New Research with Claude · Query millions of auction results from your own AI toolsGet Started
Guide · Classic-car appraisers & insurers

How classic-car appraisers and insurers find model-level values and track how prices moved

By ALT/FNDATA · October 2026 · 7 min read

An agreed-value policy and a classic-car appraisal both need two things a single recent sale cannot give you: a model-level market picture, and the direction prices have taken. One result is an anecdote. The connector lets you ask for the model index and the trend in plain language, and returns realized collector-car sales with the auction house, the date and a link on each.

Get your API keyConnect your assistant
YouMarket index: Porsche 911 2.7 RSAALT/FNDATAIllustrativeMedian $900,000market_index · n 140RM Sotheby's · 2024$1.22M↗Gooding · 2023$852,000↗Bonhams · 2022$690,000↗Every result links to the sale · auction house · date
The aha moment: ask in plain language, get a sourced answer
In short

Lead with the marque, model and year. Use market_index for a model-level band with its sample size, price_trend to show how the model moved for an agreed-value case, and price_check for a specific example. Every figure traces back to the sale, which is what an underwriter wants to see.

01How it works

Realized collector-car sales, asked for in plain language

The connector adds auction price data to your AI assistant. For cars the tools that matter are market_index for a model-level band, price_trend for movement over time, price_check for a single car and market_stats for a marque or segment. Cars are one of the covered categories for the index and the single-item check. Results are normalized to USD and each links to the sale.

02The workflow

From a model to an agreed value

Start at the model level, show how it moved, then test the specific car against it.

1

Read the model-level index

Ask your assistant“Market index for the Porsche 911 Carrera 2.7 RS.”
Toolsmarket_index
What comes back

A precomputed band for the model: low, 25th percentile, median, 75th percentile and high, with the sample size and a trend read. This is the anchor for an agreed value, a defensible band rather than a single sale.

Tip. Specify the exact variant and year. A 2.7 RS is not a base 911 of the same year, and the index reflects the variant you name.
2

Show how the model moved

Ask your assistant“How have classic Ferrari values moved year by year?”
Toolsprice_trend
What comes back

Realized prices bucketed by year, with the count and median per period, so you can show an underwriter whether a model is appreciating, flat or softening. Narrow it to a specific model for a single-vehicle case.

Tip. For an agreed-value submission, pair the trend with the index band. The band sets the level, the trend justifies holding or revising it.
3

Test the specific car

Ask your assistant“Price-check a 1973 Porsche 911 Carrera RS 2.7 Touring.”
Toolsprice_check
What comes back

A fair-value range for that example from comparable realized sales, with the comparables and a confidence label. A well-specified car with a tight band reads high; the comparables each link to their sale.

Tip. Add the specification that drives value (Touring vs Lightweight, matching numbers). It narrows the comparables to genuinely similar cars.
4

Summarize a marque or segment

Ask your assistant“Market stats for Mercedes-Benz 300 SL sold since 2018.”
Toolsmarket_stats
What comes back

Count of sold lots, median, quartiles, average, range, the date span and leading houses by volume. A quick frame for a marque before you drill into one model.

Tip. Use a date window that matches the policy period you are pricing, so the summary reflects the relevant market.
03Reading the answer

Confidence, caveats and why the number is defensible

Confidence depends on how precisely the car is specified. A full model, variant and year reads high when the comparable band is tight; a loose request reads low and is flagged, and a genuinely wide spread of realized prices is flagged wide_quality_range and capped down. For an agreed value, the model-level index and the trend together are the stronger exhibit: a band with its sample size, plus the direction of travel, each traceable to the sales behind it. Read the sample size on an index the way you would read the number of comparables on an appraisal: a band built on many sales is sturdier than one built on a few.
04Honest limits

What the data does and does not cover

Note these boundaries when you value from the connector.

  • It reports realized auction results normalized to USD, not dealer asking prices or private sales.
  • Condition, originality, matching numbers and provenance move car values and vary by lot, so the data supports but does not replace a physical inspection.
  • Model-level index and single-item comparables cover cars, watches and handbags. Cars are fully covered here.
  • A thin model will have a small sample; read the sample size before relying on a narrow band.
  • It is market evidence for a valuation, not a formal appraisal or personalized financial advice.
05Getting started

Connect it once, then ask in plain language

Access requires a paid ALT/FNDATA API key. Create one in the app, connect it to your assistant with the setup page for your tool, then ask at the model level.

1Get an API keyPaid access in the ALT/FNDATA app. There is no free tier.2Add the connectorFollow the setup page for Claude, ChatGPT, Gemini, Perplexity or your tool.
3Ask awayUse the prompts above. Every result carries a source link you can cite.

Questions

Frequently asked questions

How is this better than one recent auction result?
A single sale is an anecdote. The model index gives a band (low, median, high) with a sample size, and the trend shows direction over time. Together they are a defensible basis for an agreed value, and both trace back to the sales behind them.
Can it value a specific car with its own spec?
Yes. price_check builds a range from comparable sales for a car you specify by marque, model, year and configuration, with a confidence label. The more precisely you specify it, the tighter and higher-confidence the result.
Does the data replace an inspection?
No. Condition and originality drive car values and vary by lot. The connector supplies the market evidence; the inspection and your judgment sit on top of it.
Are the prices realized or asking?
Realized collector-car auction results, normalized to USD, each with the auction house and sale date.
Is there a free version?
No. A paid ALT/FNDATA API key is required, created in the app.
Keep reading

Related guides

Valuing client collectiblesWatch comps and price trendsCollector market researchClassic cars dataset

Put a sourced number on it today.

Connect the ALT/FNDATA connector to the AI assistant you already use, and pull realized auction comparables, market statistics and price trends in plain language, each with a link to the sale.

Get your API keySee the setup pages

The ALT/FNDATA connector is read-only and returns realized auction results across 20 categories from 650+ auction houses, normalized to USD, each with the auction house, sale date and a source link. It reports what items sold for at auction, not retail or private-treaty prices. Methodology · All datasets · All guides