Pre-fundraise health check, two months before pitching.
Inspector runs parallel deep-dive assessments across eight core departments and ten strategic areas. It flags that unit economics are solid but the churn methodology is non-standard, the founder fixes the gap before any investor meeting, reducing diligence friction.
Run Inspector- 1
Describe the task
Inspector runs the diligence a Series A investor will run, before the investor does. It spins up parallel agents across your core departments and strategic areas, pulls evidence from the data you connect, and scores each dimension against the standard a partner-track associate would apply. You get the objections early, while there is still time to fix them.
The more concrete your prompt, the sharper the flags. Tell Inspector what stage you are raising at, which departments to weight hardest, and where the underlying data lives, and it will hold that lens across all eighteen dimensions instead of grading everything the same way.
Run a pre-fundraise health check for our company ahead of a Series A raise in ~2 months. Score all 18 dimensions across the eight departments and ten strategic areas. For each dimension: - Pull supporting evidence from the connected metrics-workbook.xlsx and cap-table.pdf - Score 0-100 with a one-line rationale and the evidence it rests on - Flag anything an investor is likely to challenge in diligence Weight unit economics, churn methodology, and gross margin hardest. Group results by score band (80-100, 50-70, below 50). End with a prioritised fix list ranked by diligence risk, and note which flags I can close before the first partner meeting.
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Give Inspector context
In an Inspector workspace, point the run at the folder holding your financials, metrics, and cap table. The departmental agents read them together, so the churn number the finance agent sees matches the one the growth agent scores against, no drift between departments.
Be explicit about how you currently define your headline metrics, especially churn and CAC. Inspector will flag a non-standard methodology as a diligence risk; giving it your definition up front lets it tell you exactly how an investor will re-cut the number.
Required contextA metrics workbook, MRR/ARR, churn, CAC, payback, gross margin by monthA short company description, stage, sector, current raise target, and use of fundsOptional contextCap table and prior financing terms, so Inspector can flag ownership and runway concernsA data-room folder, contracts, customer concentration, and cohort exports for deeper evidenceYour own metric definitions doc, so the scoring matches how you report internallymetrics-workbook.xlsxcap-table.pdfdata-room/ (optional) - 3
What Inspector creates
Inspector works through all eighteen dimensions in parallel, scoring each against the standard an investor applies and citing the evidence behind every number. You get a banded health report, a prioritised fix list ranked by diligence risk, and a short set of flags it could not confidently resolve from the data provided.
From Inspector: Scored 18 dimensions against metrics-workbook.xlsx and cap-table.pdf for a Series A readiness check.
18Dimensions scored14Scored 70 or above3Diligence risks flaggedScore 80-1009 dimensionsDimension Score Evidence Unit economics 90 CAC payback 11 months, LTV/CAC 4.2x across last 6 cohorts Gross margin 80 Blended 78%, stable month over month for 9 months Revenue growth 90 MRR up 3.1x trailing twelve months, net-new accelerating Score below 503 dimensionsDimension Score Flag Churn methodology 40 Logo churn counts paused accounts as active; investor will re-cut it higher Customer concentration 40 Top two accounts are 39% of ARR, no named contract renewal dates "Two dimensions I could not confidently score, sales pipeline conversion and support SLA attainment, had no underlying data in the connected files. Want me to draft the exact churn re-cut an investor will apply, or add those two data pulls to the run?"
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Follow-up prompts
Draft the churn re-cut before diligence
Inspector can restate churn the way a Series A investor will, so you walk into the meeting with the number already reconciled instead of getting surprised by it.
Re-cut our churn using standard SaaS methodology (exclude paused accounts, count logo and revenue churn separately, monthly cohorts). Show the delta vs our current number and the exact definition change.
Turn the fix list into a two-month plan
Route the prioritised flags into a dated plan so every diligence risk has an owner and a close-by date before the first partner meeting.
Convert the three flagged diligence risks into a two-month remediation plan with an owner, a target close date, and the evidence that would clear each flag.
Re-run monthly as the raise approaches
Save the setup as a runbook and schedule it, so you watch the flags close and catch new ones before you are in front of investors.
Save this as a runbook called "series-a-health-check", then re-run it on the first of each month against the latest metrics-workbook.xlsx and show me which flags changed since last run.
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Tips and troubleshooting
Give Inspector your metric definitions up front
The single most common diligence surprise is a headline metric defined non-standardly. If you tell Inspector how you currently calculate churn, CAC, and margin, it can tell you exactly how an investor will re-cut each one, rather than just flagging that they might.
Connect the data room, not just the summary deck
Scoring is only as good as the evidence behind it. A summary metrics tab gets you scores; the underlying cohort exports and contracts get you defensible scores that survive a partner pushing on them.
A "below 50" is a gift, not a verdict
Low scores this far out are the point, they are the objections you get to fix before they cost you the round. Treat the below-50 band as your prioritised work list, not a scorecard.
Ready to try it yourself?
Point Inspector at your financials and cap table, and get the exact diligence objections an investor will raise, two months before you are in the room to answer them.
Run Inspector