# SSRS Estate AI Assistant Sizing and Value Calculator

> Source: https://netray.co/tools/ssrs-estate-ai-assistant-sizing-and-value-calculator
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: Free Tools

## Short answer

Size GPUs, report index and monthly value of a private AI assistant over an SSRS estate from users and question volume.

## Category

on-prem-ai

## Erp

SQL Server Reporting Services

## Audience

- CIO
- BI developer
- IT manager
- Finance

## Tool

**Kind:** calculator

**Currency:** $

**Inputs:**

#### Report consumers

**Key:** users

**Type:** number

**Default:** 400

**Min:** 1

**Step:** 25

**Unit:** users

#### Share active on a given day

**Key:** dau_pct

**Type:** slider

**Default:** 20

**Min:** 5

**Max:** 100

**Step:** 5

**Unit:** %

#### Questions per active user per day

**Key:** q_per_user

**Type:** number

**Default:** 5

**Min:** 1

**Step:** 1

**Unit:** questions

#### Prompt plus answer tokens per question

**Key:** tokens_per_q

**Type:** number

**Default:** 5000

**Min:** 200

**Step:** 100

**Unit:** tokens

**Help:** Summarising CSV output adds many prompt tokens. Cap rows returned to the model.

#### Reports and documents to index

**Key:** docs

**Type:** number

**Default:** 1500

**Min:** 0

**Step:** 100

**Unit:** items

#### Average pages of text per item

**Key:** pages

**Type:** number

**Default:** 2

**Min:** 1

**Step:** 1

**Unit:** pages

**Help:** Dataset queries, parameter prompts and descriptions as page equivalents.

#### Minutes saved per question

**Key:** mins_saved

**Type:** number

**Default:** 7

**Min:** 0

**Step:** 1

**Unit:** min

**Help:** Finding a report and filling parameters often takes longer than asking.

#### Loaded hourly cost

**Key:** hourly

**Type:** number

**Default:** 40

**Min:** 0

**Step:** 1

**Unit:** per hour

#### GPU monthly cost

**Key:** gpu_month

**Type:** number

**Default:** 1800

**Min:** 0

**Step:** 100

**Unit:** per GPU

#### Sustained tokens per second per GPU

**Key:** tps_gpu

**Type:** number

**Default:** 1200

**Min:** 100

**Step:** 100

**Unit:** tokens/s

#### One-time build cost

**Key:** build_cost

**Type:** number

**Default:** 40000

**Min:** 0

**Step:** 5000

**Unit:** one-time

**Outputs:**

#### Daily active users

**Key:** active

**Expr:** users * dau_pct / 100

**Format:** decimal

#### Questions per day

**Key:** q_day

**Expr:** active * q_per_user

**Format:** integer

#### Tokens per day

**Key:** tokens_day

**Expr:** q_day * tokens_per_q

**Format:** integer

#### Peak concurrent requests

**Key:** peak_conc

**Expr:** q_day * 0.2 / 3600 * 20

**Format:** decimal

#### GPUs needed (before redundancy)

**Key:** gpus

**Expr:** max(1, ceil(q_day * 0.2 * tokens_per_q / 3600 / tps_gpu))

**Format:** integer

**Primary:** true

#### Metadata index size (MB)

**Key:** index_mb

**Expr:** docs * pages * 2 * 4096 * 1.5 / 1000000

**Format:** decimal

**Description:** Two chunks per page-equivalent, 4096 bytes per vector, 50% overhead, in megabytes.

#### Hours saved per month

**Key:** hours_month

**Expr:** q_day * 22 * mins_saved / 60

**Format:** hours

#### Monthly value of time saved

**Key:** value

**Expr:** hours_month * hourly

**Format:** currency

#### Monthly net value after GPU cost

**Key:** net

**Expr:** value - gpus * gpu_month

**Format:** currency

**Primary:** true

#### Simple payback

**Key:** payback

**Expr:** if(gt(net, 0), build_cost / net, 0)

**Format:** months

**Chart:**

#### GPUs needed vs tokens per question

**Type:** line

**X:** tokens_per_q

**From:** 500

**To:** 20000

**Steps:** 20

**Series:**

- gpus

**Disclaimer:** Planning estimate. Measure real throughput, cap data returned to the model and confirm time savings in a pilot.

## Content

**Intro:** Report assistants are light on index size but can be heavy on tokens, because summarising rendered data fills the prompt. This calculator shows how users, question volume and result size drive GPUs and value.

**Sections:**

#### How to use it

**Body:** Enter report consumers and the share who ask a question on a given day. A report assistant has lower usage than a general chat, so start low. Raise tokens per question if you plan to summarise large CSV output, and cap rows in the design. Minutes saved is often higher than for lookups because it includes finding the report and setting parameters.

**Bullets:**

- Start with 10 to 20% daily use
- Cap rows sent to the model
- Measure throughput on your card
- Use the chart to test result sizes

#### The formulas

**Body:** Questions per day equal active users times questions each. Peak tokens per second equal 20% of daily questions times tokens per question divided by 3600. GPUs equal that divided by throughput per GPU, rounded up, minimum one. Index size uses two chunks per page-equivalent at 4096 bytes per vector plus 50% overhead, shown in megabytes. Value uses 22 working days.

#### Reading the result

**Body:** Most SSRS estates need one GPU; the chart shows how result size can push that higher. If the case depends on large summaries, redesign to pre-aggregate or sample instead of buying more hardware. If net value is low, a better folder structure and search may already solve discovery.

**Cta:** If you want these inputs checked against your SSRS estate, Netray can review them with your BI and IT teams.

**Faq:**

#### Why is the index measured in megabytes?

**Answer:** A report catalog is small. Even thousands of reports produce a modest metadata index, so megabytes are the more useful unit here.

#### Why does token count matter so much?

**Answer:** Summarising rendered output puts the data into the prompt. Large tables raise tokens quickly, so limit rows or aggregate before sending to the model.

#### Can I model several departments?

**Answer:** Run it once per department, or sum users and questions for a single estimate. Usage patterns differ, so separate runs show where value concentrates.

#### Does it include report server load?

**Answer:** No. Running reports on behalf of users adds load to the report server and its data sources, which you should test separately.

## Search terms

SSRS AI sizing calculator, report assistant ROI calculator, private AI reporting GPU, LLM sizing for report users, on-prem AI payback, report search value calculator

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