Clean data is the foundation
Your Business Data - Clean, Structured, and Ready for AI
For companies sitting on years of messy, siloed data. We clean it, structure it, and automate the flows so your AI systems have the foundation they actually need.
AI Data Pipeline Build is a done-for-you build offered by Crescent AI, an AI automation agency helping small and medium businesses automate repetitive workflows without hiring in-house AI engineers.
4-6 WKS
From messy, siloed data to a clean, connected foundation
1 SOURCE
Of truth your team, reports, and AI can all query
AUTO
Data stays current - pipelines refresh on schedule
School uniform season and wedding alterations back-to-back — customers ringing all day asking if their order was ready. We had jobs written on paper and no way to track any of it. Crescent AI set up automated SMS updates at every stage — dropped off, in progress, ready to collect. Calls have nearly stopped, I'm taking on twice the jobs, and it's still just the two of us.
Owner, Tailoring Business · Adelaide, Australia
The Problem
Most businesses have data - almost none have usable data
Customer records in three different formats. Sales data that doesn't match accounting data. Reports that take two days to compile manually. AI can't run on messy data. Most AI projects fail at this stage before anyone touches a model.
Data lives in 5 tools that don't talk to each other
The same customer has different records in different systems
Reporting takes days because nothing aggregates automatically
AI models give bad outputs when trained on inconsistent data
How it works
How We Build Your Data Pipeline
We start with a complete audit of your data sources in Week 1, identify duplicates and inconsistencies in Weeks 1–2, clean and standardize everything in Weeks 2–3, build automated pipelines in Weeks 3–4, set up a single source of truth in Week 4, configure automated refreshes in Weeks 4–5, and validate everything in Weeks 5–6.
Data Source Audit
Week 1Every data source mapped: what exists, where it lives, what format it's in, and how it relates to other sources.
Duplicate & Inconsistency Scan
Week 1-2We identify duplicate records, mismatched formats, and missing values across every source before touching anything.
Cleaning & Standardisation
Week 2-3Data is cleaned and standardised into a consistent format a human or model can actually use.
Integration Pipeline Build
Week 3-4Automated connections built between your data sources so records stay in sync without manual exports or copy-paste.
Single Source of Truth Setup
Week 4A queryable source your team, reports, and AI systems can all reference instead of hunting across multiple tools.
Refresh Schedule Configuration
Week 4-5Pipelines configured to run on a schedule so data stays current without manual intervention.
Validation & Handover
Week 5-6Pipeline output validated against your real reporting needs, then documented and handed over to your team.
What's included
What Gets Built
You get a complete data audit, cleaned and standardized data free of duplicates, automated integration pipelines connecting all your sources, a single queryable source of truth, and automated refresh schedules so your data stays current without manual work.
Data Audit
Every data source mapped: what exists, where it lives, what format it's in, and how it relates to other sources.
Cleaning + Standardisation
Duplicates removed, formats standardised, missing values handled. Data that a human or model can actually use.
Integration Pipelines
Automated connections between your data sources so records stay in sync without manual exports or copy-paste.
Single Source of Truth
A single source of truth your team, reports, and AI systems can query - instead of hunting across multiple tools.
Automated Refresh Schedule
Pipelines run on a schedule. Data stays current. No manual intervention after setup.
Coverage
Data Sources We Commonly Connect
Platforms we connect
Fit check
This is built for you if…
This is for companies with data scattered across 4+ tools, businesses building their first AI system, operations teams doing manual reporting, companies whose AI projects failed due to noisy data, and scaling businesses where data chaos is starting to affect decisions.
Companies with data in 4+ disconnected tools
Businesses building their first AI system and needing a clean foundation
Operations teams where reporting is still done manually in spreadsheets
Companies that have tried AI but got poor results from noisy data
Scaling businesses where data chaos is starting to affect decisions
Why Crescent AI
Why Choose Crescent AI for Your Data Pipeline
Where the risk sits
Fixed price after the initial audit. You keep the clean data and pipeline infrastructure permanently - it's your asset.
Start your project
Start with the Audit. Not a Sales Call.
30 minutes. We map the workflows eating your team's time, rank your top automations by ROI, and tell you honestly what's not worth touching yet. You get a written summary. No slide deck. No pitch.
Fixed price. Built on your existing tools. You own everything we build.