I graded NVDA's Q1 FY2027 earnings call for credibility by cross referencing guidance claims against actual financial data

I've been working on something and was hoping for honest feedback from real world practitioners/modelers. 

I've been wondering if there is a way to systematically validate the credibility of
management guidance on company earnings calls to facilitate potential
adjustments to assumptions used in DCF or other valuation models that might
reference management guidance.

So I built a process that pulls the transcript and checks major claims against
actual 8-K numbers. Each claim receives a verdict and the earnings call itself,
an overall letter grade A through F.

I tested NVDA's Q1 FY27 call and it came out a "B".

Reported revenue, data center, gross margins all checked out and confirmed against the 8-K.

But there were four things flagged:

1. Q2 guidance of 91B achievable but assumes zero China and perfect execution (Blackwell) - so instead of an initial $89-93B range, I might model $85B downside scenario.

2. The $20B Vera CPU claim had no revenue history behind it, so
treating that as upside only not base case.

3. VeraRubin Q3 ramp - Kress said too early to call.

4. $1T Blackwell/Rubin visibility over 3 years needs
sustained 80%+ growth which is a big assumption.

So a "B" and not an "A" because of those four, but nothing
contradicted so not lower than B either.

Curious if anyone would actually use something like this or if I'm solving a problem
that doesn't exist.

Thinking about building it out for all S&P 500 calls. The value-add would be scale and timeliness in terms of analyzing key claims and then recommending model adjustments if the claims are not credible or supported etc. Over time it could also reveal a trend with regard to the management team itself (do they usually get things right, wrong or are they 50/50 in terms of what they predict in their forward guidance etc.).

Not investment advice, methodology is transcript Vs 8K cross reference.