Every number traces back to the exact rows that made it

Messy spreadsheet in. Traceable dashboard out.

Row Sight reads your real export — accounting, a CRM, an e-commerce or billing report, a field-service dump, or a sheet you keep by hand — asks a few quick questions about your business, proposes a plan you approve, then returns a clean, multi-section dashboard plus a downloadable audit workbook. Ask follow-up questions in plain English and every answer still traces back to your data. Built for the people who run the business, not just the data team.

Show me revenue trends by region
Revenue by regionMargin by monthFlag rows with missing dataTop customers this quarter
Q3_export_final(2).xlsx
DateCustomerAmtCat
3/2/24Acme$1,240.00
2024-03-05acme inc980ops
#REF!Beta LLC1,2kOps
5-Mar(420)
03/11/2024Gamma Co2200SALES
mixed date formats#REF! errorsrefunds as text
Row Sight
plan · approve · compute
Clean · reconciled · traceable
Net revenue · Q3
$1,284,920
+8.4%
Gross margin
38.4%
Orders
4,182
every figure sourcedaudit workbook attached
Reads the exports you already have
QuickBooksXeroFreshBooksSageNetSuiteWaveStripeSquarePayPalChargebeeShopifyWooCommerceBigCommerceMagentoEtsyAmazon SellerSalesforceHubSpotPipedriveZoho CRMMailchimpKlaviyoGoogle AdsMeta AdsGoogle AnalyticsGoogle SheetsMicrosoft ExcelAirtableSmartsheetNotionServiceTitanJobberHousecall ProZendeskIntercomGustoADPWorkdayAsanaJiraMonday.comToastLightspeedTableauLookerAmplitude
How it works

From messy sheet to dashboard you can defend.

Four steps. No formulas, no pivot tables, no black box.

csv
xlsx
tsv
01Upload

Drop in your messy export

Excel or CSV from the tool you already use — mixed date formats, blank cells, refunds typed as text and all.

Analysis plan
Net revenue
Gross margin
Orders by region
Approve plan
02Approve

AI plans it, you approve

It profiles your columns, asks a couple of plain-English questions, and proposes exactly what it will compute. Nothing runs until you say go.

= SUM(F2:F4183)
$1,284,920
03Compute

Real code does the math

A deterministic engine executes the approved plan. Identical on every run — the AI never types the number itself.

Net revenue
$1.28M
every figure sourced
04Trust

Get a traceable dashboard

A clean, multi-section dashboard plus a downloadable audit workbook — every figure links back to the rows that made it.

Not a chart maker

Not another chat-with-a-CSV toy.

Generic chart tools and CSV chatbots guess. Row Sight proves. Where Julius, Polymer, and Copilot for Excel stop, the audit trail begins.

The chat-with-a-CSV trap
  • Numbers you can't verify or reproduce
  • Answers that change every time you ask
  • No trail from the chart back to the data
  • One chart at a time — no real structure
  • Every session starts from zero
Row Sight
  • Real calculations — identical on every run
  • A downloadable audit workbook, every time
  • Every metric traces to its exact source rows
  • A structured, multi-section dashboard
  • A Solution Trail of every decision — yours and the analyst's
Every figure links back to the source rows and the formula that produced it.
= SUM(Ledger!H2:H4183)
What you get

Everything traces back to the data.

A snapshot of what Row Sight produces on every run — no black boxes, no numbers you can't defend.

Traceable metrics

Hover any figure to see the formula and the exact rows behind it. No number appears without a source.

Net revenuetrace
$1,284,920
= SUM(Sales[Amount]) · 4,182 rows

Solution Trail

A git-log of the whole analysis — every decision you made and every one the AI made, in order.

youApproved the plan
analystComputed net revenue
flagFlagged 12 rows

Data Profile

Row Sight reads the shape of your data first — column types, roles, and quality flags — before it plans.

ColumnTypeMiss
Datedate0%
Amountcurrency0%
Categorytext0.3%

Audit workbook

Download an Excel workbook where every figure ships with its formula, source rows, and an assumptions log.

xlsx
rowsight_audit_Q3.xlsx
formulas · source rows · assumptions

Multi-section dashboards

Not one chart at a time — a structured dashboard with KPIs, trends, and breakdowns you can actually present.

Continuation chat

Keep asking follow-up questions after the analysis is done. Every answer still traces back to your data.

Why did margin dip in April?
COGS rose 6% — traced to rows 812–840.
The output

A dashboard you can defend in the meeting.

Hover any figure to see the formula and rows behind it. The Solution Trail shows every decision; the audit workbook ships it all in one file.

Q3_export_final(2).xlsx Row Sight dashboard
traceable
Net revenuetrace
$0
Gross margintrace
0.0%
Orderstrace
0
Rows flaggedtrace
0
Revenue & margin by monthRevenueMargin
JanFebMarAprMayJunJulAugSep
Revenue by category
Wholesale$540,120
Retail$421,880
Services$322,920
AI summary

Revenue rose 8.4% through Q3, led by Wholesale at $540k. 12 rows were missing a category and were flagged in the Data Profile before totals were computed.

xlsx
rowsight_audit_Q3.xlsx
Every figure above, with its formula, source rows, and an assumptions log.
Who it's for

Made for everyone who lives in spreadsheets.

A solo founder, a logistics team, a nonprofit, an agency — if your answers are trapped in a messy export, Row Sight turns them into something you can defend.

LogisticsIndustry

Shipment, cost, and on-time metrics from carrier and TMS exports.

OperationsRole

Turn a weekly ops or TMS export into a reconciled dashboard — no manual rebuild.

E-commerceIndustry

Revenue, margin, and category mix from Shopify or POS exports.

FinanceRole

Close-ready numbers where every figure ties back to its source row and formula.

SaaSIndustry

MRR, retention, and cohort views from a billing export — every number traceable.

FoundersRole

Board and investor numbers you can defend line by line.

HealthcareIndustry

Clean, auditable rollups from claims or scheduling exports.

Sales / RevOpsRole

Pipeline and quota rollups from a CRM export, traceable to every deal.

NonprofitsIndustry

Grant and donor reports funders will actually trust.

MarketingRole

Channel and campaign performance from exported reports, cleaned and charted.

Field servicesIndustry

Job, revenue, and technician metrics from field-service exports.

ConsultantsRole

Hand clients an auditable dashboard from whatever messy file they send you.

EducationIndustry

Enrollment and outcome reporting from a student-data export.

Built for teams who defend numbers

The outcome every team is after.

Honestly, I used to dread the Monday report. Now I drop in the export, sanity-check the plan, and it's done — and when someone asks where a number came from, I just show them the rows.
An operations lead
The part that won me over was the audit workbook. Every figure has its formula and source rows sitting right next to it, so “where did this come from?” just stopped being a conversation.
A finance manager
I've wrestled with the same messy export for years. First thing that handed me numbers back clean enough to put in front of investors without triple-checking every cell.
A startup founder
I stopped stitching three exports into one cursed tab. Channel performance just shows up now, and I can see exactly which numbers came from where.
A marketing lead
Our quota rollup used to be a haunted spreadsheet nobody trusted. Now every deal inside the number is one click from its source row.
A RevOps analyst
Clients send me the ugliest files imaginable. I hand back a dashboard they can take straight to their board — with a trail behind every figure.
An independent consultant
Shopify export in, margin by category out. Best part is I can prove every figure the second my accountant starts asking questions.
An e-commerce owner
Grant reporting used to eat a whole week. Now the numbers tie back to the rows, and our funders actually trust what we send.
A nonprofit director
On-time rate and cost per lane, straight from the carrier export — without me building yet another pivot table at 9pm.
A logistics manager
Your data

Your data stays explainable after the chart is made.

This is the part generic chart tools skip: definitions, exceptions, source boundaries, and reviewer-ready evidence.

01
Data boundary

The raw file stays separate from the story.

Row Sight keeps the working set, reviewer notes, and presentation output distinct. You can explain the dashboard without dumping every raw row into the room.

Example
Project scope
01
Source file: Q3_export_final.xlsx
02
Presentation view: dashboard only
03
Reviewer access: project members
04
Raw rows: available for audit
Why it matters

People can review the evidence path without turning every meeting into a raw spreadsheet inspection.

02
Definition ledger

Business definitions are captured beside the numbers.

Revenue, margin, churn, utilization, and region logic are not left as implied spreadsheet folklore. The chosen definitions travel with the result.

Example
Metric glossary
01
Net revenue excludes refunds
02
Gross margin uses landed COGS
03
Cohorts use invoice month
04
Blank region stays unassigned
Why it matters

When two teams disagree, the conversation can start from the actual definition instead of reverse-engineering the chart.

03
Quality flags

Messy rows are called out instead of washed into an average.

The section earns trust by naming the weak spots: missing dates, duplicate IDs, negative quantities, text in currency columns, and outlier rows that deserve a second look.

Example
Exception register
01
17 rows missing region
02
3 duplicate invoice IDs
03
12 negative quantity values
04
6 currency cells stored as text
Why it matters

A clean-looking dashboard is risky if the dirty rows disappeared silently. The exceptions stay visible.

04
Sensitive context

The dashboard does not need to expose every identifier.

A usable analysis can point back to source evidence without turning customer names, employee notes, or free-text fields into the main artifact.

Example
Presentation boundary
01
Show customer segment, not email
02
Use source row reference for lookup
03
Keep notes out of chart labels
04
Expose raw values only in audit view
Why it matters

The presentation can stay focused on decisions while the source file remains available for people with the right context.

05
Challenge packet

When someone asks why, the answer is already packaged.

Every defensible number needs more than a pretty chart. Row Sight keeps the formula, row range, assumptions, and exception notes close enough to answer follow-up questions fast.

Example
Reviewer packet
01
Formula used
02
Rows included and excluded
03
Assumptions that changed output
04
Exceptions worth reviewing
Why it matters

Follow-up questions do not restart the analysis. The proof packet is already attached to the result.

Pricing

Full audit trail on every plan.

An analysis is one upload or one file update. Both plans run the same engine and the same premium AI models — Pro raises the limits, nothing else changes.

Free
$0forever
3 analyses / month
  • Full guided analysis workspace
  • Audit workbook on every run
  • Full source-row traceability
  • Same premium AI models as Pro
Start free
Most popular
Pro
$19/mo
50 analyses / month
  • Everything in Free
  • Unlimited follow-up chat
  • 25 pipeline restarts per day
  • Self-service billing portal
Start with Pro
FAQ

Questions, answered.

What files can I upload?+

Excel (.xlsx) and CSV exports from just about anywhere — accounting, a CRM, e-commerce or billing reports, an HRIS, a field-service tool, or a sheet you keep by hand. Mixed date formats, blank cells, and numbers typed as text are fine — Row Sight profiles and handles them.

How do I know the numbers are right?+

The AI plans the analysis; real code computes it. Every figure traces back to its exact source rows and the formula that produced it, and ships in a downloadable audit workbook anyone can check.

Does Row Sight change my data?+

No. It reads your file and records any assumptions it has to make — like an ambiguous “5-Mar” date — in an assumptions log. Your original export is never overwritten.

Do I need SQL or to be an analyst?+

No. Ask in plain English, approve the plan Row Sight proposes, and get a structured dashboard. It's built for the people who run the business, not just data teams.

What counts as an “analysis”?+

One upload or one file update. Follow-up questions, chart tweaks, and inline answers about an existing analysis are always free.

Is my data private?+

Each analysis runs in your own project space, behind your account, and every result stays fully auditable by you.

Stop trusting numbers you can’t trace.

Bring one messy export. Get a clean dashboard and a full audit trail — in the time it takes to make coffee.