# Desk log MMA-MDA-20260822

**Status:** First-party InfiniSynapse desk log (sanitized composite; not a customer extract)  
**Page:** https://infinisynapse.com/en/blog/multimodal-data-analysis  
**Run ID:** `MMA-MDA-20260822`  
**Date:** 2026-08-22 (Saturday)  
**Operator:** InfiniSynapse Data Team  
**Attestor:** William Zhu, InfiniSynapse cofounder ([GitHub @allwefantasy](https://github.com/allwefantasy))  
**Contact for contradictions:** zhuhl@infinisynapse.com

## What this file is

A downloadable record of a table-only recap versus a table plus a bound contract. Companions: [aggregate CSV](https://infinisynapse.com/blog-media/multimodal-data-analysis/downloads/aggregate-MMA-MDA-20260822.csv) and [verify script](https://infinisynapse.com/blog-media/multimodal-data-analysis/downloads/verify-MMA-MDA-20260822.py). It is **not** a named-logo customer case, a vendor bake-off, or a Stanford / FTC / IBM / Gartner experiment.

## Four-step method (reproducible)

1. Authorize the live orders table and the signed schedule. Sanitize first.
2. Bind the invoiced-rate column, discount-band section, and in-scope amendment.
3. Ask one goal: do signed bands match invoiced margin by SKU?
4. Open the plan, cited clauses, and filtered SKUs. Re-ask the same goal from a clean seat.

## Source and goal

| Field | Value |
|---|---|
| Sources | Sanitized 18-page MSA + 62,000-row orders replica |
| Standing goal | Do signed discount bands match invoiced margin by SKU, and which SKUs sit outside the schedule? |
| Contrast | Table-only vs table + contract |

## Results

| Retrieval state | Cited clauses opened | SKUs outside band located | Same-day re-ask possible |
|---|---|---|---|
| Table-only | 0 | 0 | 0 |
| Table + contract | 1 | 1 | 1 |

Wall-clock for the successful joint rerun: 9 minutes (warehouse time excluded). The clock started when the operator opened the standing goal and ended when both folders sat side by side with the cited clauses and the filtered SKUs open.

## What you may cite

- Artifact counts 0/0/0 → 1/1/1, 18-page MSA + 62,000-row orders on this run, ~9 min wall-clock, run ID

## What you may not claim

- Customer uplift %, a 40% cleaner margin list, official EEAT score, named-logo case, or that Stanford / FTC / IBM / Gartner / WAIC scored this run

## Independent context (not this run)

- [Stanford HAI AI Index](https://hai.stanford.edu/ai-index) (retrieved 2026-08-29)
- [OWASP Top 10 for LLM Applications](https://owasp.org/www-project-top-10-for-large-language-model-applications/) (retrieved 2026-08-29)
- [NIST AI Risk Management Framework](https://www.nist.gov/itl/ai-risk-management-framework) (retrieved 2026-08-29)
- [Google Cloud: What is AI?](https://cloud.google.com/discover/what-is-artificial-intelligence) (retrieved 2026-08-29)
- [Wikipedia multimodal learning](https://en.wikipedia.org/wiki/Multimodal_learning) (retrieved 2026-08-29)
- [Google Vertex AI documentation](https://cloud.google.com/vertex-ai/docs) (retrieved 2026-08-29)
- [Google Research publications](https://research.google/pubs/) (retrieved 2026-08-29)
- [U.S. Federal Trade Commission](https://www.ftc.gov/) (retrieved 2026-08-29)
- [IBM NLP overview](https://www.ibm.com/topics/natural-language-processing) (retrieved 2026-08-29)
- First-party homepage recognition only; self-described, not independently verified on this page: [2026 WAIC Future Tech OPC Excellence Award](https://infinisynapse.com/#recognition)

## Validation boundary

No independent third-party, media, or customer reproduction was known as of 2026-08-29. Reproduction requires definition, source, retrieval, query, run, artifact, table-only baseline, joint-path, privacy, retention, timing, and conflict-of-interest disclosures.