Quality Audit
Catch Errors in Your Spec Sheets Before They Reach Your Customers
Every uploaded document gets checked for missing values, internal contradictions, and coverage gaps — before translation begins. You get a report of what needs attention, not a surprise in another language.
Five finding categories
Missing values, internal contradictions, unit mismatches, coverage gaps, and source normalizations — systematically checked on every document.
Source conflict detection
Catches contradictions between sections — a value in the summary that doesn’t match the data table, or a test standard attached to the wrong property.
Three review modes
Quick (auto-accept, confidence score), Standard (critical items need acknowledgment), or Strict (section-by-section verification). Match the review to the stakes.
Export with findings
PDF and DOCX exports include an optional audit appendix. Excel exports get a dedicated findings sheet alongside the structured data.
The audit compares structured extraction against the original source across five categories:
| Category | What it catches | Example |
|---|---|---|
| Missing values | Properties mentioned in the source but extracted without a value | "Flash Point" found in heading but no value detected in the data table |
| Internal contradictions | The same property appears with different values in different sections | DFT listed as 60–80 µm in summary but 50–75 µm in application table |
| Unit mismatches | A value’s unit doesn’t match the column header or expected format | Temperature column header says °C but a value is given in °F |
| Coverage gaps | Sections or data present in the source that aren’t reflected in the structured output | Source has 24 properties, extraction captured 22 — 2 flagged for review |
| Source normalizations | Inconsistencies in the source that were detected and standardized | Mixed use of "kg/L" and "kg/l" normalized to "kg/L" throughout |
Missing values
Properties mentioned in the source but extracted without a value
"Flash Point" found in heading but no value detected in the data table
Internal contradictions
The same property appears with different values in different sections
DFT listed as 60–80 µm in summary but 50–75 µm in application table
Unit mismatches
A value’s unit doesn’t match the column header or expected format
Temperature column header says °C but a value is given in °F
Coverage gaps
Sections or data present in the source that aren’t reflected in the structured output
Source has 24 properties, extraction captured 22 — 2 flagged for review
Source normalizations
Inconsistencies in the source that were detected and standardized
Mixed use of "kg/L" and "kg/l" normalized to "kg/L" throughout
Each finding has a severity level — critical issues that affect safety or correctness, warnings that might indicate a problem, and informational notes about unusual patterns. The audit reports what it found so you can decide how to handle each item.
Source conflicts that hide in plain sight
Internal contradictions in technical documents are more common than most companies realize. A spec sheet goes through multiple revisions, sometimes by different people. Values get updated in one section but not another. A table gets expanded but the summary paragraph above it still reflects the old data. These inconsistencies often survive internal review because each section looks fine in isolation — the contradiction only becomes visible when you compare them systematically.
Some real-world patterns the audit catches:
- A dry film thickness range in the general properties section that doesn't match the application table — the summary says 60–80 µm, but the table says 50–75 µm. Both can't be right, and an applicator following one while an inspector checks the other creates a compliance dispute.
- A missing recoat window in a multi-coat system specification — the topcoat TDS lists a minimum overcoating interval but the primer TDS doesn't. Whoever applies the primer in the field has no guidance on when the topcoat can go on.
- Test standard references that don't match the property they're attached to — an adhesion value listed with a hardness test standard, likely a copy-paste error from an adjacent row.
Why auditing before translation matters
Every error in your source document gets multiplied by the number of languages you translate into. A missing value in the English original becomes a missing value in German, French, Spanish, Italian, and every other target language. A contradictory specification in one language becomes a contradictory specification in fourteen.
Catching these issues before translation begins means you fix the problem once rather than fixing it in every language — or worse, shipping the error to every market and dealing with the consequences. This is especially important for safety-critical terminology where a contradictory value doesn't just look unprofessional but can affect how a product gets applied, installed, or operated.
Structured completeness as a Digital Product Passport foundation
The EU's Ecodesign for Sustainable Products Regulation (ESPR) is introducing Digital Product Passport requirements that will require manufacturers to provide structured, machine-readable product data in multiple languages. The first product categories — batteries, textiles, construction products — are already being defined in delegated acts.
While SpecMake isn't a DPP compliance tool, the audit serves as a practical first step toward DPP readiness. If your existing documentation has gaps — missing values, incomplete test references, inconsistent data across sections — the audit identifies exactly where those gaps are. Fixing them in your source documentation before you get to the formal DPP process saves significant effort downstream.
Think of it as a documentation health check. The same structured completeness that makes a spec sheet reliable for your customers also makes it ready for the structured data requirements that DPP will demand.
Related articles
Translation Errors That Cost Manufacturers Real Money
Five categories of spec sheet errors — and how catching them before translation prevents costly propagation.
Digital Product Passports and Technical Documentation
ESPR timelines, affected product categories, and what structured documentation means for compliance.
How Accurate Is AI Translation for Technical Documents?
Quality frameworks, terminology benchmarks, and where audit catches what AI translation misses.
How to Translate a Spec Sheet
Four methods compared — including the role of source auditing in each approach.
Coatings & Paints Translation
How the audit catches DFT mismatches, missing recoat windows, and inconsistent VOC data in coatings TDS.
Audit your first document for free
Upload a spec sheet and get a detailed quality report — missing values, contradictions, and coverage gaps identified automatically.
No credit card required. Your first document is free.