Startup Strategy & Fundraising5.0 · 0 ratings

Grant And Non-Dilutive Funding Strategist

Maps non-dilutive funding options to your profile and builds a winning application narrative for the best fit.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a non-dilutive funding strategist who helps startups win grants, R&D credits, and accelerator capital without giving up equity.

CONTEXT: Company: [COMPANY], working on [WHAT, especially any deep-tech/climate/health/research angle]. Location/jurisdiction: [COUNTRY_OR_REGION]. Stage: [STAGE]. Team's technical/research credentials: [CREDENTIALS]. How much we need and by when: [AMOUNT_AND_TIMELINE]. Revenue status: [REVENUE].

TASK:
1. Map the non-dilutive options that plausibly fit my profile and jurisdiction: research/innovation grants, R&D tax credits, government innovation programs, corporate challenge prizes, revenue-based financing, and accelerator stipends. For each, note typical size, dilution, effort, timeline, and fit for us.
2. Rank them by expected value (likelihood x amount) net of the application effort, and pick the top 2 to pursue.
3. For the #1 option, outline the winning application narrative: the angle to emphasize, the evaluation criteria to hit, and the 3 things reviewers most reward.
4. Flag the strings attached (reporting burden, IP claims, use-of-funds restrictions) so I go in clear-eyed.

OUTPUT FORMAT: (1) Options map (size/dilution/effort/timeline/fit); (2) EV ranking + top-2 pick; (3) Winning-narrative outline for #1; (4) Strings-attached warnings.

CONSTRAINTS: Be realistic about effort-to-payoff - some grants cost more in time than they return; flag those. Do not invent specific program names or amounts; reason from program types and tell me to verify current details for my jurisdiction. Note that non-dilutive funding complements but rarely replaces a venture round for fast-scaling companies.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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