Behold.ai

The algorithm is the entire product and the business model depends on it entirely. red dot classifies chest X-rays and CT head exams, and the commercial proposition is explicitly positioned as an alternative to outsourced radiology reporting, meaning the AI substitutes for purchased human reporting capacity rather than assisting it. There is no services layer; the company's own framing is that the technology delivers reporting performance at a fraction of the price of outsourcing.

Genuinely autonomous within a deliberately bounded task, and one of only a handful of vendors in this index operating at that end of the axis alongside Oxipit. Exams classified High Confidence Normal are auto-reported and REMOVED from the radiologist worklist entirely, meaning no human reads them. The oversight mechanism is not human review but the threshold itself: the model reports only the subset it is most confident about, and the published error rate for that subset is the safety argument. Peer reviewed work reports auto-reporting 15 percent of all chest X-rays as normal at a 0.33 percent error rate, against a cited average consultant radiologist error rate of 13.5 percent. Publishing the auto-report rate and its error rate together is exactly the disclosure autonomous operation requires, and it is what separates a defensible autonomy claim from an assertion.

Performance is published in peer reviewed venues with the specific numbers that matter for the autonomy claim, including the proportion of studies auto-reported and the associated error rate, plus a negative predictive value of 93 percent for the CT head product alongside the proportion of scans removed from the reporting workload. Localization is rendered through heatmaps to make outputs interpretable. Training data composition and architecture are not published, and the 32,000 patient zero-missed-cancer claim on the company site lacks a linked peer reviewed citation, so it should be treated as vendor stated rather than verified.

Real published evidence plus named NHS deployments, tempered by what the market ultimately decided. Two Clinical Radiology papers underpin the product, one on autonomous diagnosis of normal chest radiographs and one reporting a 60 percent reduction in missed lung cancer when triage ran alongside consultant radiologists in a tumour-enriched dataset. Named trust deployments include Somerset, where a 3,794 image real world trial found performance closely matching published results and more than halved time from X-ray to CT, Calderdale and Huddersfield reporting a 71 percent reduction in lung cancer waiting times, and Basildon processing 4,415 chest X-rays in 3.5 days against 4 to 8 weeks by outsourcing. A prospective HRA registered mixed methods evaluation of red dot v2 was also underway. The counterweight is significant: NICE withdrew red dot from its recommendations in February 2025, and the original company failed commercially.

No specific PHI handling or data governance framework was located. Note that autonomous reporting raises a distinct safety question beyond data handling, namely who holds clinical responsibility for an auto-reported study that no clinician read, and the vendor materials do not address where that liability sits.

No HIPAA or BAA commitment was located. The company holds FDA clearance for triage and has US validation history, but its deployment record is overwhelmingly NHS based, so US contracting terms are undocumented.

No SOC 2, ISO 27001, or equivalent attestation and no trust center were located. The successor entity's UK site claims CQC certification, which is a care quality regulator registration rather than an information security attestation and does not substitute here.

Multi jurisdiction authorization exists but the regulatory standing is unsettled, and the distinction between clearance and endorsement matters here more than usual. The product holds FDA clearance for radiology triage, validated against more than 800 UK and US cases reviewed by three independent board certified radiologists, plus CE and UKCA marking. However NICE withdrew red dot from its recommendations in February 2025, following the original company entering administration in January 2025, and sector commentary cites the withdrawal as a case study in why evidence of lifecycle performance and supplier continuity now matter alongside accuracy. Graded C: the clearances are real, the market endorsement was withdrawn, and a buyer must verify what authorizations transferred to the successor entity.

The autonomy threshold design is itself a governance mechanism, since the model only auto-reports where confidence is highest and the published error rate quantifies the residual risk being accepted. Validation spanned UK and US cases reviewed by independent radiologists. What is absent is demographic subgroup analysis, which is a pointed gap for a product that removes studies from human review entirely: if performance varies across any patient group, those patients disproportionately receive an unread scan. No formal governance framework or post market monitoring commitment was located.

The platform integrates with PACS to analyse images within existing workflows, and the auto-reporting function requires write access back into the reporting worklist, which is a deeper integration than read-only detection overlay. Deployment across multiple named NHS trusts demonstrates the integration works across different trust environments rather than a single reference site. No published connector list or API documentation was located.

No hosting, tenancy, or data residency terms were located in the materials reviewed.

No pricing is published, though the commercial framing is unusually explicit about what it displaces: the company positions red dot as a cost effective alternative to outsourced radiology reporting, which gives a buyer a concrete benchmark, the per study outsourcing rate, to price against. Reported impact includes reporting time returned equivalent to 19 consultant radiologists. The overriding commercial consideration is not price but continuity: the original entity entered administration in January 2025 after failing to win NHS AI Diagnostic Fund contracts, and any buyer should establish what the successor entity's contractual, support, and indemnity position actually is.

Two narrow but high volume targets: chest X-ray for normal rule-out and suspected lung cancer triage, and CT head for acute finding triage and normal rule-out, with a reported ability to remove more than 60 percent of CT head scans from the reporting workload at 93 percent negative predictive value. The strategy is deliberately depth over breadth, automating the highest volume normal-heavy workloads rather than detecting many pathologies. Coverage does not extend beyond chest and head.