AI service — AI Medical · Clinical language
Clinical text representation
Turn clinical and biomedical text into embeddings that your own classifiers, extractors and search indexes are built on.
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.
Encoders do not answer questions; they turn text into vectors. That is the cheapest layer in clinical NLP by a wide margin — thousands of documents per hour on modest hardware — and it is what a task-specific classifier of your own is trained on top of.
Text arrives over your API or as a batch and comes back as embeddings or task labels. Long-document models matter here: a full admission record does not fit the standard context, and truncating it loses exactly the part a readmission model needs.
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 clinical text representation 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
- Your own classifiers — Train phenotyping, triage or outcome models on embeddings rather than raw text.
- Long-record tasks — Handle a whole admission record in one pass for readmission or phenotyping.
- Search indexing — Build a semantic index over clinical or biomedical text.
More Clinical language services
- Clinical coding supportClinical coding support service →
- EHR outcome predictionEHR outcome prediction service →
- Clinical de-identificationClinical de-identification service →
- Mental health text analysisMental health text analysis service →