galenry.Software that survives contact with reality
An engineering company building AI products and enterprise platforms. We design the architecture, ship the system, and hand it over documented.
Where we stand
- Stage
- Early
- Model
- Engineering-led
- Shipped
- 2 clients · 2 products
- Practices
- Six, one team
The clients: Appooppanthaadi and Dayone.
We will tell you honestly whether we are the right team before either of us spends money finding out.
Most software fails after the launch, not before it.
What goes wrong
The demo works. The launch goes out. Then the first real load arrives, an integration changes, and the system starts to come apart, usually in the part nobody owned.
What we do instead
We build the other way round: architecture first, constraints stated up front, and the boring choice where boring means it will still be running in five years. That holds for an AI product, an enterprise platform, or the infrastructure under both.
Why the name
Galen was a diagnostician. A treatment chosen before anyone has found the cause is a guess, and so is software built that way, so we find the root cause before we build anything.
Four things we hold to. The rules we apply when a decision is contested.
Production is the finish line
We plan for the load, the failure modes and the on-call rota from the first sprint, so launch is a milestone rather than an event.
AI where it earns its place
We reach for a model when it measurably beats the alternative, and we show you the measurement either way.
Built for the team who inherits it
Documented, tested, and conventional where convention is correct, so your engineers can extend the system without us.
Difficult things said early
If the scope or the deadline looks wrong, you hear it in week one, while it is still cheap to change.
Decisions we make before writing code. The difference between a system that holds and one that needs rewriting.
Where the AI’s answers come from
Your own content, with sources shown, and a person when nothing fits. Decide this before choosing a model, because tuning can’t fix a system that is free to guess.
More in AI Product Development
How customers stay apart
Enforced by the database rather than remembered by every feature. Moving to this once customers already have data is one of the harder migrations there is.
More in SaaS Product Engineering
How a change reaches production
The same checks in the same order, every time, with a way back. Set up first, so releasing never turns into an event of its own.
More in Cloud & DevOps Excellence
What wakes someone up
Slow responses and errors people actually see, rather than every spike on a chart. An alert nobody acts on teaches a team to ignore the next one.
More in Cloud & DevOps Excellence
The things you would ask on a first call. Answered here, so you can rule us out quickly if they’re wrong for you.
Where we are
Remote-first, registered in India, working across IST and overlapping European and US mornings.
Who owns the work
You do. Source, infrastructure definitions and documentation are yours, in your repositories.
Data and access
Least-privilege access, short-lived credentials, and no production data copied to local machines. We sign your NDA and DPA.
Sectors we know
Travel, SaaS, retail and fintech-adjacent platforms. We say so plainly when a domain is new to us.
How we contract
Fixed-scope phases or a monthly retainer. No lock-in period, and no tooling only we can operate.
Who you work with
The people on the first call are the people who do the work. We introduce them by name before you commit to anything.
Tell us what you’re trying to build. We’ll tell you where we’d start.
Bring an idea, a stalled project, or a system that has outgrown itself.
Send us a brief
The problem, what you have tried, and what success looks like. A few lines is enough to start.
Prefer email? contact@galenry.com
What happens next
- 01Reply within one business dayFrom one of our engineers.
- 02First call: 30 minutes, no deckA working call about the problem. We ask questions rather than present slides.
- 03An honest answerWhere we would start, or, if we are not the right team, who might be.