These posts share ideas, tools, and lessons from the front lines of data, science, and AI—insights shaping Savvyn’s journey and designed to help life sciences teams work smarter and faster.
Not all errors are equal: formatting quirks are annoying, a bad percentage is serious, an invented subgroup kills trust. Savvyn Abstract Builder v2 tackles that with consistent voice and built-in conference rules — turning raw notes into structured, submission-ready abstracts.
A recent MIT report found that 95% of AI pilots fail. The winners won’t be the ones with the biggest models. They’ll be the ones that solve the stitching problem—wiring data, workflows, and expertise into systems that actually work.
Abstracts are short, painful, and always due yesterday, which makes them the perfect low-hanging fruit to test workflows and tools. So I built v1 of the Savvyn Abstract Builder: a Landbot–Zapier–Airtable–ChatGPT workflow that turns shorthand notes into structured drafts.
