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Dynamics NAV AI Assistant Sizing and Value Calculator

This calculator sizes a private AI assistant for Dynamics NAV from your user count and expected question volume. It outputs GPUs, token load, retrieval index size, hours saved and a simple payback, and every formula is visible.

Your numbers

users
35 %
questions
tokens
documents
pages
min
per hour
per GPU
tokens/s

Measured aggregate throughput for your model on your card.

one-time

Your results

GPUs needed (before redundancy)
1
Monthly net value after GPU cost
$15,756
Daily active users
31.5
Questions per day
252
Tokens per day
756,000
Peak concurrent requests
0.28
20% of daily questions in the busiest hour, about 20 seconds per request.
Retrieval index size
2.9491
Two chunks per page, 4096 bytes per vector, 50% overhead.
Hours saved per month
462 hrs
Monthly value of time saved
$17,556
Simple payback
2.9 months

Planning estimate only. Measure throughput on your own hardware, add redundancy for production and validate time savings in a pilot.

Save results:

GPUs needed vs questions per active user

Sweeps Questions per active user per day from 2 to 60, holding your other inputs fixed.

Get a sizing review for your NAV estate

Optional: share your inputs and we will sanity check the GPU count and rollout assumptions.

Optional. The tool and every export work without this. No spam.

How to use it

Set named users and the share who use the assistant on a typical day. Questions per user is the key driver; use the number of data requests people send to colleagues or run through SmartList-style workarounds today. Adjust tokens per question upward if answers cite documents. Enter a throughput you measured, not a marketing number.

  • Test two or three throughput values
  • Use the chart to see GPU steps
  • Keep time saved conservative
  • Share the export with finance

The formulas

Questions per day equal active users times questions each. Peak-hour tokens per second equal 20% of daily questions times tokens per question divided by 3600. GPUs equal that peak divided by per-GPU throughput, rounded up with a minimum of one. Value equals hours saved times loaded hourly cost, using 22 working days, minus GPU cost.

Reading the result

GPU count moves in steps, so the chart is a bar chart: a small rise in questions can add a card. Index size is modest for most NAV estates; model memory is the larger hardware driver. A negative net value means the case rests on factors outside this model, or that a simpler tool is a better fit.

Frequently Asked Questions

Why use a bar chart?

GPU count is a whole number that jumps when load crosses a capacity step. A bar chart shows those steps more honestly than a smooth line.

Is one GPU enough for production?

Often for small estates, but production usually wants redundancy or a fallback path. Decide based on how critical the assistant becomes.

How do I estimate minutes saved?

Time five typical tasks with and without the assistant in a pilot. Use the median, not the best case.

Does it include licences and staff time?

No. It covers GPU cost and one-time build cost only. Add operating labour and licences for a full total cost view.

If you want the inputs reviewed against your NAV environment, Netray can run a short sizing session with your IT team.

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