Services / Data Infrastructure and Engineering
We build the pipelines and data warehouses that connect EHR systems, agricultural IoT sensors, and industrial historians into a single reliable foundation your operations team can query and trust.
The problem
EHR systems, agricultural sensors, and industrial historians were built to operate independently. Pulling a clean, joined view across them requires engineering depth most internal teams don't have time to develop.
The result is manual extraction, spreadsheet reconciliation, and reports that are four days old by the time they reach the people who need them. Finance and operations are working from different numbers.
We close that gap. We build the pipelines, design the warehouse, write the runbooks, and hand it over to your team with 90 days of support so it stays running after we leave.
Reliable ELT pipelines connecting EHR systems, agricultural IoT sensors, industrial historians, and ERPs into a single foundation your team can query and trust.
BigQuery, Snowflake, or Redshift implementations designed for your specific industry. HIPAA-compliant architecture for healthcare. Optimized for operational analytics workloads.
Every engagement ends with documented failure modes, incident playbooks, and monitoring dashboards. Your team can run it. We stay available for the first 90 days after launch.
Healthcare
EHR integrations, HL7 and FHIR pipelines, billing data, and operational analytics unified into a HIPAA-compliant data layer your clinical and operations teams can query.
One network reduced reporting lag from four days to four hours.
Agriculture
IoT sensor data, weather integrations, soil and yield data connected into pipelines that produce operational views field managers actually trust.
Sensor data from 40+ devices centralised with zero data loss from equipment failures.
Manufacturing
Historian and SCADA data connected into unified warehouses that give operations teams a real-time view of equipment status, yield, and quality across the floor.
We map your existing data sources, systems, and gaps. You get a production architecture document and a scoped engagement before we write a line of code.
Pipelines and warehouse built against the agreed architecture. Instrumented with data quality checks, monitoring, and alerting from day one.
Runbooks, incident playbooks, and monitoring dashboards handed to your team. We train the people who will run it.
We stay available for the first 90 days. Incidents, questions, tuning. Your team owns it but we are there if something unexpected happens.
Related service
Once the data foundation is in place, models can go to production.
AI Deployment and Operations covers MLOps pipelines, serving infrastructure, drift monitoring, and operator-facing interfaces.