FAIR data from day one. Ready for every model.
We build cloud-native pipelines, lakes and governed data products that make scientific data FAIR the moment it lands, with AI doing the heavy lifting under our governance.
From any source to any cloud,
AI-ready.
for every study.
Governed data lakes and lakehouses for clinical, omics and discovery data, from CDISC-compliant clinical lakehouses to analytics-ready lakes built from legacy estates. AI-assisted mapping speeds migration; engineers validate every record against source.
- CDISC-compliant clinical lakehouses
- Multi-modal migration of ELN, RNA-seq, omics and clinical data
- Metadata standards and role-based, audit-ready access
- GxP risk assessment built in from day one
Discuss your data lake
An animal health company's ELN, RNA-seq, omics and clinical data sat on premises. We moved it into one analytics-ready lake on Azure.
across every R&D domain.
One connected layer across R&D, without moving every dataset. Knowledge-graph-enabled discovery fabrics · Data virtualization where federation beats consolidation · Unified search across structured and unstructured data Structure-activity relationships from patents and journals · ADMET, physicochemical and in vivo endpoints · Gold-standard training sets for Caco-2, hERG and other endpoints · Customizable to your target and assay schema
Built for a Top 20 pharma on Azure, with enterprise search, virtualization and lakehouse compute.
One front door to all of R&D
A global pharma's scientists could not find data scattered across domains. One fabric and search front door now surfaces it all.
for every study.
Governed data lakes and lakehouses for clinical, omics and discovery data, from CDISC-compliant clinical lakehouses to analytics-ready lakes built from legacy estates. AI-assisted mapping speeds migration; engineers validate every record against source.
- CDISC-compliant clinical lakehouses
- Multi-modal migration of ELN, RNA-seq, omics and clinical data
- Metadata standards and role-based, audit-ready access
- GxP risk assessment built in from day one
Discuss your data lake
An animal health company's ELN, RNA-seq, omics and clinical data sat on premises. We moved it into one analytics-ready lake on Azure.
run like software.
Cloud architecture, migration and operations for scientific workloads, with every change deployed through automated, auditable pipelines. Architecture on AWS, Azure and GCP · Lift-and-shift migration with optimization · CI/CD, GitOps and Kubernetes · Consolidation of fragmented R&D tools
Infrastructure as code throughout, so every environment can be rebuilt and audited at any time.
Scale up, spend less
A data science company's AWS bills grew with every workload. Governed access and automated cost monitoring let its scientists scale while spending less.
Here is what engineered data has made possible for one client.
A global pharma’s Animal Health division brought legacy and new OMICs data into one governed, searchable platform.
INGEST
100%
Legacy and new OMICs data consolidated
From ELNs, internal clouds and vendor systems into one repository.
HARMONIZE
1
Standardized metadata model
Ontology mapping and ETL pipelines for structured, unstructured, batch and real-time data.
GOVERN
4
User personas with role-based access
Authentication and audit trails on every dataset.
DISCOVER
30+
User workflows defined
Metadata search with predefined filters and dataset bookmarking.
OUTCOME
60%
Faster data retrieval
Plus a 30–40% gain in researcher productivity.
Find out how FAIR your data really is
Tell us about your data landscape, and we’ll show where engineering would pay back fastest.
