Pieces vs Regard (2026)
Two physician founded platforms reading the inpatient chart, and one of them has already been through the thing every buyer in this category quietly worries about. In September 2024 the Texas Attorney General settled with Pieces over its accuracy claims, the first enforcement action of its kind in healthcare AI, which is both a genuine mark against the vendor and the only instance here of an outside authority examining what a clinical AI company says about its own performance. Regard has no such history and also no published accuracy figure, model description or validation study, while doing the more consequential thing: recommending diagnoses rather than summarising. Pieces is the better answer for case management and utilisation review, which nothing else here addresses. Regard is the better answer at the bedside, with certified interoperability and an acceptance rate it actually reports.
- It is the only product in this category that explicitly addresses case management and utilisation review rather than only the clinician, which is where a large share of the reading burden in a hospital actually sits.
- The oversight architecture is more developed than most of this category and it was built under scrutiny rather than in the abstract, which is worth weighing alongside the enforcement history rather than instead of it.
- It now sits inside a group that publishes a genuine trust centre with named compliance items, which is a stronger assurance position than the product had standing alone.
- It recommends diagnoses rather than summarising, on the stated premise that clinicians see roughly 3 percent of the data in a chart, and the clinician accepts or declines each recommendation as a structural gate.
- Certified interoperability rather than claimed, as an ONC certified health information technology module implementing the modern exchange standard, with named health system deployments and quantified site level results.
- Its own headline metric is the count of recommendations clinicians acted on, which is an acceptance rate rather than an adoption figure, and it is one of the few numbers in this category that describes whether the output was useful.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Pieces and Regard are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI Health Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Fact | Pieces | Regard |
|---|---|---|
| Primary category | Clinical Summarization & Chart Review | Clinical Summarization & Chart Review |
| Founded | Not recorded | 2017 |
| Headquarters | Irving, TX, US | Los Angeles and New York City, US |
| Website | smartertech.com | regard.com |
Side by Side
Each record in one paragraph
Written to be quoted whole. Each paragraph states what the AI Health Index verified about the vendor, with the caveats attached. Generated from this pair’s live capability grades, so it moves when a grade moves.
The AI Health Index awards Pieces its top capability grade on AI Centrality. Set against Regard, Pieces grades higher on Model Supply Chain Disclosure and HIPAA and BAA Posture. Grades reflect evidence the AI Health Index could verify at the last review, so a low grade records disclosure the vendor has not published rather than a capability it has been shown to lack.
Source: AI Health Index, August 2026
The AI Health Index awards Regard its top capability grade on AI Centrality and EHR and Interoperability Depth. Set against Pieces, Regard grades higher on Clinical and Operational Evidence and EHR and Interoperability Depth. Its thinnest published disclosure sits on Model Supply Chain Disclosure. Grades reflect evidence the AI Health Index could verify at the last review, so a low grade records disclosure the vendor has not published rather than a capability it has been shown to lack.
Source: AI Health Index, August 2026
Questions buyers ask
Should we choose Pieces or Regard?
On the axes where the AI Health Index separates them, Pieces grades higher on Model Supply Chain Disclosure and HIPAA and BAA Posture, and Regard grades higher on Clinical and Operational Evidence and EHR and Interoperability Depth. Neither leads on the greater share of scored axes, so the decision turns on which constraint is binding rather than on an overall winner.
Where do Pieces and Regard differ most?
The widest separation the AI Health Index records between Pieces and Regard is on Model Supply Chain Disclosure, where Pieces grades C and Regard grades D. That axis sits in the AI Capability group, so it should carry the most weight for a buyer whose binding constraint is how much of the work the model itself is trusted to do.
Where do Pieces and Regard grade the same?
The AI Health Index grades Pieces and Regard the same on several axes, including AI Centrality, Autonomy and Oversight Model and Model and Technology Transparency. Neither holds an advantage the index can evidence on those axes, so they should not carry weight in a selection between these two.
What have Pieces and Regard not disclosed?
At the last review, at least one of Pieces and Regard published thin or absent detail on Model Supply Chain Disclosure. The AI Health Index treats an absent disclosure as a gap in the public record rather than a failure of the product, so these are the axes to get in writing during diligence instead of inferring from the grade.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Clinical Summarization & Chart Review page.
In September 2024 the Texas Attorney General reached a settlement with Pieces over its accuracy claims, the first enforcement action of its kind against a healthcare AI vendor. That is a matter of public record and it cuts both ways: it is a real accuracy governance failure, and it also means this vendor's claims have been examined by an external authority in a way no competitor's have. Read the settlement terms rather than the headline.
Regard publishes no model description, accuracy figure, validation publication or error taxonomy, and its regulatory credential examines record system criteria rather than diagnostic performance. Both vendors surface undocumented diagnoses that raise reimbursement as well as clinical completeness, and neither separates the two effects.