Extensions

CSV Import Pipeline

Drop in a CSV file and your product takes the rows that are valid, rejects the rest and tells you why.

Loading spreadsheet data by hand usually means a messy import, broken records and an afternoon of clean-up. This add-on gives the product you already run a validated route for CSV files. Each file is checked against agreed column rules before anything loads. Good rows go in, and bad rows come back with a clear reason, so you fix the source once.

Checks every row against agreed column rules first
Loads the good rows and returns the bad with reasons
Stops one broken file from corrupting your records

$1,500 10–20 working days

Choose delivery and add to cart Ask an expert

Wooden sieve letting most paper slips through and catching a few, valid rows loaded and bad rows held back.

What it is

CSV Import Pipeline is an add-on that gives an existing Upmark Labs product a validated route for importing CSV files. Each file is checked against agreed column rules before anything is loaded, and rejected rows come back with reasons. It fits document, analytics and workflow products.

Why businesses buy it

Bad data imported once can quietly break reports, answers and automations for weeks. Many import tools either accept everything or reject the whole file, which leaves your team guessing. A validated pipeline makes imports routine: anyone can drop in a file and see exactly which rows failed and why. The written scope covers one file format, the column rules, row-level rejection reasons and testing with the parent product, so imports become a quick task instead of a risk.

Problems this solves

Bad CSV files load wrong data into the product

CSV Import Pipeline checks each file against agreed column rules before anything is loaded. Files that fail the rules are stopped before they can spoil records.

Imports fail and nobody can say which rows went wrong

Rejected rows come back with the reason each one failed. Staff can fix just those rows and import them again, instead of hunting through the whole file.

Data is entered by hand because importing feels risky

A validated route gives staff a safe way to load data in bulk. The updated documentation explains the column rules, so files can be prepared correctly first time.

Scope card SKU UPM-A0047

CSV Import Pipeline

Everything this build includes, written down before you pay. Choose how you want it, own the code or license it yearly, then the delivery speed and any add-ons.

$1,500 one-time build price

What is included

Channel: As per the parent product
Integrations: As described in the add-on
Knowledge: As per the parent product
Workflows: Adds a validated CSV import route into an existing product
Languages: As per the parent product
Testing: Tested together with the parent product
Revisions: 1 round
Handoff: Written handover report
Support: 14 days after launch

A good fit if

Data reaches you as spreadsheet exports from systems the product is not connected to.

Bad rows have caused problems before, such as missing fields, wrong dates or duplicates.

You can describe the columns a good file should have and what each must contain.

Your product is an Upmark Labs document processing, analytics or workflow automation build.

Not the right fit if

You want records kept in step with a live spreadsheet both ways. Google Sheets Sync does that.

The data sits in a system with an API you could connect to directly. Custom API or Webhook Integration avoids the file step.

You are moving content from an old chatbot. Data Migration from Existing Bot is built for that.

Your product is a chatbot, voice agent or creative generator. This add-on fits data-handling products.

How it works

The file format is defined. Columns, required fields, formats and allowed values are agreed with you and written down.
An upload route is set up. Files arrive through the route agreed at intake, such as a folder or an upload step in the product.
Each file is validated. Rows are checked against the rules, and duplicates are caught before loading.
Results are reported. Valid rows are loaded; rejected rows come back in a file with the reason for each.
Test files, good and bad, are run through it with the parent product, then you review with one revision round.

What you provide within 72 hours

Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.

The order reference of the product receiving the data
A sample CSV file, plus a deliberately messy one if you have it
The rules for each column: required or optional, format and allowed values
How duplicates should be treated
One person who approves the file specification

The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.

Timeline

Start Sample files and column rules received

Week 1 File specification written and agreed

Weeks 1–2 Upload route and validation built

Week 2 Good and bad test files run

Week 2 Your review and one revision round

Go-live Import route live, walkthrough recorded

Delivery options, in working days (Monday to Friday) from completed intake. They can extend because of national or public holidays, technical issues outside our control (such as platform outages, third-party changes, account approvals or access delays), or natural disasters and other events beyond our control. If a delay happens, we tell you in writing with a new date.
Option	Delivery time	Price
Standard	10–20 working days	$1,500

What you receive at handover

A validated CSV import route into your existing product
Agreed column rules applied before data loads
Rejected rows returned with reasons
Updated documentation, a test report, a handoff note and a written walkthrough

Expected benefits and how to measure them

Helps keep bad data out of the product
Can save time fixing failed imports
Makes bulk loading less risky

Rejected rows: Track rejected rows per import from the pipeline's results and watch them fall as files improve.
Data clean-up time: Ask staff to note time spent fixing bad records each month, before and after.
Manual entry volume: Count records keyed by hand each month, before and after the pipeline.

Before you start: Note how data gets into the product today and how often bad records need fixing.

These are things to track, not promised results. Outcomes depend on your data, your team and your market.

Running costs

Importing files adds little running cost. Any processing or storage it uses sits in your own accounts with the rest of the parent product's usage.

Ask about running costs

Custom requirements

Several different file formats, Excel workbooks with multiple sheets, or imports pulled automatically from another system are outside this add-on. Note them at checkout for a written Change Quote. Larger or bespoke projects go through the Custom AI request form instead.

Request a custom version

Keep it running

If the source system changes its export, the column rules need updating. That fits in the parent product's maintenance, which grows in line with the add-on's price.

Adds $75/mo to maintenance

Covered by the main product's maintenance, which grows by this amount.

How maintenance works

How this compares

	Do it yourself with a SaaS tool	Hire a custom agency	Upmark Labs
Price	Import features are often limited to a higher plan	An agency quotes data work after reviewing files	Ours is one fixed price, shown before you buy
Validation	Basic column matching	Depends on the brief	Ours checks your agreed rules on every row
Bad rows	The whole import may fail	Set per project	Ours returns rejected rows with a reason for each

Questions about this product

What happens to rows that fail validation?

They are not loaded. They come back to you in a separate file with the reason each row failed, such as a missing required field or a date in the wrong format. Valid rows from the same file still load, so one bad row does not hold up the rest.

How does the import catch duplicate rows?

Using the rule you choose at intake. Common choices are matching on an ID column, or on a combination such as email and date. A duplicate can be rejected, merged with the existing record or flagged for review. The test files include duplicates so you can see the behavior.

How do files get into the pipeline?

Through the route agreed at intake, such as a watched folder in your cloud storage or an upload step in the product. The route is set up in your own accounts. Automatic pulling from another system's server is not included, but can be quoted.

Which products can use the CSV Import Pipeline?

Document processing, analytics and workflow automation products. Those work with structured data, so a validated import route fits them. Conversational agents and creative generators usually take knowledge documents or brand files instead, and other add-ons, such as Knowledge Base Expansion, handle those.

Can the CSV pipeline handle a format we use today?

Yes, as long as it is one consistent CSV layout. Send a sample file during intake and we agree the column rules from it. Several formats or multi-sheet Excel workbooks need a Change Quote. The pipeline follows the delivery speed chosen for its product, with a fixed price and date shown before you pay.

Can it handle more than one CSV layout?

This add-on covers one file format. If you receive several layouts, for example exports from two different systems, each needs its own specification. Describe them in the checkout note and you get a Change Quote, or add the pipeline once per format.