Prepare before a procedure
Review procedure-specific decisions, risks, and teaching points without searching through full-length recordings.
Physician-reviewed surgical knowledge infrastructure
Designed for hospital-controlled on-premises / VPC deployment
Capture the reasoningsurgical video alonecannot preserve.
Hospitals already accumulate video, images, records, and device data. What rarely gets captured is why an expert acted, what risk they recognized, and how they adapted. MY ROBOTS converts permitted surgical video and audio into source-linked knowledge candidates that physicians approve, edit, or reject before reuse.
Recognition → Decision → Reaction
Video + permitted audioPhysician reviewedOn-prem / VPC
Phase 1 focuses on preparation, post-case review, education, and skill transfer—not autonomous diagnosis, treatment decisions, or unsupervised real-time guidance.
CONCEPT UIDesign and specifications subject to change
MY ROBOTS / AI Surgical MentorPhysician-reviewed surgical knowledge
What changes
Turn individual judgment into institutional memory.
The goal is not to create more recordings. It is to make the reasoning inside and around those recordings easier to find, validate, teach, and reuse.
Run focused case reviews
Return directly to source-linked moments and discuss what happened, why, and what should be retained.
Preserve expert reasoning
Capture the cues, decisions, cautions, and troubleshooting logic that are otherwise person-dependent.
Scale teaching across a team
Build a procedure-specific, physician-reviewed knowledge base for education and skill transfer.
Typical today
- Videos are stored, but learning moments remain buried.
- Expert explanations happen verbally and disappear.
- Teaching materials require repeated manual work.
With MY ROBOTS
- Key moments and reasoning are proposed with source timestamps.
- Physicians decide what becomes reusable knowledge.
- Approved knowledge can be searched and reused by procedure.
Clinical usefulness, review burden, and time impact are validated through focused pilots before broader deployment.
01 / The missing data layer
Clinical data accumulates.
Surgical reasoning does not.
Healthcare systems already capture enormous amounts of data. The scarce layer is often the expert reasoning that connects what was recognized to what was decided and how the team reacted.
Clinical evidence
- Electronic health records and procedure notes
- Laboratory values and pathology
- CT, MRI, X-ray and other imaging
- Prescriptions, claims and administrative data
- Surgical video and device logs when recorded
MY ROBOTS target layerRecognition↓Decision↓Reaction
The context that explains expert action.
Expert reasoning
- “Why is this the right plane now?”
- “What cue changed the approach?”
- “What makes this anatomy risky?”
- “What should a junior surgeon watch for next?”
- “How did the team respond when conditions changed?”
MY ROBOTS is built for this missing layer. It combines permitted video/audio context with AI-assisted extraction and mandatory physician review so tacit surgical know-how can become a traceable knowledge asset.
02 / Where we start
Knowledge before guidance.
The near-term product is deliberately centered on review, preparation, and education. This creates a safer, measurable path to value before considering any future intraoperative assistance.
Prepare with reviewed knowledge
Surface relevant decisions, risks, tips, and prior learning for a specific procedure.
Review exact moments and rationale
Connect discussion to the source timestamp, surrounding context, and physician-reviewed interpretation.
Build procedure-specific teaching assets
Turn selected cases into reusable material for trainees, departments, and institutional learning.
Current boundary: Phase 1 is not presented as autonomous diagnosis, an automated treatment decision maker, or unsupervised real-time clinical guidance. Any future intraoperative functionality would require separate clinical, safety, and regulatory assessment based on the exact function.
03 / How it works
From evidence
to institutional memory.
AI accelerates the first pass. Physicians determine what becomes trusted knowledge.
Permitted surgical video and audio enter a controlled workflow.
AI proposes candidate decisions, tips, pitfalls, and troubleshooting moments.
A physician approves, edits, or rejects each candidate.
Validated items retain source timestamps, reviewer state, and context.
Approved knowledge supports preparation, review, education, and skill transfer.
Core design principleAI proposes.
Physicians decide.
Physicians decide.
The system is designed to extend clinical knowledge—not replace clinical judgment.
04 / Product output
A source-linked
knowledge asset.
Not a generic transcript or summary. Each retained item is intended to preserve the clinically meaningful moment, rationale, review decision, and source context.
Decision pointTechniquePitfallTroubleshootingComplication preventionAnatomyTeachingSafetyEquipmentBest practice
MY ROBOTSSurgical Knowledge Sheet
Physician reviewedProcedureFocused procedure · de-identified caseReview statusCompleted
4knowledge items
3approved
1edited
DECISIONReconfirm the anatomical landmark before progression
ApprovedPhysician approved · linked to source moment
PITFALLPotential blind spot during the field transition
EditedEdited for clinical specificity · linked to source moment
TIPTechnique that stabilizes the next procedural step
ApprovedPhysician approved · linked to source moment
05 / Product concept
One review workspace.
Traceable end to end.
The current product direction connects source video, permitted audio, knowledge candidates, physician review, and searchable reuse in one controlled workflow.
CONCEPT UIDesign and specifications subject to change
06 / Reuse across the learning cycle
One case.
More than one use.
Prepare with relevant decisions and risks
Review procedure-specific, physician-approved knowledge without scrubbing through full recordings.
Reflect on what happened and why
Link discussion to exact moments, reviewer comments, and surrounding context.
Turn experience into shared memory
Build a reviewed knowledge base for education, continuity, and procedure-specific learning.
07 / Clinical design principles
Trust is part of
the architecture.
A knowledge item is only useful if teams can trace where it came from, who reviewed it, and how it changed.
Physician in the loop
AI output remains a candidate until a physician approves, edits, or rejects it.
RequiredTraceable to source
Each retained item stays linked to the relevant timestamp and surrounding case context.
Source-linkedProcedure-specific validation
Quality is defined within a focused procedure and clinical workflow before expansion.
FocusedHospital-controlled deployment
On-premises or private VPC patterns are selected according to partner governance requirements.
ControlledRole-based access and auditability
Permissions, reviewer state, and change history are designed to support accountable use.
AuditableThe product is under development and validation. Product scope, deployment architecture, and data-handling requirements are finalized with each partner before pilot use.
08 / Deployment & governance
Hospital-controlled
by design.
Surgical data requires a different operating model from ordinary SaaS. MY ROBOTS is being built to support controlled environments rather than assuming raw case data should move to a public cloud.
Local AI processing
An on-prem AI PC deployment pattern supports local video/audio processing and review workflows within the approved hospital environment.
Alternative controlled deployment
A private VPC pattern can be considered where partner security, networking, and governance requirements permit it.
Role-based permissions
Reviewer, department, and administrative access can be scoped so knowledge is reused only by authorized users.
Auditability and minimization
Source linkage, review history, de-identification, retention, and permitted use are defined with the partner organization.
Current product stage
MVP hardeningOn-prem integrationPhysician-review workflowFocused pilot readinessJapan + U.S. market validation
09 / From interest to pilot
Start narrow. Measure value. Expand only if it works.
The recommended starting point is one department, one procedure, a limited case set, and a small group of physician reviewers.
30-minute fit discussion
Clarify the target procedure, clinical need, recording environment, intended users, and governance constraints.
Define the pilot protocol
Agree the cases, data flow, knowledge categories, physician-review method, and measurable success criteria.
Run the focused pilot
Test ingestion, AI-assisted candidate creation, approve/edit/reject workflow, and source-linked output.
Decide from evidence
Evaluate usefulness, review burden, approval/edit/reject patterns, reuse, and whether paid expansion is justified.
10 / Recognition
Selected programs.
Global pathways.
Current recognition spans healthcare market entry, AI, edge computing, and global business development. Public cohort sizes are stated only where an official source is available.
2026Selected
JETRO GSAP 2026 — StartX AI Course
- Cohort
- 20 companies in the AI course
- Focus
- U.S. market entry and Silicon Valley business development
StartX-led AI acceleration for global business development, mentorship, and U.S. market validation.
Official JETRO page ↗2026Selected
J-StarX US Healthcare Breakthrough — Foundational Course
- Cohort
- 10 companies in the Foundational course
- Partners
- JETRO × Mayo Clinic Platform × Kicker Ventures
MY ROBOTS is publicly listed by JETRO among the 2026 Foundational cohort for U.S. healthcare market-entry support.
JETRO cohort announcement ↗2026Shortlisted
Qualcomm AI Program for Innovators 2026 — APAC
- Cohort
- Up to 15 shortlisted startups across APAC
- Current status
- Shortlist grant eligibility confirmed
Edge-AI development and commercialization support across Japan, Singapore, and South Korea, including mentorship and Qualcomm platform access.
Official Qualcomm page ↗View all selected programsExternal links lead to official program pages where available.
11 / NEWS
Current progress,
published carefully.
Product progress and external recognition are separated from clinical claims. We publish only what can be stated responsibly.
ProductSelectionProgramsCompany
Qualcomm QAIPI APAC shortlist grant eligibility confirmed
Following technical review, MY ROBOTS received confirmation that it passed the shortlist grant eligibility review for the 2026 APAC program.
Program details ↗JETRO publishes the 2026 J-StarX US Healthcare Breakthrough cohort
MY ROBOTS is listed among 10 companies selected for the Foundational course delivered with Mayo Clinic Platform and supporting partners.
Official announcement ↗On-premises MVP integration moves into final validation
The current build is being hardened around local video/audio ingestion, AI-assisted knowledge extraction, and the physician approve/edit/reject workflow.
Selected for the JETRO GSAP 2026 StartX AI Course
Selected for the 20-company AI course focused on U.S. market entry and Silicon Valley business development.
View all news Last updated: August 29, 2026
12 / Founder & company
Turning OR experience into a system for knowledge transfer.
Yoichi MiyazakiFounder & CEO
The company was founded from a recurring problem observed across decades in medical technology and operating-room environments: valuable clinical judgment is often explained in the moment, but rarely retained in a structured, reusable form.
MY ROBOTS is building the infrastructure to capture that missing layer while keeping physicians responsible for what becomes trusted knowledge and keeping deployment aligned with hospital governance.
“The scarce asset is not another recording. It is the reasoning that gives the recording meaning.”
CompanyMY ROBOTS Inc.
Founded2023
Based inYokohama, Japan
FocusSurgical Knowledge Infrastructure
Start with one procedure
Request a demo or focused pilot discussion.
We will clarify the target procedure, current recording environment, intended reviewers, deployment constraints, and the smallest useful pilot scope.
Please notePlease do not submit patient information, case images, medical records, or other sensitive clinical data through this form.