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Services

End-to-end capabilities for bioinformatics, AI, and life sciences software. We combine deep domain expertise with modern engineering.

Bioinformatics pipeline development

We design and implement production-ready pipelines for NGS, genomics, proteomics, and multi-omics. Every pipeline is version-controlled, documented, and built for reproducibility.

  • Variant calling, RNA-seq, ChIP-seq, single-cell
  • Containerized (Docker/Singularity) for portability
  • Integration with LIMS and reporting systems
  • GxP-ready documentation and validation support

AI & ML for biological data

From proof-of-concept to deployment: we build models for omics, imaging, clinical, and real-world data. We prioritize interpretability and regulatory alignment.

  • Deep learning for imaging and sequence data
  • Survival analysis, stratification, biomarker discovery
  • MLOps and model versioning
  • Explainability and audit trails

Custom software for life sciences

Web applications, lab tools, and internal platforms tailored to your workflows. We use modern stacks and design for scientists, not just IT.

  • React/Next.js, Python backends, APIs
  • Electronic lab notebooks and workflow tools
  • Integration with instruments and external systems
  • Secure, role-based access

Data analysis & visualization

Interactive dashboards and analysis platforms that let your team explore data without writing code. We connect to your data warehouse and keep everything in sync.

  • Multi-omics exploration and reporting
  • Clinical and operational dashboards
  • Custom visualizations (D3, Plotly, etc.)
  • Export and sharing for stakeholders

Cloud infrastructure for scientific computing

Scalable, secure compute and storage on AWS, GCP, or Azure. We handle batch jobs, workflows, and data lakes so you can focus on science.

  • HPC-style jobs and workflow orchestration
  • Cost optimization and right-sizing
  • Compliance (HIPAA, SOC2) and encryption
  • Disaster recovery and backup

Biological database design & management

Schemas, ontologies, and data management that support FAIR principles and integration with public and proprietary resources.

  • Relational and graph databases
  • Ontology alignment and metadata standards
  • ETL and data quality pipelines
  • APIs and query interfaces