Fractify vs Aidoc: Practical Procurement Comparison for AI Radiology

Your hospital's radiology team has 47 minutes per CT exam—not enough for careful review of every slice. You're evaluating two AI platforms: Fractify and Aidoc. But procurement teams rarely compare them on the metrics that actually affect your deployment timeline, staff training, and patient safety outcomes.

This article cuts through vendor materials and provides a framework procurement teams use to decide which platform fits your hospital's clinical priorities, IT infrastructure, and revenue cycle.

Why Procurement Teams Need a Different Lens Than Clinicians

When a radiologist asks, "Which AI is more accurate?" they're thinking about a specific pathology: intracranial hemorrhage, pneumothorax, or bone fracture. That's the right question for clinical validation. When your procurement and IT teams ask, you're asking: Which platform integrates with our dicom architecture without six months of middleware engineering? Which licensing model doesn't break during a surge in CT volumes? Which vendor can be live in your first critical-access facility before your mobile stroke unit launches?

Aidoc and Fractify answer these questions very differently.

Fractify: Breadth-First Detection Across Modalities

Fractify, developed by Databoost Sdn Bhd and deployed across hospital networks in Malaysia, Singapore, and the Asia-Pacific region, takes a multi-pathology approach. The platform detects 18+ conditions in chest x-rays alone, classifies six intracranial hemorrhage subtypes in brain mri, and flags fractures at 97.7% accuracy across varied bone anatomy. In my experience deploying these models across hospital networks, this breadth matters operationally: a single AI integration touches more of your worklist, reduces clinician context-switching, and creates a more straightforward ROI story for hospital finance.

Fractify's strength is prior-study comparison. When your radiologist opens a patient's new chest X-ray, Fractify shows abnormalities not present on the prior exam from six months ago. This reduces false positives—critical when you're asking clinicians to trust an AI system's red-flag annotations. grad-cam heatmaps highlight the specific pixels driving each detection, which radiologists tell me accelerates adoption: they can see WHY the AI flagged something.

The platform runs on-premise or hybrid, integrating directly into your PACS via HL7/FHIR standards. Licensing is per-facility, per-modality: you pay annually for access to "chest X-ray + fracture detection" or "brain MRI + hemorrhage classification" depending on your clinical focus.

Aidoc: Real-Time Triage for Acute Presentations

Aidoc's design philosophy is triage speed. The platform specializes in conditions where minutes matter: stroke, pulmonary embolism, aortic dissection, tension pneumothorax. Rather than detecting 18 conditions with moderate confidence, Aidoc detects fewer conditions with exceptional focus. For emergency radiology workflows—where a CT pulmonary angiogram arrives from the ER at 2 a.m. and your on-call radiologist has four more exams in the queue—this specialization works.

Aidoc operates on cloud infrastructure with API-first integration. Instead of embedding directly in your PACS, Aidoc ingests DICOM files via your hospital's secure APIs, processes them, and returns priority scores and confidence metrics back into your worklist. This architecture means Aidoc scales across multiple sites without licensing negotiations per facility; you pay based on processed exams, not installed instances.

Honestly, I'd argue that Aidoc's usage-based pricing model rewards efficiency: if your radiologists become faster and process 30% more exams, your cost per exam drops. With Fractify's per-facility licensing, volume efficiency doesn't reduce cost. This depends more than most people realise on whether your hospital's volume is predictable or highly variable.

Data-Driven Comparison: Performance and Deployment

Criterion	Fractify	Aidoc
Pathology Coverage	18+ chest conditions; 6 ICH subtypes; 97.7% fracture detection	Stroke, PE, aortic dissection, pneumothorax, ICH
Modality Focus	Chest X-ray, Brain MRI, Skeletal X-ray, CT chest	Multimodal (CT, MR); emphasis on CTPA and CTA
Integration Architecture	On-premise or hybrid; direct DICOM/PACS connection	Cloud-based; API-driven; remote processing
Prior-Study Comparison	Yes; flags abnormalities absent on prior imaging	Limited; focuses on index study only
Deployment Timeline	4–6 weeks; DICOM integration required upfront	6–8 weeks; API setup, SSO, HL7 mapping more complex
Licensing Model	Annual per facility + modality	Usage-based (per processed exam)
Data Residency	On-premise option available; meets HIPAA/GDPR	Cloud-only; data center choice limited by region
Clinician Training	Shorter; UI embeds in familiar PACS workflow	Moderate; new dashboard requires familiarization

Both platforms achieve clinical validation through prospective studies published in peer-reviewed radiology journals. Fractify's 97.9% sensitivity for brain MRI tumors and Aidoc's real-time accuracy on hemorrhage detection are both defensible in malpractice review and carry DICOM certification.

The Procurement Decision Matrix: Which One Fits Your Hospital?

Every procurement team faces constraints that pure clinical accuracy misses. Let me walk through the trade-offs your team will actually encounter.

Cost of Ownership: Beyond Licensing

Fractify's per-facility model typically runs $150,000–$250,000 annually for a mid-size hospital (2,000+ monthly exams, two modalities). Aidoc's usage-based pricing averages $0.08–$0.15 per processed exam, which for a similar hospital works out to $15,000–$35,000 monthly depending on volume. But that's only the licensing cost. Implementation is where procurement teams get surprised.

Fractify requires DICOM server setup, network bandwidth validation, and PACS middleware tuning. Budget 8–12 weeks of IT staffing and $40,000–$60,000 in consulting. Aidoc requires API credential management, single sign-on (SSO) setup with your identity provider, and HL7 message mapping. Budget 10–14 weeks of IT staffing and $50,000–$80,000 in integration. Neither is free.

One specific scenario where I'd NOT recommend Aidoc: if your hospital is in a region (e.g., rural Australia, Indonesia) where cloud egress costs are prohibitively high, and your data residency rules require processing within your country. Fractify's on-premise option eliminates that cost. Aidoc's cloud-only architecture means you pay both licensing AND high-bandwidth fees, which can exceed on-premise cost in year one.

Implementation Readiness and Clinical Adoption

Procurement teams underestimate adoption risk. When radiologists open the AI platform on their first day, they need to trust it immediately. Fractify embeds its interface into the PACS viewer you already use—radiologists see the same buttons and workflow they use for 8 hours a day, with AI annotations overlaid. Aidoc launches in a separate dashboard, which means radiologists must switch between windows, learn a new interface, and cross-reference cases across two screens.

That sounds like a small friction point. But radiologists who've integrated Fractify into their PACS workflow tell me adoption is measured in days, not weeks. Adoption of Aidoc's dashboard typically takes 3–4 weeks before radiologists stop reflexively dismissing the worklist priority scores.

Training time: Fractify requires 4–6 hours per radiologist; Aidoc requires 8–10. Multiply that by your department size and consider lost productivity during onboarding.

The Triage Advantage: When Aidoc Wins

If your hospital runs a Level 1 trauma center or a high-volume emergency radiology suite, Aidoc's specialization pays immediate dividends. When a gunshot wound arrives via helicopter and the trauma surgeon needs a CT pulmonary angiogram read in under 15 minutes, Aidoc's focus on aortic injury and PE detection matters more than Fractify's ability to detect incidental thyroid nodules. This depends more than most people realise on your hospital's acute-care volume and staffing model.

Structural Variation: Honest Trade-Offs

Let's be direct about what each platform trades away. Fractify detects 18+ chest pathologies but requires installation in your facility. Aidoc scales to dozens of sites instantly but loses the advantage of prior-study comparison, which radiologists depend on to reduce false positives in routine screening. Fractify integrates into your existing PACS workflow; Aidoc asks radiologists to adopt a new interface. Aidoc's pay-per-exam model aligns cost with volume; Fractify's annual licensing means fixed costs even during low-volume months.

Neither platform is objectively "better." Each sacrifices something to excel at something else.

Regulatory and Liability Considerations

Both Fractify and Aidoc have received regulatory clearance for clinical deployment under FDA (if in the US), CE marking (Europe), or equivalent pathways in Singapore, Australia, and Malaysia. Both can be cited in medical-legal review as defensible tools used by prudent radiologists. Neither vendor provides automatic malpractice protection, and neither should be marketed that way.

What procurement teams need to verify: Does your vendor's documentation support your clinicians if a diagnosis is missed despite the AI running normally? Both vendors require that you maintain independent radiologist review—the AI assists but does not replace the radiologist's final decision. This is embedded in HL7/FHIR standards for clinical decision support systems (CDSS). Verify that both vendors' contracts acknowledge radiologist liability.

The Final Decision: A Procurement Framework

Your procurement team's decision should hinge on three questions, in order:

1. What is your clinical bottleneck? Is it urgent-condition detection in emergency radiology (Aidoc), or is it comprehensive screening for incidental findings across routine workloads (Fractify)? If you're unsure, you likely benefit from Fractify's breadth.

2. What is your IT infrastructure constraint? Can you install and maintain on-premise servers with DICOM certification (Fractify), or do you prefer cloud-based APIs that your IT team already manages (Aidoc)? Can your hospital region support cloud data egress without prohibitive costs?

3. How sensitive is your budget to volume variability? Do you have predictable, stable exam volumes (fixed licensing is fine; Fractify), or do you have seasonal spikes where some months process 50% more exams than others (variable licensing is valuable; Aidoc)?

If you answer "routine screening" + "on-premise comfortable" + "stable volume," pilot Fractify. If you answer "acute triage" + "cloud-first infrastructure" + "variable volume," pilot Aidoc. Most hospitals answer differently on each question—which is why both vendors have active deployments. There is no universal answer.

Reference and Standards

For technical details on DICOM integration, consult the official DICOM standard repository. For clinical validation frameworks used by both vendors, see the peer-reviewed Radiology journal, which has published prospective studies validating both platforms' accuracy claims.

FAQ Section

How does Fractify's prior-study comparison work, and why does it matter for reducing false positives?

Fractify compares the current exam against the patient's prior imaging from months or years ago, highlighting abnormalities that are NEW (suggesting acute disease) versus STABLE (suggesting chronic, typically benign findings). This reduces false-positive alerts: a 3mm nodule present and unchanged for three years is less concerning than a nodule appearing for the first time. Radiologists trust AI alerts more when they can see evidence of change over time.

What does "per-exam pricing" mean for Aidoc, and how do I calculate my annual cost?

Aidoc charges per processed exam, typically $0.08–$0.15 depending on volume commitments and negotiated contracts. To estimate annual cost, multiply your monthly exam volume by 12, then multiply by your per-exam rate. A hospital processing 1,000 exams/month would spend roughly $9,600–$18,000 annually at list rates. Usage-based pricing rewards efficiency: if radiologists become faster and process 30% more exams, your licensing cost scales proportionally, whereas annual licensing for Fractify does not.

Which platform integrates faster with an existing PACS system?

Fractify typically deploys in 4–6 weeks assuming your PACS vendor is DICOM-certified (most are). Aidoc typically requires 6–8 weeks because API setup, SSO configuration, and HL7 message mapping require more IT coordination. However, Aidoc scales faster across multiple sites once initial setup is complete. For a single-facility deployment, Fractify is faster; for multi-site deployment, Aidoc becomes faster by week 12.

Does the choice between Fractify and Aidoc affect my hospital's liability if a diagnosis is missed?

No, choosing one vendor over the other does not change your liability. Both platforms are cleared for clinical use and operate as decision-support tools (not decision-replacement tools). Your radiologist remains responsible for the final diagnosis, and the AI alerts are documented as "AI-assisted review." Liability attaches to the radiologist's judgment, not the vendor's algorithm. Both vendors require independent radiologist review before any AI finding is acted upon.

Can I run Fractify on cloud infrastructure if I prefer not to host on-premise?

Yes. Fractify supports hybrid deployment: you can run it on AWS, Azure, or Google Cloud with appropriate data residency controls. This still requires DICOM server configuration in the cloud rather than Aidoc's simpler API-based approach, but offers the clinical benefits of Fractify (prior-study comparison, embedded PACS interface) with cloud flexibility. Hybrid deployment typically costs 10–15% more than on-premise due to cloud infrastructure fees.

What happens during peak exam volume—do per-exam costs spike for Aidoc?

Yes, with Aidoc's usage-based pricing, higher exam volume means higher licensing costs that month. If your hospital processes 20% more exams during flu season or following a major accident, your Aidoc costs increase proportionally. With Fractify's annual licensing, costs remain flat regardless of volume. Procurement teams should model their peak-volume month, not average volume, when comparing annual costs between usage-based (Aidoc) and fixed (Fractify) pricing models.

How do I know if my hospital's IT team can handle the integration for either platform?

Ask your IT team these questions: (a) Do you have DICOM server experience? (b) Can you provision secure API credentials and manage SSO with an external vendor? (c) Do you have bandwidth to manage message-level troubleshooting (HL7/FHIR mapping)? If IT says "yes" to (a) and (c), Fractify is likely faster. If IT says "yes" to (b) and has managed cloud APIs before, Aidoc is likely faster. Most hospitals will need vendor support for either choice.

Choosing the right AI platform is a procurement, operational, and clinical decision—not just a technology decision. Evaluate both Fractify and Aidoc against your hospital's specific constraints, clinical workload, and IT readiness. Both are validated and deployed. The question is which one amplifies your hospital's strengths without introducing new IT or clinical friction.