Build a Data Platform for Small Research Labs

1. 1

   Wedge in through instrument capture

   The daily pain is walking results off instruments by USB stick. A small agent that watches the instrument PC's export folder, parses the common output formats, and files results to organized, searchable cloud storage with sample metadata is the product labs feel in week one. Support the ten most common instrument types first, not all of them.

2. 2

   Version protocols like code, explained like science

   The folded-in second lane: protocols with real versions, diffs a biologist can read, fork-and-merge for lab variants, and a link from every result to the exact protocol version that produced it. That linkage (which run used which method) is the reproducibility feature reviewers and PIs actually want.

3. 3

   Make preservation the compliance story

   The folded-in third lane: immutable backup with retention rules, and one-click export packages shaped for funder data-management plans and repository deposits. Since the NIH policy took effect in 2023, every grant needs this story; being the lab's easiest honest answer to it is the budget line you occupy.

4. 4

   Price for grant budgets

   Per-lab monthly pricing that fits inside a grant's other-expenses line without procurement review, with an institutional tier when a department wants twenty labs. The buyer is a PI spending grant money; make the invoice fit how grants spend.

5. 5

   Sell through the people labs already trust

   Core facility managers, research-computing offices, and library data-services teams field data-management questions weekly and have no product to point small labs at that fits their budget. Pilot with two or three labs at one institution and let the internal recommendation network do what cold outreach cannot.

6. 6

   Coexist with the incumbents deliberately

   Institutions license big electronic lab notebooks; you are the layer those deployments skip: instrument capture, protocol versioning, and preservation for labs that will not live in a heavyweight ELN. Integrate and export freely; lock-in fear kills sales in academia, and open export is a feature you advertise, not a risk.

7. 7

   Handle sensitive data honestly

   Human-subjects and clinical-adjacent data carry IRB, HIPAA, and institutional security requirements. Either meet those bars deliberately (encryption, access logs, agreements) or scope the product to non-human-subjects research and say so; ambiguity here ends university deals.

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