HIPAA-Compliant Edge AI for Skilled Nursing Facility Mobile Apps in 2026 (Fixed-Price, Money-Back)
Mohammed Ali ChherawallaHow skilled nursing facilities ship HIPAA-compliant edge AI for CNAs and nurses documenting at the bedside — no cloud exposure, no connectivity dependency.
Your CNAs document on shared tablets at the nursing station instead of at the bedside because the AI documentation tool requires WiFi. Your compliance team hasn't approved any cloud AI tool that touches resident records.
Bedside documentation reduces transcription errors, catches missed care items in real time, and gives your charge nurses a cleaner shift handoff. Every workaround that routes CNAs back to the nursing station is a quality and efficiency cost your facility absorbs every shift.
The Project Shape
Four decisions determine whether this project changes how care is documented or becomes a pilot that never gets past QA.
On-device vs edge server. A true on-device model runs on the tablet with no network dependency. An edge server inside the facility firewall offloads compute but requires the tablet to reach the LAN. SNF networks are unreliable enough that the distinction matters in practice - a model that depends on the LAN will fail on tablets that drift to poor signal near the end of a wing. The connectivity profile of your actual facility determines which architecture is appropriate.
Model size vs device spec. Shared facility tablets are often 3-4 years old. A model that runs within acceptable latency on a new iPad Pro may not perform adequately on a 2021 iPad 8th gen. Scoping the model to the device floor you actually have - not the device floor you'd prefer - avoids a hardware refresh becoming a prerequisite for the AI feature.
CNA workflow fit. CNAs document ADL completions, vitals observations, and behavioral notes. These are short, structured inputs - not long-form clinical narratives. A general-purpose summarization model is the wrong tool for this task. The model has to be configured for the specific input types your CNAs produce, or the outputs will require more correction time than just typing the note manually.
HIPAA audit logging. Local processing still requires a log that proves the model didn't transmit resident data outside the device or the facility boundary. The logging architecture has to be designed and reviewed before the compliance team signs off, not added as a patch after the first audit question.
Most teams spend 4-6 months discovering these decisions by building the wrong version first. A team that has shipped this before compresses that to 1 week.
The Off Grid Anchor
We built Off Grid because we hit every one of these problems in production. Off Grid is the fastest-growing on-device AI application in the world, with 50,000+ users running it today. It's open source, with 1,650+ stars on GitHub and contributors from across the world. It has been cited in peer-reviewed clinical research on offline mobile edge AI. Every decision named above - model choice, platform, server boundary, compliance posture - we have made before, at scale, for real deployments.
The Delivery Shape
The engagement is four sprints. Each sprint is fixed-price. Each sprint has a named deliverable your team can put on a roadmap.
Discovery (Week 1, $5K): We resolve the four decisions - model, platform, server boundary, compliance posture. Deliverable: a 1-page architecture doc your CTO can take to the board and your Privacy Officer can take to Legal.
Integration (Weeks 2-3, $5K-$10K): We ship the on-device model into your app behind a feature flag. Deliverable: a working build your QA team can test against real workflows.
Optimization (Weeks 4-5, $5K-$10K): We hit the performance and compliance targets from the discovery doc. Deliverable: benchmarks signed off by your team.
Production hardening (Week 6, $5K): Edge cases, OS version coverage, app store and compliance review readiness. Deliverable: shippable build.
4-6 weeks total. $20K-$30K total. Money back if we don't hit the benchmarks. We have not had to refund.
"Retention improved from 42% to 76% at 3 months. AI recommendations rated 'highly relevant' by 87% of users." - Jackson Reed, Owner, Vita Sync Health
The Close
Worth 30 minutes? We'll walk you through what your version of the four decisions looks like, what a realistic scope and timeline would be for your app, and what your compliance posture and on-device target mean in practice. You'll leave with enough to run a planning meeting next week. No pitch deck. If we're not the right team, we'll tell you who is.