Auction Systems & Automation

Software for the auction work that should not require heroics.

At McLemore, I build the internal platform that carries work from first intake through cataloging, bidder communication, invoicing, and closeout. The point is simple: make repeatable work quiet so people can spend judgment where judgment matters.

Operating map

Intake Leads, seller context, asset notes, photos, and first decisions.
Research Comparable sales, description drafts, category logic, and value signals.
Catalog Lots, titles, descriptions, images, terms, and publish readiness.
Routing Customer questions, staff handoffs, reminders, and next actions.
Closeout Invoices, payments, settlement, follow-up, and records.

What it handles

Catalog acceleration

Draft descriptions, normalize details, pull the useful bits forward, and keep catalog work moving without pretending the machine is the auctioneer.

Valuation support

Bring comparable-sale research and item context into the same workflow as the asset, so estimates are easier to review and explain.

Task routing

Turn loose operational signals into the next right owner, reminder, or status, instead of relying on memory and heroic Slack archaeology.

Communication workflow

Help staff answer routine questions, preserve context, and keep sellers, buyers, and internal teams from losing the thread.

Invoice and closeout flow

Move from auction result to invoice, payment, settlement, and records with fewer re-keyed facts and fewer ambiguous handoffs.

Operator visibility

Make the state of the work visible: what is stuck, what changed, what needs judgment, and what can safely be automated away.

Where AI fits

AI is useful in auction operations when it is close to the work and humble about its role. It can draft, summarize, classify, compare, and route. It should not replace the judgment calls that make an auction credible.

The best systems do not make the business feel futuristic. They make tomorrow morning feel less clogged.

Built in the work

These systems are not demos. They are built against the daily mess of estates, equipment, real estate, seller updates, bidder questions, invoices, settlements, and closeout. That is the advantage: the software learns from operations because it has to survive them.

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