Camino Robotics Walking Toward Better Health AI Enhanced Mobility Solutions Driving Clinical Insig

Company & Problem

• Company: Camino Robotics (brand: Commamino Mobility)
• Co-founder/CEO: Duncan Orl Jones
• Focus: “Elderly mobility,” prompted by observing a “silent pandemic” of decline from mobility issues.
  • Examples cited:
    • Parkinson’s in father
    • Fall → sedentary spiral and death within ~18 months for mother
• Market need: Walking improves health span, but existing assistive devices are described as stigmatizing, cumbersome, and not integrated with clinical or insight workflows.

Customer Insights & Unmet Need

Stigma & usability issues with current devices

• Human-powered/push devices are described as:
  • “difficult to push”
  • “super cumbersome”
  • not user-friendly (e.g., not folding like a baby stroller)

Clinical gap

• Current solutions do not provide actionable insights that help inform care decisions.

Go-to-Market (GTM) Strategy (Stated Direction)

Initial model: Consumer cash-pay

• Why: DME reimbursements for rollators exist but are described as small.
• Near-term demand is driven by willingness to pay “several thousand” for lifestyle improvements.

Long-term model: Shift toward B2B

• Target users: health systems and value-based care providers
• Value proposition: device data helps reduce readmissions and enables remote rehab assessment.

Distribution & partnerships (examples)

• Distributors: inbound interest globally; active engagement with a major US distributor.
• Manufacturing ramp: fundraising over the next few years to reach manufacturing and the first “couple hundred” devices for end users.

Product & Differentiation: The “Smart Walker” Platform

Core proposition

• A power-assist smart walker that communicates activity vs. disability, with progressive software capability over time.
• Framed as a “Tesla of walkers.”

Feature buckets (playbook structure)

1. Commamino (automatic power assist)

   • Automatic adaptation to the environment (no pushing required)
   • Goal: reduce user effort and increase confidence and ambulation

2. Commamino Guardian (safety automation)

   • Automatic downhill braking
   • Parking brake when the user sits/turns to prevent scooting
   • Automatic headlights at night

3. Embedded AI gate analytics (on-device)

   • No cloud video storage: analytics are processed on-device
   • Produces gate (gait) metrics (later stated as ~26 different gate metrics)
   • Supports:
     • fall risk stability predictions
     • rehab progress tracking
   • High data throughput: “thousands of data points per minute”

Clinical & Technical Progress Milestones

Core technology developed

• Power assist systems
• Embedded AI gate analytics
• Hybrid AI braking system
• Mobile app + cloud/backend + fleet monitoring
• Cybersecurity/regulatory requirements

Regulatory progress

• “Through all the regulatory challenges” over the last ~1.5 years

IP status

• 1 patent granted
• 2nd patent filed
• 3rd patent “should be filed this month”

Proof Points & Outcomes (Metrics/KPIs)

Walk improvement vs baseline (pilot/test)

• Test users previously wore Fitbits; during trials, they walked up to 5x more than before (as described).

Engagement & value signals

• “Motivational” feedback; device “watching them”
• Increased confidence, including safety assist in familiar environments (e.g., headlights enabling movie theater navigation)

AI analytics scope

• ~26 gait metrics
• AI reconstructs 3D limb/foot positioning from video frames (described as feet position plus leg data points)

Clinical Use Cases (B2B Value)

The clinical application is framed in three buckets:

1. Red flags: detect changes in gait/activity/instability to increase risk identification
2. Rehab care enablement: support recovery for chronic and ongoing conditions
3. Treatment tracking: personalize treatments and track progression remotely

B2B hospital deployment ideas

• Assessment for discharge
• Virtual PT / remote standardized tests
• Reduced risk of readmission
• Post-discharge monitoring to maintain ongoing insight

Concrete Commercial Traction (Pipeline/State)

Customers & waitlist

• “Hundreds” of customers on a wait list.

Pilots & contracts timeline

• Pilot contracts starting towards the end of this year / beginning of next year

Named partnership signals

• LOI from one of the largest value-based care providers on the West Coast
• Grant-funded clinical trial planning with a major rehab hospital
• Multiple retirement communities lined up for pilots

Integration & data delivery direction

• Not deep into EHR specifics yet; working with integrators
• Clinician-oriented delivery via dashboards and red-flag focused outputs (not raw data dumps)
• Possible initial EHR integration via flat files
• Packaging with hospital clinicians during trials

Pricing & Business Model (As Described)

• Short-term: consumer cash-pay (with B2B aspiration long-term)
  • Device cost “several thousand” dollars is framed as a “slam dunk” for many users due to lifestyle impact and continued ambulation benefits.
• Long-term: expect DME reimbursement similar to power wheelchairs.
• B2B concept: “Hardware as a Service”
  • Hospital system receives devices without upfront purchase
  • Devices support assessment and discharge; insights continue post-discharge
  • Devices can be recycled for subsequent patients (revenue + marketing channel angle)
• Remote therapy reimbursement alignment
  • Notes existing reimbursements for remote therapy monitoring, with their data making remote rehab more feasible.

Marketing & Channel Strategy

• Low marketing so far
  • “Almost no marketing,” with plans to gear up marketing next year
• Website mentioned as collateral, with no further details provided.

Frameworks/Playbooks Explicitly Used

• No formal frameworks (e.g., OKRs/SWOT) were named.
• The pitch uses a structured decomposition:
  • Three-bucket product architecture: power assist + safety automation + embedded AI gait analytics
  • Three clinical outcome buckets: red flags, rehab care enablement, treatment tracking/personalization

Risks/Constraints Mentioned

• EHR/data packaging challenge: clinicians don’t want “data dumps”; need actionable dashboards and red flags
• Pilot logistics constraint: battery/pilot readiness requires users to stay off airplanes (airport-readiness mentioned as a future improvement)
• AI/processing constraint: on-device analytics are “super difficult” due to privacy and computational requirements

Presenters / Sources

• Presenter: Duncan Orl Jones (Co-founder and CEO, Camino Robotics / Commamino Mobility)

• Other sources mentioned in the video context:

  • Bill Gross (startup incubator founder; Idealab/Idealab Studio; co-founder intro cited)
  • Ivar (multi-startup CTO; described as recovering quadriplegic and walking with a walker)
  • German semiconductor company (component supplier; related video segment)
  • ARP (partner associated with the featured video segment)
  • Pilot/test user (featured testimonial; name not provided)
  • Advising physician from a major value-based care provider (badge blurred; name not provided)
  • Multiple undisclosed healthcare partners (value-based care provider, rehab hospital, retirement communities, distributor/distribution partner; names not shown in subtitles)