MLOps for
life sciences.
We build and operate the machine learning infrastructure behind life-sciences R&D: data and model pipelines, training and deployment, bio- and cheminformatics, and the dashboards and tools that make the science usable, the whole stack from data to production.
What we build, end to end.
Four practices, one team. We also ship AI and LLM integrations and the surrounding infrastructure when an engagement calls for them, but the spine of our work is the four below.
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i.
MLOps & Pipelines
Train, evaluate, and deploy custom ML models. Reproducible pipelines from data ingestion through production model serving.
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ii.
Bio & Cheminformatics
Cheminformatics, molecular property prediction, sequence and structure analysis, protein engineering, computational drug discovery. The foundational layer for natural-products-inspired ML.
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iii.
Dashboards & Analytics
Interactive dashboards for exploration, decision-making, and publication. Visualization tuned to the shape of scientific data, not generic BI charts.
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iv.
Bespoke Software
Internal tools, web applications, CLI utilities, and the connective tissue around them. Development, deployment, maintenance, by the same people.
The science travels.
Work the Phyla Tech team has shipped, in academia and at biotech companies, has been read and built on around the world. Live citation counts, fetched from OpenAlex.
- 2,460
- Citations
- 76
- Countries
- 23
- Disciplines
Scientists who ship software.
The same people who scope the work do the work, no layered handoffs and no junior delivery. Between us we cover chemistry, biology, mathematics, and the software engineering that holds them together.
A pipeline that needs ML. A dataset that needs a dashboard. A model that needs to ship.
If any of those describe a project on your desk, write to us. Real engagements, scoped together, with the people who will do the work.
Or by email: hello@phylatech.com