Describe the device you're developing once, and Predicase uses it to find candidate predicates, score them transparently, and draft your substantial equivalence argument — all in the same place you already organize your submission.
Four steps, all inside the project you're already using to organize your submission.
One time, per project: intended use and technological characteristics, in your own words. This becomes the basis for everything else in the workspace.
Predicase searches across 175,000+ clearances for devices similar to yours — surfacing candidates you might not have found by keyword search alone, ranked before you save a single one.
Every candidate gets a transparent AI-ranking score with a visible breakdown — semantic similarity, product code match, recency, and precedent strength — not a single opaque number.
For any predicate you save, generate a draft substantial equivalence argument comparing your device to it — reviewed and edited by you before it goes anywhere near a submission.
Once your device description is saved, Predicase searches the full 510(k) corpus for semantically similar devices — surfacing candidates you can add to your project with one click, ranked by the same transparent score used everywhere else in the workspace.
Every scored predicate shows its work: semantic similarity to your device description, product code match, how recent the clearance is, and how often it's been cited as a predicate by later submissions. No black box — you can see exactly why a candidate ranked where it did.
Generate a draft substantial equivalence argument — intended use and technological characteristics, argued separately — comparing your device to any predicate saved to your project. Edited drafts stay distinct from the AI original, and a flag appears automatically if your device description changes after a draft was generated.
Watch any predicate and get notified if it gets a new MAUDE adverse event report, an FDA recall, or a CDRH warning letter — checked daily, so a predicate's safety profile can't change underneath your submission strategy without you knowing.
Regulatory work doesn't run on confidence — it runs on being able to explain your reasoning. The AI-ranking score is built around that.
A single number, no breakdown. You can't tell a reviewer — or yourself — why it's an 87 and not a 60, or which factor actually drove the result.
Similarity 39/45 · product code match 25/25 · recency 12/15 · cited as a predicate 4 times. Every point traces back to something real, and editable when your device description changes.