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tags:
  - medical LLM，R&D，Life science
---

# CrossNow AI

> LLMs for medical

We built upon a life‑science knowledge framework, integrates hospital data (e.g., de‑identified medical records, clinical guidelines), pharmaceutical information (e.g., drug development, clinical trials, package inserts), and regulatory compliance data. Its core lies in constructing a “compliance‑aware brain” that combines a medical knowledge graph (millions of entities) with retrieval‑augmented generation (RAG) and fine‑tuning techniques.

Key features:

Data foundation: High‑quality, curated, and anonymised data from clinical practice and drug development, annotated by medical experts to avoid “hallucinations” and low‑quality web data.

Compliance pillars:

Data compliance – rigorous de‑identification and standardisation.

Algorithmic compliance – guardrails, real‑time risk interception, and pharmacovigilance monitoring.

Operational compliance – AI supports decision‑making, but final clinical actions (e.g., prescriptions) remain with human professionals.

Four operational modules:

Data perception – multimodal processing (text, images, molecular structures).
Knowledge enhancement – secure, auditable integration of R&D assets.
Logical reasoning – AI agents bridging healthcare, insurance, and pharmacy workflows.
Intelligent interaction – natural language Q&A with traceable citations.
Application scenarios:

Healthcare – assisted diagnosis, personalised treatment, medication safety.

Pharma R&D – target discovery, clinical trial optimisation, adverse event monitoring.

Medical insurance – automated fraud detection and cost control.

Regulation – compliance reporting, intelligent audits.

In essence, the model acts as an intelligent hub across the full life‑science chain – diagnosis, medication, R&D, payment, and regulation – driving efficiency and precision medicine while upholding strict safety and compliance standards.

## Links

- 🌐 [Website](https://www.crossnow.cn)
- 📧 [Contact](mailto:routine@crossnow.cn)

## Focus areas

`medical LLM，R&D，Life science`