The #1 question we get

“Can’t I just paste this into ChatGPT?”

An LLM reads. IACalc computes. Here’s what that difference means for your investment committee.

Paste into ChatGPT

Run through IACalc

✗ ReproducibilityAsk three times, get three different answers. Output varies with temperature, model version, and prompt phrasing.

✓ ReproducibilitySame document, same result. Every time. Published formulas, defined inputs, deterministic code.

✗ Source traceabilityProduces a number. Cannot show which table cell it came from or whether it confused net income with EBITDA.

✓ Source traceabilityEvery value traces to a page, table, and cell. Audit companion shows method, confidence, and extraction state.

✗ Contamination resistanceMay confuse P&L revenue with DCF equity value. Processes text, not table semantics.

✓ Contamination resistance4-layer firewall classifies each table by type. Valuation assumptions never contaminate financial actuals.

✗ Intent-aware judgmentApplies generic financial knowledge. Same answer regardless of your investment thesis.

✓ Intent-aware judgmentEvaluates every signal against thresholds calibrated to your thesis. Same data, different mandate, different verdict.

✗ Cross-method verificationOne answer. No way to cross-check against an independent source.

✓ Cross-method verificationMultiple extractors run in parallel. When two methods agree within 1%, the data is marked verified.

The difference between a tool that sounds like an analyst and a system that works like one.

Going deeper

Five things an LLM cannot do.

ChatGPT doesn't run Altman Z-Scores

IACalc runs 42+ structured financial calculators — Altman Z-Score, Beneish M-Score, DuPont decomposition, FCF conversion, and forensic metrics — with documented formulas and defined inputs. An LLM guesses ratios from training data.

ChatGPT doesn't calibrate thresholds to your thesis

IACalc adjusts 250+ signal thresholds based on your stated investment intent. A yield buyer and a turnaround buyer see different verdicts from the same data — because different fears apply.

ChatGPT doesn't cite source pages

IACalc traces every extracted value to a source page, table, and cell in the original document. The audit companion shows extraction method, confidence rating, and verification state.

ChatGPT doesn't produce committee-ready output

IACalc produces a structured Investment Analysis Report — DOCX with severity badges, signal tables, source citations, counter-narrative analysis, and prioritised diligence questions. Not conversational text.

ChatGPT doesn't keep your documents secure

All IACalc inference routes through AWS Bedrock. Zero document content leaves the AWS account boundary. No data to external APIs. Fully automated pipeline with no manual review.

See the difference on a real document.

Request a walkthrough and we’ll show you a pre-run report you can compare against your own internal analysis.

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