Precision AI Surgical Planning System (PAI-SPS)

K251558

Precision AI Pty, Ltd. · cleared 2026-01-12 · product code QHE · Orthopedic

Premarket evidence — what FDA accepted

Device typehardware with ml
source quote (p.4)
“The Precision Al Planning Software is intended to be used as a pre-surgical planner for simulation of surgical interventions for shoulder joint arthroplasty. The software is used to assist in the positioning of shoulder components by creating a 3D bone construct of the joint and allows the surgeon to visualize, measure, reconstruct, annotate and edit pre-surgical plan data. The software leads to the generation of a surgery report along with a pre-surgical plan data file which can be used as input data to design the Precision Al Shoulder Guide and Biomodels. Hardware The Precision Al Planning System Guides and Biomodels are intended to be used as patient- specific surgical instruments to assist in the intraoperative positioning of shoulder implant components used with total and reverse shoulder arthroplasty by referencing anatomic landmarks of the shoulder that are identifiable on preoperative CT-imaging scans.”
Algorithmlocked, or static, artificial intelligence algorithm
source quote (p.7)
“The patient's CT scan images are the design input for this to be created and are auto segmented via a locked, or static, artificial intelligence algorithm.”
Adaptive (vs locked)No
source quote (p.7)
“The patient's CT scan images are the design input for this to be created and are auto segmented via a locked, or static, artificial intelligence algorithm.”
PCCPNo
Cybersecurity addressedNo

Validation studies (1)

Bench

sample size not stated

endpoints: Software verification and validation; Usability validation

standards: Premarket Submissions for Device Software Functions, General Principles of Software Validation, Applying Human Factors and Usability Engineering to Medical Devices

Reported performance (0 observations)

FDA source did not state a quantitative performance metric — non-reporting is itself the signal.

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

1
recalls in product code, 24mo
1
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
0
drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Orthopedic panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K251558