orchestration. Where the work is shaped by the interface and needs to move quickly without losing type safety.
Services that need throughput and simple operations. Boring to deploy and boring to run, which is what you want from infrastructure.
Where correctness and performance both have to hold at once, and the cost of getting it wrong is higher than the cost of the extra care.
Team
Aquila is deliberately small. There is no account layer between you and the engineering, and nobody is going to hand your project to a junior once the contract is signed. We work in your repository, your tracker, and your Slack rather than behind a wall.
Owns the technical side of a build: architecture, AI and data pipelines, and the production platform underneath them. Works in TypeScript, Go, and Rust.
Works closely with customers to translate their goals into a roadmap, with a focus on tech-enabled services. Owns product management and the account relationship through delivery.
FAQ
Get in touch
A half-hour call is usually enough to work out whether we are a good fit and what a first phase would look like. If we are not the right team for it, we will say so.
