Choose what to get done
SaaS magic number
Your SaaS magic number (annualized new revenue over prior-quarter sales-and-marketing spend) with an efficiency band telling you whether to scale acquisition.
Score a content piece on the STEPPS virality framework
The buyer gets a complete STEPPS scorecard: all six factors rated on the agreed scale, each with a stated rationale tied to the content, plus a computed total.
Score a set of OKRs (0.0-1.0) and run the six classic-trap litmus checks
You get your OKR set scored on the 0.0-1.0 scale (each objective = the average of its key-result completion rates), each objective color-banded on the Google red/yellow/green scale, and a structural pass/fail against the six classic OKR-writing traps.
Score a term sheet's economic terms clause-by-clause
A structured JSON scorecard that classifies every required economic clause of the term sheet onto a three-tier favorability scale and computes a weighted founder-friendliness index.
Score AI model process and tool maturity into bands
A team assessing whether an AI model is mature enough to sell as a service gets a process-maturity band and a tool/system-maturity band computed directly from per-phase level scores, ready to feed the AIaaS feasibility decision.
Score an AI idea's business feasibility on 1-4 scales
A founder comparing AI product ideas gets a defensible 1-4 score on each business-feasibility dimension and an average, derived from concrete inputs (SOM, usage cadence, validation %, scalability), so ideas can be ranked on a like-for-like basis.
Score and rank candidate pricing metrics on the six-criteria rubric
I get a filled scorecard where every candidate metric is rated 1-5 on all six criteria with a weighted total and a clear rank order, so I can pick the key pricing variable defensibly.
Score and rank causes by importance, tractability, neglectedness
A function that takes a list of candidate causes each rated on importance (scale/severity), tractability (feasibility of progress), and neglectedness (how underfunded), and returns each cause's composite priority score plus a stable descending rank.
Score Problem Candidates on the Ikigai Four-Lens Fit
A founder receives a structured four-lens score for each candidate problem and a shortlist of those that clear every lens, so they pick a problem to focus on rather than a buzzword.
Screen Startup Against Incubator/Accelerator Eligibility Criteria
A founder receives a structured eligibility screen showing, criterion by criterion, whether the startup qualifies for a given incubator or accelerator program and whether it clears the overall gate.
SETDA AI Outcome Discovery Register
A product team running AI discovery gets a structured register of candidate AI outcomes, each correctly categorized (revenue / cost / risk) and mapped to a Sense/Explain/Think/Decide/Act method, with needs and requirements broken out per the SETDA framework.
Shared value opportunity register
A validated shared value opportunity register where every opportunity has both a business benefit and a societal benefit, is mapped to a pathway, spans at least 2 distinct pathways, and has a feasibility tier.
You are not what you make. You are the one who can make it.
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