Ask your fleet data a question. Get answers through AI-powered conversation.
FASTER AI Analysts are five specialists covering comebacks, maintenance, warranty, lifecycle cost, and parts. Ask them what you'd ask a data analyst, if you had one.
The questions that sit on the list
Most fleet teams don't have a data analyst. So questions like these wait months for someone to have a free afternoon:
- Why does unit 4471 keep coming back for the same brake job?
- Did we pay for any repairs last quarter that were still under warranty?
- Which parts have gone up the most in price over the past three years?
- How much shop time went to comebacks last year?
With AI Analysts, you type the question and get the answer back, usually in seconds.
Analyst | Use it to | Try asking |
|---|---|---|
Comeback Repairs | Find vehicles that keep returning for the same repair, and get to the root cause | "Which assets had repeat repairs in the last 90 days?" |
Maintenance | See what's due and which assets are at risk of a breakdown | "Which assets are due for preventive maintenance in the next 7 days?" |
Asset & Warranty Coverage | Check coverage before you pay for a repair yourself | "How many assets are still under warranty?" |
Lifecycle Cost | Understand total cost of ownership and why a unit is flagged for replacement | "Why is this asset flagged for replacement?" |
Parts Inventory | Spot shortages before a vehicle sits waiting on a part | "Which parts are at risk of shortage based on current stock and reorder levels?" |
Try it on your own fleet
Book 20 minutes with us. Bring two or three questions about your fleet and we'll run them live.
Can you trust it?
AI Analysts can read your FASTER data but can't change it. They use FASTER's own definitions, so a comeback means the same thing in chat as it does in your reports.
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Handoff from Insights
Start with a dashboard, then ask the analyst
Open the Asset Replacement Analysis dashboard in FASTER Insights, find a flagged asset, and ask the Lifecycle Cost Analyst what's driving the recommendation.
No. If you can ask a coworker a question, you can use AI Analysts.
You can look back at your entire history, and you can specify the date range you want to look at; it’s fully dynamic.
The output responses are as good as your data is, think of it like a report but driven on natural language. So, if you have incorrect or missing data going into your system, that will show up in the AI responses coming out of the system. Missing data may be flagged, but incorrect data may be assumed as correct, unless it falls outside the norm which then may be flagged as an outlier
