Free Data Readiness Assessment
A 30-minute call to work out whether you need a full pipeline, a warehouse, or just a cleaner setup of the tools you already run. No pitch, no obligation.
Extract · Load · TransformAI-assisted reportingWarehouse-ready output
ELT Product
Move Every Business System Into One Warehouse — And Report On It The Same Day
ScriptStory's ELT platform extracts data from your accounting, commerce, and spreadsheet sources, loads it into a warehouse you control, and transforms it into reporting your team can actually trust. Connect a source in minutes, not quarters.
- Fixed-scope pipelines
- Source-neutral advice
- We'll tell you if you don't need a warehouse
Pipeline OverviewLive Sync
Extract8 sources
Load1.2M rows
Transform34 models
QuickBooks · invoicesSynced 2m ago
Shopify · ordersSynced 5m ago
Stripe · payoutsSynced 11m ago
Monthly revenue$248,400
12+Prebuilt source connectors, live today
15 minFrom OAuth connect to first synced rows
99.5%Sync success rate across scheduled jobs
48 hrsTypical turnaround on a scoping call
✓
Fixed-Scope Pipelines Written scope before build
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Engineers Who Know Finance Data models + accounting
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Source-Neutral QuickBooks, Xero, Zoho, Shopify, Stripe
✓
Your Warehouse Or Ours Postgres, BigQuery, Snowflake
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AI Chat On Your Data Ask questions in plain English
For teams that outgrew spreadsheets
A Data Platform For The Middle Ground
Most data conversations happen at two extremes: spreadsheets and manual exports that a growing business outgrows quickly, and enterprise data platforms that cost six figures and need a dedicated engineering team to operate. ScriptStory's ELT product works in the space between.
It is built for companies whose operational complexity has outpaced the systems tracking it — teams selling across several channels, running more than one entity, or reconciling accounting against operations by hand every month. If your finance numbers and your operations numbers disagree and nobody can say which is correct, that gap is exactly what this platform closes.
Disconnected tools are the usual root cause. When orders live in one system, payments in another, and accounting in a third, your team becomes the integration layer and month-end turns into a manual reconciliation project. We connect those systems into a single warehouse — so the numbers match reality, and reporting stops depending on who remembered to run the export.
Scope of service
What You Get — Every Engagement Deliverable
These are the named services inside our data practice. Most clients start with a free assessment, move into paid discovery, then choose the engagement that fits. Each deliverable is scoped and priced in writing before it begins.
Paid Discovery & Fixed-Price Scoping
A structured audit of your sources, data quality, refresh needs, and reporting gaps — delivered as a written report with a timeline, itemised scope, and a fixed-price proposal.
Full ELT Pipeline Implementation
End-to-end delivery: source authorisation, extraction jobs, schema design, transformation logic, scheduling, monitoring, user training, and go-live support.
History-Preserving Data Migration
We extract, clean, map, and load your historical transactions, customers, vendors, and balances so year-over-year reporting stays intact through cutover.
Pipeline Rescue & Stabilisation
For syncs that technically run but produce numbers nobody trusts. We audit what's breaking, fix the mappings and transformations, and get you to reporting you can sign off on.
Connector Health Check
A focused diagnostic of an existing integration — token handling, incremental logic, duplicate protection, schema drift, and failure alerting — with a prioritised fix list.
Default Reports & Dashboard Pack
Ready-made reporting on top of your synced data: revenue, expenses, vendor spend, invoice aging, and cash movement, generated automatically from Excel or connector sources.
AI Chat Layer On Your Data
Ask questions in plain English and get answers grounded in your own synced tables — with the generated query shown, so analysts can verify the logic behind every number.
Custom Connector Development
If your source isn't in our catalogue, we build it: authentication, pagination, rate-limit handling, incremental sync, and the same monitoring as every prebuilt connector.
Ongoing Monitoring & Managed Support
Scheduled job monitoring, failure alerting, schema-change handling, and monthly support after launch, so the pipeline keeps pace as your sources change.
How we engage
A Discovery-First Process That Makes Fixed Pricing Possible
Most firms bill data work by the hour, which makes scope creep a revenue model. We do the opposite: scope the work in writing first, then commit to a price. Here is the path from first call to a pipeline your team trusts.
01
Readiness Assessment
Free 30-minute call to decide whether a pipeline is the right move at all.
02
Discovery
Documented audit of sources and reporting needs, then a fixed-price proposal.
03
Build & Load
Connector setup, schema design, transformations, and historical backfill.
04
Test & Go-Live
Parallel runs and reconciliation against your source of truth before cutover.
05
Optimise
First month-end close together, then ongoing monitoring and tuning.
Rescue & stabilisation
Who Fixes Pipelines That Run But Can't Be Trusted?
Data integrations usually fail for one of three reasons: the wrong architecture was chosen, the work was done without understanding the business logic behind the numbers, or the migration moved the records without the reporting rules that made them meaningful. The result is a pipeline that runs on schedule and produces reports nobody signs off on.
Cost discipline
We fix before we rebuild
A full re-implementation is expensive and disruptive. Repairing an existing sync, remapping a schema, or correcting transformation logic is usually faster and cheaper.
No blind quotes
Written diagnostic before any price
Every rescue starts with a documented audit of what's broken, what's salvageable, and what a fix costs — so you know the scope before we start.
We do this differently
Data model first, tooling second
Most failed pipelines have connectors that work correctly. The real problem is the schema, the join logic, or the transformation rules. We audit those first.
Common rescue scenarios: a connector set up once that silently stopped syncing months ago; duplicate records from a job with no idempotency; a source API version change that broke a schema without raising an alert; or a migration completed without preserving the historical reporting logic behind the balances.
Multi-entity & consolidation
Multiple Entities, Channels, And Locations — Configured To Consolidate
If you operate across several legal entities, storefronts, or locations, standard tooling creates fragmentation: separate books, manual consolidation, and no unified view without significant monthly effort.
We model these environments so leadership sees the consolidated picture in real time, without waiting for someone to compile it at month-end — while each entity keeps its own reporting intact.
- Multiple entities or subsidiaries reporting on one shared chart of accounts
- Several storefronts or payment processors that need one revenue number
- Location-level P&Ls without maintaining separate spreadsheets
- Intercompany transactions that should reconcile automatically, not by hand
Source-neutral
The Sources We Connect — And Who Each Is For
We support these connectors today and recommend among them based on what your business actually runs, not what is easiest for us to deploy.
Accounting
QuickBooks
Invoices, bills, vendors, customers, chart of accounts, payments, journal entries, and P&L summaries via OAuth with scheduled incremental sync.
Accounting
Xero
Full accounting extraction for teams standardised on Xero — the same normalised output schema as QuickBooks, so reporting stays consistent across entities.
Business suite
Zoho Books
Accounting and operational records for organisations running the Zoho stack, mapped into the same warehouse tables as every other finance source.
Commerce
Shopify
Orders, products, customers, refunds, and payouts — reconciled against your accounting data so COGS and revenue line up by SKU and channel.
Payments
Stripe
Charges, payouts, refunds, disputes, and fees, matched to invoices so net revenue and processor costs are visible without manual export work.
Files & sheets
Google Drive, Sheets, Excel & CSV
Folder-scoped Drive access, live Sheets sync, and direct spreadsheet upload with automatic schema detection and a generated default report pack.
Maybe you don't need a warehouse at all. For plenty of teams the right answer is a cleaner accounting setup with two integrations, not a platform migration. We'll say so — see our QuickBooks integration services
Decision support
Which Source Type Fits Your Business?
The right starting point depends on where your data currently lives and how quickly you need reporting on it. This table reflects what we see working in practice.
| Accounting sources | Commerce sources | Files & sheets | Custom sources | |
|---|---|---|---|---|
| Best for | Accounting-led reporting | Commerce & payments | Spreadsheet-first teams | Custom / internal systems |
| Typical sources | QuickBooks, Xero, Zoho | Shopify, Stripe | Excel, CSV, Sheets, Drive | REST APIs, databases |
| Setup effort | OAuth connect | OAuth connect | Upload or folder link | Custom connector build |
| Historical backfill | Full history | Full history | Whatever you upload | Depends on source API |
| Refresh cadence | Scheduled incremental | Scheduled incremental | On upload or on schedule | Scheduled incremental |
| Default reports | Included | Included | Auto-generated | Built to spec |
| AI chat support | Yes | Yes | Yes | Yes |
| Typical time to live | 1–2 weeks | 1–2 weeks | Same day | 3–6 weeks |
Timelines reflect ScriptStory implementation effort only. Source-system licensing, where applicable, is billed separately by the vendor. Ranges vary with data complexity, history volume, and the number of integrations.
Industry fit
How Teams In Your Sector Use It
We match the build to your operational reality rather than a predetermined template. Here is how the platform tends to be used across the industries we serve.
Retail & e-commerce
Multi-channel order and inventory data, Shopify and Stripe reconciliation, and COGS by SKU joined to your accounting records.
Professional services
Project billing, utilisation, time tracking, and department-level P&Ls consolidated across multiple operating entities.
Manufacturing & distribution
Inventory movement, purchase orders, supplier spend, and margin analysis pulled from operational systems alongside the ledger.
Financial operations
Cash flow, invoice aging, vendor concentration, and month-end close reporting built directly on synced accounting data.
Startups & scale-ups
A warehouse and reporting layer that scales past spreadsheets without hiring a full data team to run it.
Agencies & multi-entity groups
Client or entity-scoped workspaces with isolated credentials, shared reporting models, and consolidated roll-up views.
Why ScriptStory
Why Growing Businesses Choose Us Over Enterprise Platforms
Most data vendors are either enterprise platforms built for companies with their own engineering teams, or contractors who disappear after go-live. Neither fits a business that needs trustworthy reporting without a six-figure budget.
We recommend what fits, not what we sell
Sometimes the answer is a warehouse and a full pipeline. Sometimes it's two integrations and a cleaner chart of accounts. We say which, before a proposal is written.
Reconciliation is not optional
Every implementation includes a data-migration audit and a reconciliation pass against your source of truth, so the first report you see already ties out.
We don't disappear after go-live
Pipelines break when source APIs change. Monitoring, alerting, and schema-drift handling are part of the build, not a separate upsell.
Rescue work is something we actually do
If a previous build left you with syncs nobody trusts, you get an honest assessment of what's salvageable and what needs rebuilding before you commit to anything.
Who this is for
Signs You're Ready For A Real Data Pipeline
You don't need a big budget or an in-house data team. You need a clear signal that your current setup is holding the business back. The most common ones we see:
- Your team exports the same reports by hand every week
- Finance and operations numbers disagree and nobody can say which is right
- Month-end close takes more than five business days of manual work
- You run several entities or storefronts with no consolidated view
- Analysts wait on someone else to pull data before they can start
- Reporting lives in spreadsheets that only one person fully understands
- You've hit row limits, refresh limits, or reporting walls in your current tools
- A previous integration was set up once and never quite worked
If four or more apply, you're likely a strong candidate. A free assessment is the fastest way to find out what the right next step is for your specific situation.
Not Sure If You Need A Pipeline — Or Just A Better Setup?
That's the most common question we get. Sometimes you need a full warehouse build, and sometimes you need two integrations and a cleaner data model. We'll tell you which, and why, before any proposal is written.
30 minutes · no pitch · no obligation
FAQ
Frequently Asked Questions About ELT Pipelines
What is an ELT pipeline?
ELT stands for Extract, Load, Transform. Data is pulled from your source systems, loaded into a central warehouse in raw form, and transformed into reporting-ready tables there. Loading before transforming keeps the original records intact, so logic can be corrected and re-run without going back to the source.
How is ELT different from ETL?
In ETL, data is transformed before it lands in the warehouse. In ELT, it lands first and is transformed in place. ELT suits modern cloud warehouses because storage is cheap and compute is elastic — and because keeping raw history means you can rebuild your reporting logic without re-extracting years of records.
Which sources can you connect to?
QuickBooks, Xero, Zoho Books, Shopify, Stripe, Google Drive, Google Sheets, and direct Excel or CSV upload are available today. If your source isn't in that list, we build a custom connector with the same authentication, incremental sync, and monitoring as the prebuilt ones.
Do I need my own data warehouse?
No. We can deploy into a warehouse you already own — Postgres, BigQuery, Snowflake, or similar — or host the storage layer for you. If your data volume is modest, a managed database is often enough and considerably cheaper than a full warehouse.
How long does implementation take?
A single accounting or commerce source is typically live within one to two weeks. Spreadsheet and file sources can be same-day. A multi-source build with historical backfill and custom transformations usually runs three to six weeks, depending on data quality and how many integrations are involved.
What happens to my historical data?
We backfill it. Transactions, customers, vendors, and opening balances are extracted, cleaned, mapped, and loaded so year-over-year comparisons still work after cutover. Preserving reporting history through a migration is a specific deliverable, not an afterthought.
How often does data refresh?
Scheduled incremental syncs, with the frequency set per source — hourly, daily, or on demand. Incremental logic means only changed records move after the first full load, which keeps runs fast and stays well inside source API rate limits.
What happens when a sync fails?
Failed jobs retry automatically with backoff. Anything that still fails raises an alert and is written to a sync log with the specific record and error, so the cause is visible rather than silently producing an incomplete dataset.
How does the AI chat feature work?
You ask a question in plain English and it answers against your own synced tables. The generated query is shown alongside the answer so an analyst can verify the logic. It reads your data — it does not modify records or write back to source systems.
Is my data secure?
Credentials are stored encrypted and scoped to the narrowest permission the source allows — folder-level for Drive, read-only where the API supports it. Each client workspace is isolated, and access to synced data follows role-based permissions you control.
Do I actually need this, or can my current setup be improved?
That's the most common question we get, and the honest answer is that it depends. For plenty of teams the right answer is a better-configured accounting system and two integrations, not a warehouse. We'll tell you which applies before any proposal is written.
What does it cost?
Engagements are scoped and priced in writing before work begins. Cost depends on the number of sources, historical data volume, transformation complexity, and whether you need ongoing managed support. The readiness assessment is free and carries no obligation.
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