CASE STUDY · Franklin Discovery™ by entigenlogic®
Taking a patented AI model from the lab to the market.
Brand, message, investor story, and go-to-market for a neurosymbolic model built for the work that can't be wrong.

TL;DR
- 01
A patented neurosymbolic AI model, years ahead of a market that had finally caught up, told in engineering terms across five product names.
- 02
Brought back in by the CTO I'd worked with at Cleversafe and IBM. One brand, five products folded in as use cases, a message built from voice-of-customer interviews.
- 03
Positioned for mission-critical, regulated work where a wrong answer costs more than the software, in the space between open models and generative AI.
- 04
CMO on the executive team: investor decks, market sizing, next verticals, board presentations, and the story now rolling out on the website and LinkedIn.
Most marketers will never launch an AI model. I'm launching one. Franklin Discovery is a patented neurosymbolic model, a hybrid approach that pairs contextual understanding of your own documents with frontier models for fast evaluation. It finds the right answer, shows you where it came from, and doesn't make things up. In a market drowning in AI products that are mostly a prompt and a logo, that's a different animal. It needed to be sold like one.
I knew Tom Shirley, the CTO, from Cleversafe and IBM. When it was time to take the model to market, he brought me back in. What I walked into was a technology built over years, patented and finished, and a market that had only just caught up to it. The story was still being told in engineering terms, across five separately named products. No brand for Franklin Discovery. No shared language for what it was. The hard part was done. Now marketing and sales had to catch up to the technology.
We ran a series of workshops with the founding team and made one structural call that simplified everything after it: one brand, Franklin Discovery, with the five products folded in as use cases like train and search. Then voice-of-customer interviews, because AI is broad and this model isn't for the average use case. It's for mission-critical work in legal, compliance, and regulated industries, where a wrong answer costs more than the software. We positioned it in the sweet spot between open models and generative AI, and we kept it out of the technical weeds. That's the message running across the website and LinkedIn right now, ahead of paid programs.
As CMO, I sit on the executive team and present at board meetings. I built the investor decks and the financials behind them, sized the addressable markets, and mapped the next verticals. Franklin Discovery went from five names and no brand to one story told the same way to customers, investors, and the board, and it's building traction from a standing start with a model the market is finally ready for.