WAITLIST OPEN · WINDOWS · EST. 2026

Excel stops at
1,000,000 rows.
LocalSheet handles
250 million.

For analysts who work with big raw data files and can't — or won't — send them to the cloud.

Reconciliation Joins Dedup Diff Local AI Split & Append Anomaly Detection

No account  ·  No cloud  ·  Your data never leaves your machine

Muhammad Haroon Butt — AI Builder, LocalSheet
0max rows · no cloud
0%auto-match rate
$0cloud cost · ever
0savg query time
// The problem

Built for the files Excel
fundamentally can't handle.

01

Excel hits its limit

Caps at 1,048,576 rows — and slows down well before that. The files you actually work with don't fit.

02

Reconciliation is manual

Exact-match only. 30–40% of exceptions end up worked by hand. Multi-file recon across millions of rows isn't possible.

03

Every alternative requires the cloud

Cloud BI tools, data warehouses, AI analytics — all require you to upload your data. Your data can't leave. End of conversation.

04

Python works — for engineers

SQL and Python get the job done. Most analysts don't write code, don't want to, and shouldn't have to.

05

Splitting, stacking, and diffing is manual

Breaking big files apart, stacking monthly exports, or comparing two versions is tedious copy-paste work — and Excel's row cap makes the files themselves unworkable anyway.

// What LocalSheet does

Everything Excel should have built.
Offline. On your machine.

// 01 — SCALE

Handle data at scale

  • Open files up to 250M rows — CSV, Parquet, Excel, JSON, SQL dumps
  • Append — stack files vertically; columns auto-align by name even when they differ across files
  • Split — slice a big file into filtered subsets, or batch-split by column value (one file per country, per region) in a single action
  • Combine a folder of monthly exports into one clean table in one step — no copy-paste, no row cap
  • Cross-file joins: draw a line between columns to run a SQL join on two 60M-row files in seconds
  • Filter, sort, pivot, and chart at full scale without waiting or crashing
// 02 — RECONCILE

Reconcile and find problems

  • Multi-pass recon: exact → tolerance → fuzzy → grouped (one bank deposit = sum of many invoices). 85–95% auto-match rate.
  • Three-way chained recon: sale ↔ PSP ↔ bank deposit, PO ↔ goods receipt ↔ invoice, or any source chain. Reports exactly which leg broke.
  • Exception workbench: every unmatched row gets a deterministic reason — timing difference, amount mismatch, missing from one side, duplicate key, fee/rounding
  • Save a reconciliation once. Next month, drop in new files and re-run in one click.
  • "What changed?" diff: rows added, rows removed, cell-level changes with old→new values. On a 40M-row file in seconds.
  • Find near-duplicate payments across millions of rows — same vendor + amount + near date, different invoice number
  • Data quality report on open: null rates, type mismatches, leading zeros stripped, inconsistent date formats, orphan keys
  • Anomaly detection: Benford's Law, z-score outlier flags, period-over-period spikes, and gap/completeness checks
// 03 — LOCAL AI

Ask in plain English

  • "Reconcile sales.csv and stripe_payouts.csv on order_id, amounts may differ by fees, dates by a day or two — tell me what doesn't match." Done.
  • "What drove the revenue drop?" Breaks down the delta by dimension in seconds.
  • "Are there duplicate payments in this file?" Get a flagged result sheet.
  • Every analysis lands as a new sheet you can review, export, or build on
  • Advanced users can see and edit the SQL it generates
  • All AI runs locally and offline — no cloud model, no data exposure
// How it works

Three steps. Zero cloud.

STEP 01

Load your files

Drop in any format, any size. CSV, Parquet, Excel, JSON, SQL dumps. Nothing is uploaded.

STEP 02

Connect, split, stack, or ask

Define relationships visually, stack or slice sheets, or just type what you want done in plain English.

STEP 03

Get results as sheets

Every analysis, reconciliation, or AI answer lands as a new sheet. Review, export, or build on it.

trades_2026.localsheet LOCAL · 0 NETWORK CALLS
› ▍
● FILTER matched 1,284,902 rows scanned 250,000,000 in 0.41s RAM 2.1 GB · LOCAL
// Who it's for

If your work involves big raw data files,
LocalSheet is built for you.

  • Analysts doing reconciliation across two or more large files — bank, AP, intercompany, payment settlement, any domain, any industry
  • Anyone whose data cannot or should not be uploaded to a cloud service — data residency laws, IT upload restrictions, client confidentiality
  • Analysts who need to split big reports into smaller files, stack monthly exports, or diff two versions of a file
  • Analysts who get CSV or Excel exports from systems and need to do real work on them
  • Auditors and consultants working on client data that must stay on their machine
  • Anyone whose workflow involves Excel crashing, waiting, or hitting row limits
Muhammad Haroon Butt
Muhammad Haroon Butt AI Builder · LocalSheet
// Data privacy

"Your data stays on your
machine. Always."

No account required. No internet after install. No cloud sync. No telemetry. The AI model runs locally — it never phones home. Built for teams under data residency laws, corporate IT upload restrictions, and client confidentiality requirements.

// The competitive gap

Why analysts are stuck choosing between
too small and too expensive.

Capability Excel Cloud recon tools (BlackLine, FloQast) LocalSheet
Row limit1MUnlimited250M
Offline / local✓✗✓
Multi-pass recon + fuzzy + grouped✗✓✓
File diff / split / append at scale✗✗✓
Plain English setup✗✗✓
AI — local, offline✗✗✓
PriceOffice license$30K–$300K/yearSpreadsheet price
Setup timeInstant6-month IT projectMSI installer
Early access · Limited spots
250M rows.
Your laptop. Offline.

Early access is limited. Join the waitlist to be first in line when we open the doors.

No account  ·  No cloud  ·  Your data never leaves your machine