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Glossary

The terms behind the systems

Definitions used across our writing on custom software for machinery dealers — our own vocabulary first, then industry terms explained from the buyer’s side.

Our vocabulary

Catalog operations
The recurring work of keeping a multi-brand product catalog current — intake, verification, publication, history — measured in hours per year, not in features.
Deletability
The ability to remove or replace a system through a documented, tested exit path without losing business data or process continuity — we use a one-week removal exercise as the design test.
POC syndrome
Our name for the recurring pattern in which AI prototypes are funded and demonstrated but never given the ownership, integration work, or commercial commitment that production requires.
The data-model test
A pre-purchase proof: one difficult manufacturer, two product series, one historical price list and one current update — through the vendor's data model, ending in an export and a reversal.
The price-list update path
The eight steps between a manufacturer's new price book arriving and a salesperson quoting from it with confidence — intake to retained history, each with an owner.
The production gap
The work between a working prototype and a system running in production — verification, integration, security, operational ownership — which cheap prototyping makes more visible, not smaller.
The three layers of running cost
A way of splitting what a catalog-driven system costs after go-live: infrastructure, operations and availability (including mandatory upkeep), and capability development — only the last is discretionary.

Industry terms

CPQ (configure, price, quote)
The software category for configuring products, pricing them, and producing quotes — strongest where configuration is complex, volume justifies a product model, and the buyer controls the pricing logic.
Effective-dated pricing
Prices carry validity intervals, so the system can reconstruct the catalog state for any date — one half of reproducing an old quote; the other half is an immutable quote snapshot.
ETIM and BMEcat
The open classification standard (ETIM) and exchange format (BMEcat) for technical product data — useful where manufacturers apply them, absent where they don't.
EU Data Act (for software buyers)
EU regulation applicable since September 2025: switching and portability obligations for covered data-processing services, with regulated switching charges removed from January 2027. The right to switch is not the migration.
Golden set
A versioned reference set of real cases that model-dependent behavior is tested against before changes ship — alongside production monitoring, not instead of it.
Grounding vs. training
Grounding supplies client data to a model at request time without updating the model's weights; training changes the weights. The distinction answers whether data changes a model — not where it is processed, retained, or logged.
PIM (product information management)
The software category for maintaining one trusted product record — descriptions, attributes, media — across catalogs and channels.
Syndicai

Syndicai is a software engineering company. We design, build and operate AI systems for companies in Europe and the United States.

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Latest insights
  • What a quoting system costs to run
  • What to check before you sign
  • Enterprise CPQ vs custom: how to work out which one pays
  • What happens when the champion leaves
  • Who updates the price list?
  • The most valuable AI in dealer quoting isn't the AI that writes quotes
  • One app or four? How a machinery dealer should sequence quoting, stock, and service
  • Where an AI quoting system gets its prices — and whether your data is safe
  • Will your sales team actually use the AI quoting tool?
  • The data problem nobody quotes for in machinery-dealer AI
  • Why mid-market AI POCs fail to reach production — the structural diagnosis
  • Vendor pricing predicts production outcome — the engineering decision treated as procurement
  • Data engineering is the AI engineer most vendors don't hire
  • The on-call question — the engineering artifact that predicts AI production survival
  • Production wins are boring — what mid-market AI deployments quietly become
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