Data Volume
Sequencing output exceeds the throughput any team can process by hand.
Industries · Industry 04
Research Moves Faster When AI Does the Data Work.
Genomics analysis, experimental result interpretation, literature synthesis, and protein structure analysis. Models hosted on dedicated GPU infrastructure with reproducible pipelines.
The challenges
Where teams in biology lose time and signal today.
Literature Drift
Relevant papers are published faster than any researcher can read them.
Reproducibility Gaps
Manual notebooks and ad-hoc scripts make experiments hard to repeat.
What we build
Capabilities tuned for the vertical, deployed on your stack — cloud or on-prem.
Genomics Data Analysis
Variant calling, annotation, and cohort comparison pipelines.
Experimental Interpretation
Statistical analysis with plain-language summaries linked to raw data.
Literature Synthesis
Continuous monitoring of relevant journals with structured weekly digests.
Protein Structure Analysis
AlphaFold-API-backed structural prediction integrated into your tooling.
In practice
A genomics lab used NovaFekra pipelines for a 1,200-sample cohort study.
Before
Variant calling and annotation took eight weeks of analyst time.
After
Pipeline turnaround dropped to four days with reproducible artifacts and audit logs.
Metric Before After
Cohort processing 8 weeks 4 days
Reproducibility Notebook bound Pipeline bound
Analyst hours 320+ 40
Integrations
We meet your existing systems where they are.
AlphaFold APIBioPythonJupyterHubS3SlurmSnakemake
Get started
Bring AI to your biology operation.
Cloud, onsite local or both. We reply to sales questions within 4 business hours.