Healthcare AI Demo Gallery — Working Patterns From Real Engagements
The most common question from prospective buyers in the first sales call: “Can you show us something?” Slide decks describe AI. PowerPoint demos pretend to. A real demo gallery shows actual working healthcare AI patterns — ambient documentation that writes back to Epic in real time, sepsis prediction running against test patient streams, oncology treatment matching against the current NCCN guidelines, dermatology lesion classification with fairness slicing visible on the calibration dashboard. The Demo Gallery is the page where prospective buyers see what Taction has actually built — not abstractions, but working artifacts.
This page is for healthcare AI buyers in the evaluation phase, clinical leadership exploring what is possible, and engineering teams scoping what production healthcare AI actually looks like. Each demo links to the deeper specialty or service page where the underlying capability is sold as a productized engagement.
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What the Demo Gallery Is and Is Not
It is: A curated collection of working healthcare AI patterns Taction has shipped or that we maintain in our internal lab on synthetic data. Each demo represents an EHR-integrated, BAA-eligible, audit-logged architecture that has passed (or is designed to pass) hospital security review.
It is not: Live patient data. Every demo in this gallery runs on synthetic clinical data (Synthea or equivalent) or on de-identified historical encounters from buyers who specifically consented to demo use. No PHI appears in any gallery demo regardless of buyer access level.
It is not: A list of customers or case studies. The customer-specific stories with named institutions and outcomes data sit in the case studies section (see ambient documentation case study, AI triage copilot case study, and predictive cardiac RPM case study).
It is not: A library of prebuilt products. Each demo is a working pattern that we adapt to the buyer’s specific use case, EHR, and clinical workflow. The productized pathway (Discovery Sprint MVP Sprint Pilot-Ready Sprint) is the engagement model.
Ambient and Documentation AI Demos
The first category clinicians ask about. The lowest-risk entry point for most healthcare AI deployments.
Multi-specialty ambient scribe with Epic write-back. Real-time conversation capture, structured SOAP note generation, write-back to Epic via FHIR DocumentReference. Specialty-tuned prompt templates for primary care, internal medicine, behavioral health, and pediatrics. Demo runs on synthetic visit transcripts. Linked deeper at primary care AI and behavioral health AI.
Specialty-tuned ambient for psychiatry sessions. 42 CFR Part 2-aware documentation handling. Crisis-language detection running alongside the documentation. Behavioral-health-specific note structure. Deeper context: behavioral health AI page.
Ambient with procedure-aware billing capture. Used in dermatology and other procedural specialties. Captures the visit narrative plus the procedure codes (CPT 11102, 88305, etc.) plus the path requisition in one flow. Reduces under-coding by 15–25% based on internal benchmarks. Deeper context: dermatology AI page.
Clinical Decision Support and Copilot Demos
The highest-stakes category. Every demo here has eval harness output visible alongside the AI behavior.
Sepsis early warning with alert-fatigue management. Streaming vitals and lab evaluation against the Sepsis-3 criteria with AI prioritization to suppress low-confidence alerts. Demo shows the calibration curve and false-positive rate over time. Linked deeper at hospital AI page and emergency medicine AI page.
Oncology treatment matching against NCCN. AI parses NCCN guideline updates monthly, matches against a synthetic patient’s stage and biomarker profile, produces ranked treatment options with evidence citations. Demo shows the citation grounding back to the NCCN source. Linked deeper at oncology AI page and clinical trial AI page.
AI triage copilot for emergency departments. ESI-aligned triage prioritization, sepsis flag, stroke/STEMI time-critical routing. Demo runs against synthetic ED visit data. Linked deeper at emergency medicine AI page and the AI triage copilot case study.
Clinical copilot embedded in Epic Hyperspace. SMART on FHIR launch, contextual patient summary, differential diagnosis suggestions with literature citations, override and audit workflow. Demo shows the Hyperspace embedding pattern. For the embedding details, see our embedded AI inside Epic via SMART on FHIR build guide.
Imaging and Pathology AI Demos
Dermatology lesion screening with skin-tone fairness reporting. Image-based lesion classification with explicit performance reporting across Fitzpatrick skin types I through VI. Demo shows where the model is well-calibrated and where the calibration gap exists. Linked deeper at dermatology AI page.
Pathology WSI analysis with biomarker quantification. Gigapixel whole-slide image processing with HER2 and PD-L1 quantification. Demo runs on publicly available synthetic pathology slides. Linked deeper at pathology AI page.
Diabetic retinopathy screening for primary care. Fundus-image-based DR screening with autonomous AI workflow modeled after IDx-DR. Demo shows the integration handoff to ophthalmology. Linked deeper at ophthalmology AI page.
Revenue Cycle and Workflow AI Demos
The category where economic ROI is most easily demonstrated. Often the first AI feature to break even on cost for ambulatory practices.
AI medical coding with documentation-evidence linkage. Real-time CPT and ICD-10 suggestions during charting with the supporting documentation evidence highlighted. Demo shows the coder review workflow with override audit. Common entry point for hospital and clinic AI engagements — see hospital AI page and clinic AI page.
Prior authorization automation. AI drafts PA requests from clinical context using FHIR Da Vinci profiles. Demo shows the payer-specific form population plus the status tracking. Linked deeper at hospital AI page and clinic AI page.
No-show prediction with smart outreach. Risk scoring per appointment combined with text/email reminder cadence and automated waitlist fill. Demo shows the historical no-show curve and the predicted post-intervention curve. Common in the clinic AI page buyer profile.
Patient Engagement and RPM Demos
The category where wearable, BLE device, and patient-app integration are the dominant technical challenges.
Predictive cardiac RPM with alert-fatigue reduction. Continuous monitoring of heart-failure patients with deterioration prediction 7–14 days before clinical event. Demo shows alert prioritization driven by AI prioritization rather than threshold-only rules. Linked deeper at cardiology AI page and the predictive cardiac RPM case study.
Patient triage and intake chatbot. Pre-visit symptom intake with structured chief complaint extraction and triage routing. Demo shows the handoff to clinician with the synthesized intake summary.
Post-visit follow-up automation. SMS-driven post-visit follow-up with adherence tracking and escalation for non-response patterns. Particularly useful in surgical and orthopedic post-op contexts — linked deeper at orthopedics AI page.
From Demo to Production Healthcare AI
A demo is not a product. Every demo in this gallery represents an architectural pattern that needs adaptation, integration, and compliance work before it becomes a production AI feature in a specific clinical environment.
The path from “this demo looks like what we want” to “this is running on our patients”:
- Discovery Sprint ($45K, 4 weeks) — Adapt the demo pattern to your specific EHR, clinical workflow, and compliance context. See Discovery Sprint page.
- MVP Sprint ($95K, 8 weeks) — Build the production-grade version of the feature in your sandbox EHR. See MVP Sprint page.
- Pilot-Ready Sprint ($145K, 12 weeks) — Harden for real clinical pilot with drift monitoring, evidence package, and pilot operations support. See Pilot-Ready Sprint page.
- Care Package — Ongoing operations post-pilot. See Care Packages.
Frequently Asked Questions About the Demo Gallery
Yes. Most demos in the gallery have a recorded walkthrough that goes out under NDA. Live demonstration sessions with the engineering team are scheduled by request — typically a 45-minute Zoom session with the buyer’s clinical, technical, and compliance leadership in the room. Request via the consultation link above.
Yes, through the Founder Sprint at $25K for startups or through the Discovery Sprint at $45K for established healthcare organizations. A custom demo takes 4–6 weeks to build on representative data with your selected EHR.
The patterns are. Each demo represents an architecture pattern we have shipped or maintain in our internal lab. The synthetic data is not from real patients, and the demos do not reveal any customer-specific implementation details that would breach confidentiality. Where a customer has consented to be named, the relevant case study page covers the customer-specific work.
Yes for the architectural patterns and technical capabilities. The demos demonstrate what Taction can build. For named customer references, the relevant case study pages provide that context, and direct customer reference calls can be arranged through the consultation process.
The gallery covers the most common patterns. Less common use cases — specialty-specific niche AI, novel research-grade applications, multi-site federated learning, on-prem-only deployments — are scoped through Discovery Sprint regardless of whether a demo exists. The absence of a gallery demo does not mean we have not built something similar; it means the pattern is less commonly requested.
Synthetic data only. Tools like Synthea generate FHIR-compliant synthetic patient records realistic enough for demo purposes without any HIPAA exposure. Where de-identified historical data appears in a demo, it is under explicit consent from the originating customer and reviewed for re-identification risk before any external use.
Via the consultation request. Include the demo categories that interest you and the clinical/technical/compliance roles that will attend. We will respond with a 45-minute Zoom invitation including the relevant engineering and clinical leads from our side.