The data infrastructure
that finally held

They ran workspace bookings for enterprises worldwide. We built the AWS data pipeline
that unified every CRM and API into one source of truth.

100%

Data Accuracy Rate

1 m

Full Infrastructure Built

1 team

Dedicated End-to-End Ownership

AI & Automation

About The Company

A leading SaaS provider of hybrid workspace solutions: helping enterprises manage office bookings, desk allocation, and employee footprint at scale. With data flowing in from multiple CRM systems and APIs, their infrastructure couldn't keep up with their product.

SaaSGlobalB2B

The Challenge

No single source of truth

Multiple CRM systems and external APIs: each with its own format, its own update schedule, its own version of the data. No single source anyone could trust.

Manual reconciliation at scale

Without continuous integration, teams spent hours manually reconciling records. Every report was out of date before it was finished.

Fragmented data, blocked decisions

Employee footprint calculations, workspace utilisation, growth analysis - all of it depended on data that was fragmented, inconsistent, and impossible to act on at scale.

Complexity growing faster than control

In a high-competition health app market, more spend without smarter targeting just inflated CPC and diluted ROI. The goal wasn't more leads: it was the infrastructure to find the right ones, consistently, at scale.

The Approach

AI & AutomationData EngineeringAWS Infrastructure

Phase 01Week 1

Audit & Architecture

Mapped every data source, format, and sync frequency. Designed the AWS architecture before writing a single line of code.

All CRM and API sources mapped
Data schema and pipeline designed
AWS stack selected and scoped

Phase 02Weeks 2-3

Pipeline Build

Built the full ETL pipeline on AWS: collecting, transforming, and loading data from every source into a centralised RDS Postgres database.

Lambda for serverless data processing
EC2 + VPC for heavy data loads
S3 for raw storage before transformation

Phase 03Weeks 4+

Monitor & Validate

CloudWatch set up to monitor the pipeline continuously. Data validated end-to-end until 100% accuracy was confirmed across every source.

100% data accuracy confirmed
CloudWatch monitoring live
Zero manual reconciliation needed

The Results

100%

Data accuracy across every integrated CRM and API source.

1 month

Full AWS pipeline built, validated, and handed over.

Manual reconciliation required after go-live.

1 source

Single centralised database replacing every fragmented system.

Most data projects ship late and still need fixing. This one delivered 100% accuracy in a month, because the architecture was right before the first line of code was written.