Ontology definition and governance in commercial and open-source platforms alongside deep domain and technical knowledge to support your FAIR and semantic data journey.
Automated assay and screening, batch release, workflow orchestration, BPMN, low-code-no-code process automation (RPA) and robotics platforms.
Architecting, development and managed services on the major providers AWS, AZURE, GOOGLE, on-prem systems integrations, DevOPs and TechOps.
"Always on", end-user support, proven scale, quality, processes and knowledge of scientific applications have a measurable impact on end-user efficiency, satisfaction and application downtime.
Extracting data from and transforming to alternate formats including graph data structures like RDF, special structures like ADF etc to support loading to data lakes, warehouses for reuse and data FAIRification
Data modelling, plumbing, wrangling, transformation, management, and enrichment all support Machine Learning (ML) & artificial intelligence (AI) as need good quality data to work well.
ERP, Registration, Inventory, ELN, LIMS integration, laboratory instruments & robotics, project planning & lab audit tools, integration layer technology, instrument data standards (ADF, AniML, SeLA etc.), tech blueprints
Industry gurus engage in current state and vision setting, transformation coaching, building change momentum, thought leadership, technology options and innovation via POCs & value demonstrators, industry insights & benchmarking
Making scientific data Findable, Accessible, Interoperable and Reusable is a journey that needs experienced and expert planning, design, execution and governance.
Generating, transforming non-graph data, and graph data storage platforms like GRAKN, NEPTUNE, NEO4J etc. alongside ontology definition & management supports interoperable and reusable data.
Automated HTE & Manufacturing Batch Release, product specification ingestion to LIMS, our experience covers BPMN, RPA, AI, and many low-code-no-code open-source and proprietary tools & platforms.
Security, authentication, bandwidth, latency, data formats, and automation implications of robotics, automation, sensors, and instruments in the scientific lab
Master Data Management (MDM), Semantics and Data Enrichment can help maximise data value, trust in data and support the FAIRification of data assets and digital transformation.
Program and Project scale, AGILE to WATERFALL and all the different connotations between, project scoping and resource planning, kick-off and project delivery, reporting, finalisation and closing
Bidirectional translation of biomedical knowledge from the early research laboratory, through development and manufacturing to clinical & patient-oriented and population-based research