The platform under every Roshan AI product.
One clinical core turns ingestion, model intelligence, grounded reasoning, and APIs into products that can compound without a re-architecture.
Four layers. One clinical contract.
Each layer remains reusable as products, workflows, and integrations grow.
Clinical data, normalized into something models can read.
Notes arrive through API or batch, are normalized under customer policy, and become the canonical clinical representation downstream models consume.
Notes arrive through API or batch, are normalized under customer policy, and become the canonical clinical representation downstream models consume.
Clinical encoders trained on real clinical text.
The encoder is paired with a learnable concept-query bank trained against explicit clinical concepts: the substrate for a grounded representation contract.
The encoder is paired with a learnable concept-query bank trained against explicit clinical concepts: the substrate for a grounded representation contract.
A concept bottleneck every prediction must flow through.
The reasoning layer activates the concepts present in a note and routes prediction signal exclusively through them, making evidence a requirement rather than an afterthought.
The reasoning layer activates the concepts present in a note and routes prediction signal exclusively through them, making evidence a requirement rather than an afterthought.
One integration shape, many products downstream.
Every product returns predictions, evidence, concepts, and alternatives through the same response shape—one integration surface for evolving clinical workflows.
Every product returns predictions, evidence, concepts, and alternatives through the same response shape—one integration surface for evolving clinical workflows.
Integrate ShifaMind today. Build on what's next.
If your clinical workflow needs grounded reasoning, partner deployments can shape the next product on the stack.