AI service — AI Medical · Genomics
Genomic sequence analysis
Score variant effects, predict regulatory consequences and prioritise candidate causal variants from sequence and phenotype.
Send us your data volume, throughput and latency targets and any constraint we should design around. You get a proposed configuration, a benchmark on your own data, and a known cost per unit of work before you commit.
Variant interpretation is the bottleneck in clinical genomics: sequencing is cheap and deciding what a variant does is not. These models score pathogenicity and regulatory effect directly from sequence, and phenotype-driven tools rank candidate causal variants against the patient’s own clinical terms.
Sequence, VCF and phenotype terms arrive over your pipeline and come back as scores and ranked candidates. This work runs comfortably as a batch, which is why it suits scheduled capacity rather than always-on serving.
Every output is clinical decision support, not a diagnosis: a qualified professional reviews and signs it. Where clinical use requires regulatory approval in your jurisdiction, that approval remains yours to hold — we provide the infrastructure, the model operations and the audit trail behind it.
What we size for
We build the genomic sequence analysis pipeline around the workload you actually have: data format, accuracy target, latency, throughput, concurrency, retention and scheduling. Start with a pilot, then scale production capacity without changing a line of your integration.
Common use cases
- Rare disease pipelines — Rank candidate causal variants against the patient phenotype.
- Non-coding interpretation — Score variants outside coding regions where classical tools are weak.
- Splice and regulatory effects — Predict splice gain and loss, and expression consequences.
More Genomics services
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