Founder pitch · Robert Schmid
Hero slot, Wefunder shows a 16:9 image or video here. Robert’s founder video drops in at launch.
Highlights
- ✓Founder–market fit: 16 years in ICU/ED critical care, including the NYC COVID-19 frontlines, plus an M.Eng in Cybersecurity and a nursing professorship at USD
- ✓IdeaFunding 2026 Catalyst Award winner ($10K, Arizona)
- ✓4 provisional patents filed (P1–P4); non-provisional filing targeted for June 2026
- ✓Runs entirely on-device, no cloud, no PHI, works offline; HIPAA-aligned by architecture
- ✓Prototype validated at the University of Arizona's ASTEC simulation center; invited to NSF Phase I and TechConnect's Critical Technology program
- ✓Hardware + recurring SaaS: a 250-rack hospital ≈ $1M hardware + $120K ARR, with customer ROI in under six months
The problem
Supply locations live in nurses’ heads. New, float, and agency staff are at risk the moment they walk into a room they’ve never worked in, and even veterans lose time in the supply room daily. Memory degrades under stress, and the high-stress moments of acute care are exactly when clinical recall fails hardest. Billions have gone into electronic health records; the supply room is still analog.
Supply locations live in nurses' heads, new and float staff are immediately at risk.
Cognitive recall degrades under stress; codes and traumas demand instant retrieval.
Billions invested in EHRs, almost nothing in modernizing the supply environment.
The supply room is the last analog system in the hospital
estimated annual U.S. productivity lost to supply-search inefficiency
lost per nurse, per shift, worst in codes and traumas, when recall fails hardest
“The patient is unstable. I need an IV start-kit and pulse ox now. I’ve checked every supply rack. It’s been over six minutes.”ICU nurse, Level 1 trauma center
A note from our founder
Robert Schmid
Before I was a founder, I was an acute-care nurse for sixteen years: ICU, the emergency department, and the COVID-19 frontlines in New York City during the worst days of the pandemic. I have held people’s lives in my hands, and I know what it costs when a minute disappears.
I’ve watched brilliant, experienced nurses lose critical time searching for a supply that should have taken seconds to find, in the middle of a code blue. We built Ambi so a nurse can simply speak, and the right slot lights up. It isn’t an efficiency tool. It’s a patient-safety intervention disguised as a supply rack.
Robert Schmid, MSN · CNS · M.Eng
Founder & CEO
Meet Ambi
So we built one. Ambi is a voice-activated, LED-guided supply retrieval system that lives directly on the supply rack. A clinician walks up, speaks the item they need, and Ambi illuminates the exact slot in seconds. No screens. No apps. No cloud. No PHI. Just the rack, the voice, and the light.
Under the hood, Ambi’s on-device speech recognition classifies the request, fuses it with long-term usage priors and short-term recency signals, and lights the correct slot in under a second. If the network goes down, or the hospital loses power to the server room , Ambi keeps working.
“Where are the 18-gauge IVs?”
Voice → on-device AI → light
Natural-language voice command. Hands-free, no screen.
Edge inference on the rack. No cloud. No PHI. Sub-second.
The exact slot illuminates. Zero searching.
Why it’s different: a deterministic embedded system
Ambi runs on DECA, a Deterministic Edge Context Architecture closer in lineage to aerospace and medical-device systems than to cloud AI. It’s built for environments where “mostly works” isn’t an option.
Runs entirely on the rack. Works when the network, or the server room, is down.
Patient data never leaves the rack. HIPAA-aligned by architecture; no attack surface.
A hardware watchdog enforces worst-case timing. Static memory allocation, no runtime surprises.
TinyML inference on ESP32-class silicon. Sealed housing for clinical environments.
It installs on any existing rack in about 30 minutes, no construction, no IT integration, no capital-committee approval.
Why now
Four forces converge at this exact moment: edge AI is finally practical on ultra-low-power microcontrollers; hospital operational strain has made nurse retention a board-level crisis; on-device compute has become a security requirement, not a preference; and hospitals want retrofit solutions they can deploy without construction or procurement cycles.
Four forces converging at once
TinyML on ≤2 MB MCUs delivers deterministic inference that was impossible 3 years ago.
Post-COVID burnout made nurse retention a board-level crisis.
PHI never leaves the rack. Cloud AI is a non-starter; HIPAA-aligned by architecture.
No construction, no procurement cycle. Installs on any existing rack.
Validation & traction
ICS is pre-revenue with a validated prototype. The recognition below cleared bars most early companies never reach, and we’re honest that paying pilots are still ahead of us, not behind. Securing the first written pilot commitment is the next milestone.
Recognized before revenue
Catalyst Award winner · $10K, Arizona
P1–P4 filed · non-provisional Jun 2026
Prototype validated at the ASTEC simulation center
Critical Technology Spotlight + oral presentation
Engineering collaboration (Dr. Hung Cao, NSF CAREER)
Invited to submit, program & status confirming
Market opportunity
We start where the stakes are highest and the pain is most documented, the hospital. But DECA doesn’t change between verticals; the vocabulary changes, the buyer changes, the architecture does not. The same system that guides a nurse to an 18-gauge IV can guide a soldier to a field kit or a technician to the right component.
Start where the stakes are highest
annual U.S. nurse productivity lost to supply search
6,090 U.S. hospitals × 250 racks × $2,500 hardware
Year-5 target: 280 hospitals, 4.7% of the base (ICS projection)
Business model & unit economics
Hardware up front plus recurring per-rack SaaS. A 250-rack hospital is roughly $1M in hardware and $120K in ARR, with customer ROI in under six months on recovered nurse time. Low capex means department-level approval, not the capital committee.
Hardware up front, recurring SaaS that compounds
Competition
ERP systems, RFID/RTLS, smart cabinets, and pick-to-light all answer “what’s in stock?” Ambi answers the question a nurse actually has mid-shift: “where is it, right now?” They track inventory. We drive execution.
They track inventory. We drive execution.
| Capability | ERP | RFID/RTLS | Smart Cab. | Pick-to-Light | ICS |
|---|---|---|---|---|---|
| Voice-activated retrieval | , | , | , | partial | ✓ |
| Light-guidance to item | , | , | , | ✓ | ✓ |
| On-device edge AI | , | , | , | , | ✓ |
| Retrofit-ready | partial | partial | , | , | ✓ |
| Adapts to workflow | , | partial | partial | , | ✓ |
| Sub-10s retrieval | , | partial | partial | partial | ✓ |
The team
Clinical credibility and engineering depth, at the exact intersection Ambi requires.
16 years of ICU/ED critical-care nursing, including five months on the NYC COVID-19 frontlines. MSN & CNS (UCSF Critical Care), M.Eng in Cybersecurity (USD), nursing professor at USD. Sits at the intersection of clinical workflow, edge AI, and secure systems design.
Chair of Electrical Engineering at USD. Former CEO of PCN Technology; prior roles at JPL and SRI International in robotics, control, and embedded systems.
Associate Professor, UCI HERO Lab. Biomedical sensors and bioelectronics for health monitoring. NSF CAREER awardee.
Budgeting, forecasting, cash-runway management, and investor-ready financials.
Engineering and operations.
Supported by a growing bench of clinical, regulatory, and embedded-systems advisors. Reference to USD and UCI is for identification purposes only and does not imply endorsement.
Roadmap
The campaign launches after the non-provisional patent filing. The milestones ahead:
Milestones in motion
Reasons to invest
Led by a 16-year critical-care nurse who also holds an M.Eng in Cybersecurity, the exact person to build secure, clinical-grade edge AI.
Four provisional patents and the DECA architecture: on-device, deterministic edge AI no inventory competitor offers.
IdeaFunding Catalyst Award, ASTEC validation, and an NSF Phase I invitation, third-party signals at the earliest stage.
The same architecture extends from hospitals to defense, aviation, logistics, and pharmacy, a large, staged opportunity.
As with any early-stage hardware + healthcare company, this opportunity is subject to scientific, execution, regulatory, and commercialization risks.
The ask & use of funds
ICS is raising on a SAFE through Regulation CF on Wefunder, launching after the non-provisional patent filing. Proceeds fund pilot deployments, the engineering team, DECA development, the patent filing, clinical benchmarking, and the data that unlocks NSF Phase I, getting Ambi into the hands of nurses providing care in hospitals in your community. Planned allocation: engineering 40% · sales & pilots 25% · operations 15% · G&A 10% · reserve 10%.
Risks
As with any early-stage company, this opportunity carries significant risk. ICS is pre-revenue; the product is in development and its performance figures are current design targets subject to clinical validation. The business depends on converting pilots to paying contracts, on the timing of the patent filing, and on manufacturing and regulatory execution. Results may differ from current expectations. Full risk factors will be disclosed in the Form C.
FAQ
A voice-activated, LED-guided supply retrieval system that lives on the supply rack. A clinician speaks the item; the exact slot illuminates in seconds, fully on-device, offline, with no PHI exposure.
ERP, RFID/RTLS, and smart cabinets track what's in stock. Ambi answers where it is, right now, and guides the clinician straight to it, adapting to the clinical workflow.
Patient data never leaves the rack. No cloud dependency means no attack surface and no failure during outages. HIPAA alignment is built into the architecture.
Pre-revenue with a validated prototype, four provisional patents, the IdeaFunding Catalyst Award, and ASTEC clinical-simulation validation. Securing the first paying pilot is the next milestone.
Pilot deployments, the engineering team, DECA development, the non-provisional patent filing, clinical benchmarking, and the data that unlocks NSF Phase I.
Invest in this round on Wefunder, or follow the campaign for updates and ask questions through the platform.
Help us put intelligence on every supply surface.
Your investment funds the pilots, the team, and the data that get Ambi into the hands of nurses who need it now, and builds the architecture for every shelf, rack, and bin where a human searches for something under pressure.
Invest now