Curalink
Fetches 100+ research papers per query with citation-backed AI responses — a production research assistant for medical teams.
Fetches 100+ research papers per query with citation-backed AI responses — a production research assistant for medical teams.
Curalink is live in production today. It was built the same way every CodeMyth project is: scoped honestly, built by a senior owner end to end, and shipped with real monitoring — not left as a prototype.
We're deliberately not the studio that quotes you a number and disappears until the deadline. Expect short, regular check-ins, staging access from early on, and a straight answer any time something turns out to be harder — or easier — than it looked at the start. If a piece of this isn't the right fit for your team, we'll say so directly rather than stretching the engagement to fill a quarter.
How we build it
Scope & validate
The core workflow mapped and validated before a line of code was written.
Build the core
Front end, back end and data layer built in parallel by the owning engineer.
Ship & measure
Deployed with monitoring in place, then iterated against real usage.
Frequently asked
For live, shipped work we're often happy to make an introduction or share more detail on a call — just ask.
Most new projects start from a pattern like this one, then get adapted to your specific data, users and constraints — nothing here is a rigid template.
Timelines vary by scope, but the pattern is consistent: a working staging build within the first couple of weeks, then iteration against real usage rather than a single big-bang launch.
Who this is for
- Teams in a similar space looking for a reference build
- Founders sizing up what a comparable engagement might look like for them
- Anyone deciding between building this in-house or bringing in outside help
What you walk away with
- A working reference for what a comparable build looks like
- Specific technologies and timelines you can benchmark against
Have a project like this?
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