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Digital health companies

Engineering support for digital health platforms

AI capability, data layer rebuilds, enterprise integrations and scaling work.

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Screenshot of a digital health platform Pashupatastra extended, using synthetic data
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We work in your repositories and process
Defined ownership boundaries
Handover planned into the engagement

Success creates a different set of engineering problems

What worked for two customers strains at twenty. The database becomes a bottleneck, every enterprise customer wants a different integration, and the team has no capacity for the work that would make the service easier to run.

Scenarios

Where we usually come in

Situation What we do
Adding AI to an existing platform Scope a first use case, assess whether the data supports it, build it as a service the platform can call rather than as a rewrite
The data layer needs rebuilding Assess what exists, design the target, migrate incrementally so the service keeps running
Every new customer needs a new integration Build an integration layer that isolates customer differences so the core product stops forking
The platform will not scale Identify the actual constraint, which is rarely where the team assumes, then rebuild that part
Enterprise security review is blocking a deal Close the gaps that matter, document the architecture and data flows, prepare the answers
A specialist capability is missing Take a defined area such as device connectivity, FHIR integration or the data platform, while your team continues on the product
In use

Before and after

Where a client permits it, showing the same view before and after the work is the most persuasive image on the page.

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Before
The platform view as it was before the engagement, using synthetic data
16:9 · Product screenshot, synthetic data only
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After
The same view after the rebuild, using synthetic data
16:9 · Product screenshot, synthetic data only

How we work alongside an in-house team

Most engagements here run beside an existing engineering team rather than replacing it. That works when the boundary is clear, so we agree at the start which areas we own, which interfaces we are working to, how code review and deployment are shared, and who makes the call when a design decision affects both sides. We work in your repositories, your pipelines and your ticketing system rather than asking you to adopt ours.

Common Questions

Frequently asked questions

Yes, and that is the usual arrangement. We take a defined area with clear interfaces, and agree ownership and review process before starting.

[CLIENT INPUT REQUIRED: confirm typical lead time to start an engagement.] Whatever the answer, a short technical review comes first, because starting without one tends to cost more time than it saves.

Yes, for your team rather than for us. Architecture notes, decision records and runbooks are part of the work.

That is a normal end point. We plan handover into the engagement rather than treating it as an exit.

Talk to us about your platform

Tell us where the constraint is and what it is blocking. That is usually enough to establish whether we can help.