The Only Clinical AI
Adoption is the hardest problem in clinical AI — not accuracy. We have seen systems with 95%
Read postHealthcare AI you can deploy with our
healthcare AI consultancy. Packaged services, custom builds, EHR integration, every claim cited back to the chart. We build clinical AI that ships into real hospitals.
We care about your data in our privacy policy.
Features
Six packaged AI services for the clinical work that does not scale — built with practicing clinicians, on your data, behind your firewall.
Pulls imaging, pathology, labs, medications, and NCCN guidelines into a structured pre-read packet — ready before the MDT starts. Every claim linked to its source in the chart.
Learn moreDrafts the prior auth request against the payer's actual policy, flags missing documentation before submission, and logs every decision for compliance. First-pass approval rates improve immediately.
Learn moreAI reads alongside your radiologist — DICOM-native, integrated with your PACS. Flags findings before the study is opened. Structured report output writes back to the chart automatically.
Learn moreSurfaces evidence-based recommendations inside Epic, Cerner, or Athena where the clinician is already working. No separate application, no context switch — the chart gets smarter.
Learn moreMaps drug interactions, comorbidity patterns, lab trends, and diagnostic relationships across your patient cohort. Answers cross-patient analytical queries the chart was never designed to handle.
Learn moreIndexes and searches across discharge summaries, operative notes, clinical trial records, and 200-page prior auth bundles. Ask clinical questions in plain language — get answers with source citations.
Learn moreFanoni Lab is a healthcare AI consultancy: practicing clinicians, ML engineers, and integration specialists who have shipped clinical AI inside real hospitals. We sit behind your existing systems and surface AI where the clinician already works.
Six packaged AI services for the clinical work that doesn't scale — tumor boards, prior auth, imaging, decision support, knowledge graph, and RAG over long documents. Built with practicing clinicians, every claim cited, deployed behind your firewall.
Fanoni Lab is a healthcare AI consultancy. We build clinical AI that runs inside real hospitals — tumor-board pre-reads, prior authorization, imaging triage, decision support, knowledge graphs, and RAG that searches across your long clinical documents. Plus custom builds, EHR integration, and the infrastructure underneath. Built by practicing clinicians and ML engineers who have shipped clinical AI before. Deployed behind your firewall, every claim cited back to the chart.
Citation-first AI you can audit at the chart level.
Sits behind Epic, Cerner, Athena, your PACS, and your LIS.
Pricing
Every deployment is sized to your case mix, integration surface, hosting model, and clinical-eval cadence. We share a written proposal — line-item, no surprises — within a week of the technical scoping call. Pilot first. Production second. No per-seat tier sheet, no surprise overages.
Fixed fee, bounded scope, live on your data with success criteria you set.
Talk to usPer-case, per-clinician, or per-encounter pricing. Whichever fits how the workflow drives value.
See it liveWe share a written proposal, line-item, no surprises.
“Our tumor board coordinator used to spend four hours per patient pulling the packet together — imaging, pathology, labs, medications, NCCN guidelines. Fanoni Lab assembles it in under twenty minutes and every claim links to the source. Our oncologists actually read it before they walk in now. The MDT meetings start on time for the first time in years.”
“We were averaging 4.2 days on prior auth approvals with a 34% first-pass denial rate. Fanoni Lab drafts the request against the payer’s actual policy, flags missing documentation before we submit, and logs every decision for compliance. We are at nine hours now. The denials we still get are ones that genuinely should not be approved — which is the right outcome.”
“We evaluated six clinical decision support vendors. Four required a separate application — adoption was near zero within two weeks. Fanoni Lab sits directly inside our Epic workflow. Suggestions appear where the physician is already looking. At six months we are at 91% utilization, with a 31% alert override rate versus the 80% override rate we had with our previous vendor.”
FAQ
Common questions about Fanoni Lab and how we work.
Inside your perimeter — your VPC, on your hardware, or hosted by us in your region. PHI never leaves your boundary without an explicit BAA. Audit log on every clinical decision.
Yes. SOC 2 Type II audited annually. BAA included with every contract. HITRUST r2 in progress. Deployable in your VPC, on-premise air-gapped, or hosted in our single-tenant environment in your region.
Epic (Hyperdrive + Bulk-FHIR), Cerner Millennium, Athena, Meditech Expanse, Allscripts, plus PACS via DICOMweb and the LIS. We sit behind your existing systems — clinicians don’t change tools, the chart gets smarter.
Every recommendation we surface links back to a source span — the chart entry, the lab result, the imaging study, or the guideline behind it. Your clinicians can hover any claim and see exactly why we said it. No black boxes.
A pilot is bounded scope, a fixed fee, and live on your data with success criteria you set. We share every result during the pilot — including the misses — and only move to production if the workflow earns its place.
Our team
Practicing clinicians, ML engineers who have shipped models into hospitals, and integration specialists who know Epic in their sleep. We publish real names and bios as the team grows — no stock photos.
We are looking for people who have shipped real AI into hospitals. Clinicians, ML engineers, integration specialists, designers. If that is you, talk to us.
Latest posts
Notes from the team building Fanoni Lab — research notes, customer case studies, and the unsexy infrastructure decisions that actually determine whether clinical AI ever leaves the demo and reaches the chart.
Adoption is the hardest problem in clinical AI — not accuracy. We have seen systems with 95%
Read postAn AI that tells a physician to consider switching medications without showing the chart note that prompted
Read postPrior authorization denials cost US hospitals $11B annually in rework. The problem is not the payer —
Read postThe multidisciplinary tumor board is one of oncology's most powerful tools — and one of its most
Read postNotes from the team — clinical AI research, customer stories, and field reports. One short email a month.
Healthcare AI you can audit, deploy, and trust — six packaged services, RAG and knowledge graph included, built by practicing clinicians and ML engineers.