We take on work where getting the details wrong is expensive: patient data, money, machines on a production line.
We have spent years inside hospital workflows: OPD queues, IPD beds, billing packages, pharmacy and the lab. We build software that fits how hospitals actually run, and we connect it to the machines they already own.
Money software is unforgiving. A rounding error is a support ticket; a race condition is a loss. We build financial platforms with ledgers that reconcile, permissions that hold up to review, and integrations that fail safely.
Factories cannot wait for the cloud to come back up. We design monitoring systems that run on the plant network, survive power cuts and noisy wiring, and tell maintenance teams about a failing machine before it stops the line.
Writing the code is half the job. The other half is deployments that do not break on Friday evening, backups that actually restore, and someone who notices when a certificate is about to expire. We run production for our own products and yours.
A demo takes an afternoon. Making AI dependable inside a business process takes engineering: the right data, guardrails, evaluation, cost control and a fallback for when the model is wrong. We add AI where it removes real work.
We build complete products: the admin panel, the customer app, the API between them and the reports the owner asks for at month end. Fixed scope when the requirements are clear, a dedicated team when they are still moving.
AI tools make it easy to build a first version. They do not tell you about the open admin route, the missing database index or the payment webhook that runs twice. We audit what you have, fix what matters and keep the parts that work.
Our founder led precision-agriculture work with earth-observation imagery before starting Amsa. We build pipelines that turn satellite, drone and survey data into maps and numbers people can act on.