revelations

academia is just fundamentally different from industry.

two relevant events:

1. speaking to aarjav during the cofounder matching event in boston, where we discussed the importance of industry-level validation and practical de-risking strategies beyond academic proof-of-concept.

2. talking to the bateup lab @ uc berkeley. turns out they only have 6 iphone images, yes, 6 IPHONE IMAGES taken behind a brightfield lens of organoids. they said these images can stress test. no thanks. yeah they don't do manual qc at all. just like salk institute.

revelations:

automated non-invasive qc for brain organoids has extremely inconsistent and averagely low demand in academia. what they want is not even the platform (evidenced by UCI's response, stressing co-authorship over free platform access) but publication/citation index. some of their unwillingness to collaborate with a venture due to political strains kills momentum. and the identification of labs that can provide their unique, specialized cortical brightfield data is a battle that needs to expand and continue beyond salk and umass IF...

if the hypothesis regarding adopting a completely novel platform is feasible for industry manufacturers. Take a random CRO—if they already have vendor solutions, is their solution bad enough that a specialized cortical segmentation tool can drive them to abandon their current automation methods and switch over to a webapp? how does the onboarding work? can file uploads be automated? do they already have specialized cortical brightfield image intake AND segmentation solutions? what microscopes are they using? is hardware agnosticism even necessary if there is high variability in how each manufacturer deals with brightfield QC? are they even doing brightfield vs. confocal?

academic use case is not scalable. everything is pointing toward industry, which is where the most revenue-driving customers are. talking to them will bring clarity and conviction.

several things to understand from them:

how does your current workflow work?

what is your QC pain point and what would you want to see? if it's the time and resources, know the exact quantity to better calculate hypothetical solution pricing to save their cost and drive up our revenue.

how should the proposed solution take shape—segmentation + predictor, or just the latter? how can it be integrated—standardized platform vs. integrated vendor model?

what would be the adoption potential for whatever solution we create? probability comparison between vendor integration vs. standardized platform?

getting the answers to these questions is the next fundamental step toward clarity for everyone: me, potential cofounder, and investors.

two possible directions:

• if a custom base model (harmonization + segmentation + feature extraction) is necessary, we need to build toward this internal tool to enable downstream capability developments. getting more diverse brightfield cortical data would make sense. securing DUAs with top labs is necessary for progress and due diligence. applying to an accelerator would make more sense.
• if specialized segmentation and feature extraction already exist for each manufacturer, we can skip the entire first step and aim straight for predictor development. funding would be a bigger hurdle but would shift focus toward VCs and angels. funding becomes the main game, not academic partnerships. a prototype for the predictor needs to be built. heavy reliance on UMass Amherst for endpoint data generation. the first round of funding (larger than typical accelerator grants) would extend runway and enable SRAs, LOIs, and commercialization.

either way, after this round of clarity gathering, i will have a much better picture of whether i should pivot or stay in lane with the current standardized platform idea. the ideal would be a platform, not vendor integration, to centralize our user base. these questions need to be designed in a sharper way.

and right now is the time for someone to hop in to help with validation—and that person is going to be a cofounder. i2i moves too slow. i need to move faster with someone actually committed to join. nothing to build yet—just information gathering. volume of CROs isn’t the issue. the challenge is getting them on a call and extracting the crucial answers that define our next steps.

i need an architect who designs these questions, understands what i’m going through, and starts joining me on this journey.

what i've just covered isn’t enough. there are more intricacies on the technical side that need to be considered. i’m caring too much about both macro and micro. i need someone to care more about the micro while i focus on the macro—not because macro is easier, but because it defines the overall direction once the details are clear.

i’m still early, and i was too optimistic about the fundraising timeline. school is taking a lot of energy. this solo battle needs to end soon. i'm drained and need someone to help refuel momentum.

hopefully that person comes soon.

aarjav brings experience from previous product cycles. there is runway until may 2026. i need someone to hop on the train so we can start large-scale market validation—this time toward industry, as every major academic lab has suggested.