How AI uses your business information, and where it goes wrong

• Part numbers and measurements that disagree across systems

  The same item has four identifiers and three kinds of size. Systems agree until a person or a machine has to pick one.

  4 min read

  2026-10-16

• What makes a B2B catalog ready for AI agents

  Facts that agree everywhere, dated, with an owner. Everything else is formatting.

  3 min read

  2026-10-16

• Does ChatGPT read PDF spec sheets? The PDF problem

  AI can read a public PDF. It is slower to trust an undated one two clicks from the page. Put the key facts in text and keep the PDF as proof.

  3 min read

  2026-10-07

Every article in this topicResearch focus areas

• Dealer directory data is wrong in more places than one

  One dealer is described in six places. No directory is the record, and a correction in one does not travel to the others.

  4 min read

  2026-10-16

• Duplicate business entities across dealer networks

  One physical location, three identities. Machines count them as three businesses.

  3 min read

  2026-10-16

• Dealer network data: who decides which fact is right

  A dealer network disagrees with itself by design. The fix is deciding, per fact, who wins.

  3 min read

  2026-10-16

Every article in this topicThe automotive research brief

• Trace a wrong AI answer to its source

  Every wrong answer came from somewhere. The work is finding the copy that was wrong first.

  3 min read

  2026-10-16

• Measuring AI answer accuracy against your own records

  An answer is accurate or not only relative to a record. Build the record first, then ask.

  3 min read

  2026-10-16

• Who can change a business's published facts

  Most of a company's public facts are writable by someone else. The first step is knowing by whom.

  3 min read

  2026-10-16

Every article in this topicThe Lehvel Observatory