How fast do you deliver?

Most scripts in 3–7 days; static sites in 1–2 weeks.

Do I need to be technical?

No. You describe the task in plain English; I set it up on your files and hand you a Run button.

14-day tweaks included. Optional care plan available for ongoing checks and quick fixes.

Examples

See practical automations in action

Run each demo with sample data directly in your browser. Everything stays local—no upload required.

Clean messy duplicate contacts (25k+ rows)#

Merge contacts from multiple CSVs, normalize emails and names, and safely dedupe 25k–50k rows with a review report.

Runs as: Desktop buttonSaves 1–3 hrs/runBuilt in 3–4 days

Steps

Load 2–3 CSV exports (CRM, newsletter, spreadsheets)
Validate and normalize columns (emails, names, phones)
Lowercase + trim emails, strip whitespace & weird characters
Standardize name casing (e.g. "joHN" → "John")
Detect exact duplicates by email + phone
Generate a review table with "keep/merge/drop" decisions
Write out a cleaned, deduped master file and an audit log

See code excerpt

// Normalize name + email then dedupe
const { emailCol, fullNameCol, firstNameCol, lastNameCol } = resolveColumns(rows);
const seen = new Set<string>();
const out: Row[] = [];

for (const r of rows) {
  const email = (r[emailCol] || "").trim().toLowerCase();
  const name = fullNameCol && r[fullNameCol]
    ? r[fullNameCol]
    : `${firstNameCol ? r[firstNameCol] : ""} ${lastNameCol ? r[lastNameCol] : ""}`.trim();
  
  const cleanName = name.replace(/\s+/g," ").replace(/\b\w/g,m=>m.toUpperCase());
  const normalized = { ...r, email, name: cleanName };
  
  if (!email || !seen.has(email)) {
    if (email) seen.add(email);
    out.push(normalized);
  }
}

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Elapsed: 00:00.00

CSV → Branded PDF invoices (multi-client batch)#

Turn a raw CSV of 500–2,000 line items into grouped, branded invoices with taxes, subtotals, and ready-to-send PDFs.

Runs as: Mini web pageSaves 3–6 hrs/batchBuilt in 4–6 days

Steps

Import CSV with raw line items (client, project, hours, rate)
Validate required columns and flag malformed rows
Group line items by client + invoice # or billing period
Calculate subtotals, taxes, and final balances
Inject data into a branded invoice template (logo, colors)
Export one PDF per client + an all-in-one archive
Optionally generate a CSV of invoice metadata for your system

See code excerpt

// Normalize customer + amount from flexible CSV
const cols = Object.keys(rows[0]);
const customerCol = findCol(['customer','client']);
const amountCol = findCol(['amount','total']);
const hoursCol = findCol(['hours','qty']);
const rateCol = findCol(['rate','price']);

const normalized = rows.map(r => ({
  ...r,
  customer: r[customerCol],
  amount: amountCol ? r[amountCol] : (parseFloat(r[hoursCol]) || 0) * (parseFloat(r[rateCol]) || 0),
}));

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Elapsed: 00:00.00

Rename, classify & sort 1,000+ receipts#

Rename mixed JPG/PDF receipts using dates, vendors, and amounts, then sort into job and month folders with an audit log.

Runs as: Desktop buttonSaves 45–90 min/runBuilt in 3–5 days

Steps

Scan a folder with hundreds of receipts (JPG, PNG, PDF)
Extract dates from filenames and text (multiple formats)
Parse vendors & amounts where possible; flag ambiguous files
Generate standardized filenames: YYYY-MM-DD_Vendor_Amount.ext
Map receipts to client/job folders based on naming rules
Move files into Year/Month/Client folders
Output a summary CSV of all renamed and moved receipts

See code excerpt

// Extract date from messy filename
const date =
  receipt.date ||
  extractDateFromFilename(receipt.name) ||
  "2024-01-01";

const newName = `${date}_receipt_${cleanBase}.${ext}`;

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Elapsed: 00:00.00

Analyze 10k–50k Orders — Instant Pivot & Chart#

Turn a massive multi-channel orders CSV into weekly revenue, AOV, and top-product insights with interactive pivot charts.

Runs as: Mini web pageSaves 1–2 hrs/weekBuilt in 4–6 days

Steps

Load a large orders CSV (10k–50k rows)
Normalize dates, channels, and product/category names
Handle refunds, discounts, and canceled orders
Group by week, channel, and product category
Calculate revenue, order count, and average order value (AOV)
Generate pivot-ready data for charts and summaries
Render interactive charts (by week, channel, and category)

See code excerpt

// Compute total if missing, parse mixed dates
const orders = rawOrders.map(o => ({
  ...o,
  total: o.total || (o.subtotal - o.discount + o.shipping + o.tax)
}));

const d = parseDateFlexible(o.order_date); // supports 2025-01-02, 03/01/2025, etc.

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Elapsed: 00:00.00

Mail-merge → PDFs & Draft Emails (segmented)#

Take a messy contacts/export CSV, validate it, dedupe it, and generate segmented PDF letters plus email drafts in one run.

Runs as: Desktop buttonSaves 2–4 hrs/batchBuilt in 4–6 days

Steps

Load or validate CSV (names, addresses, emails, segments)
Check for missing fields and flag invalid rows
Optionally dedupe by email or household
Stamp data into a branded letter/email template
Generate one PDF per row + an indexed ZIP archive
Create ready-to-send email drafts or an email-tool import file
Output a run log with counts, skips, and errors

See code excerpt

// Flexible mail-merge mapping
const customerIdx = findIdx(['customer','client']);
const amountIdx = findIdx(['amount','total']);
const hoursIdx = findIdx(['hours','qty']);
const rateIdx = findIdx(['rate','price']);

const rows = lines.map(vals => ({
  customer: vals[customerIdx],
  amount: amountIdx >= 0 ? vals[amountIdx] : (parseFloat(vals[hoursIdx]) || 0) * (parseFloat(vals[rateIdx]) || 0),
  date: vals[dateIdx],
  invoice: vals[invoiceIdx],
}));

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Elapsed: 00:00.00

Smarter deduping with typos, nicknames & formats#

Catch near-duplicates across multiple exports using fuzzy matching on names, emails, and phone numbers — even with typos.

Runs as: Desktop buttonSaves 1–2 hrs/runBuilt in 3–4 days

Steps

Parse multi-source contact CSVs (CRM, email tool, spreadsheets)
Normalize phones (strip symbols, country codes, extensions)
Normalize names (split first/last, handle nicknames)
Compute similarity scores on name + email + phone
Cluster likely duplicates with confidence scores
Surface "canonical" record suggestions per cluster
Export a cleaned master list and a review CSV of all clusters

See code excerpt

// Normalize columns then fuzzy match (capped to 2k contacts)
const contacts = parseCsv(text);
const result = findFuzzyDuplicates(contacts);

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// Normalize name + email then dedupe const { emailCol, fullNameCol, firstNameCol, lastNameCol } = resolveColumns(rows); const seen = new Set<string>(); const out: Row[] = []; for (const r of rows) { const email = (r[emailCol] || "").trim().toLowerCase(); const name = fullNameCol && r[fullNameCol] ? r[fullNameCol] : `${firstNameCol ? r[firstNameCol] : ""} ${lastNameCol ? r[lastNameCol] : ""}`.trim(); const cleanName = name.replace(/\s+/g," ").replace(/\b\w/g,m=>m.toUpperCase()); const normalized = { ...r, email, name: cleanName }; if (!email || !seen.has(email)) { if (email) seen.add(email); out.push(normalized); } }

// Normalize customer + amount from flexible CSV const cols = Object.keys(rows[0]); const customerCol = findCol(['customer','client']); const amountCol = findCol(['amount','total']); const hoursCol = findCol(['hours','qty']); const rateCol = findCol(['rate','price']); const normalized = rows.map(r => ({ ...r, customer: r[customerCol], amount: amountCol ? r[amountCol] : (parseFloat(r[hoursCol]) || 0) * (parseFloat(r[rateCol]) || 0), }));

// Compute total if missing, parse mixed dates const orders = rawOrders.map(o => ({ ...o, total: o.total || (o.subtotal - o.discount + o.shipping + o.tax) })); const d = parseDateFlexible(o.order_date); // supports 2025-01-02, 03/01/2025, etc.

// Flexible mail-merge mapping const customerIdx = findIdx(['customer','client']); const amountIdx = findIdx(['amount','total']); const hoursIdx = findIdx(['hours','qty']); const rateIdx = findIdx(['rate','price']); const rows = lines.map(vals => ({ customer: vals[customerIdx], amount: amountIdx >= 0 ? vals[amountIdx] : (parseFloat(vals[hoursIdx]) || 0) * (parseFloat(vals[rateIdx]) || 0), date: vals[dateIdx], invoice: vals[invoiceIdx], }));