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Micromeet
Microware Group · 1985.HK · Est. 1985

Micromeet AI

AI for governed healthcare

Micromeet connects reports, consultations, follow-up, devices, and claim documentation into governed, doctor-reviewed continuous care.

41+ Years Enterprise Heritage
HKEX Listed · 1985.HK
ISO 27001 · 20000 · 9001 · 14001
HK · SG · CN · ID
micromeet.ai  |  Incubated by Microware Group (1985.HK)
Company Background

Microware Group

Hong Kong IT Leadership and Enterprise Delivery Foundation

Microware Group was established in 1985 and listed on the Main Board of the Hong Kong Stock Exchange in 2017 (1985.HK). The Group has long served government, public-sector, education, healthcare, finance and enterprise clients, with deep capability in enterprise IT services, systems integration, cybersecurity, managed services and regional delivery.

41
Years of Hong Kong enterprise IT service
1985.HK
HKEX Main Board listed · public governance
2,000+
Government, public-sector & enterprise clients
No.1
Hong Kong IT leader for government & large enterprise
Group Foundation

41 years of Hong Kong enterprise IT

Long-standing delivery to critical institutional clients has built enterprise project governance, systems integration, cybersecurity, operations and multi-site delivery.

Cross-sector Delivery

Healthcare, finance, government, enterprise, education

Experience across high-reliability, compliance-sensitive environments — from infrastructure and integration to ongoing service operations.

Regional Replication Base

Hong Kong, Mainland China & Southeast Asia

HK commercialization and compliance context, Shanghai R&D, Singapore coordination and Indonesia project experience support cross-market deployment.

Company Background & Product Positioning

Micromeet AI

Healthcare AI infrastructure for continuous care

Micromeet builds healthcare AI infrastructure for continuous care. It provides a governed patient-context runtime where healthcare institutions, clinicians, care teams, and AI agents run clinical and operational workflows together across reports, consultations, patient intake, booking, follow-up, telemedicine, connected-device data, and claim preparation.

ENTRY WORKFLOWS
MCU · AI Scribe / V2N · Intake workflows
Capture high-volume reports and consultations; route intake, booking, and follow-up tasks.
PATIENT CONTINUITY
Care Loop
Convert reports and encounters into next steps, review, booking, follow-up, and long-term care journeys.
CLAIM DOCUMENTATION
Claim Readiness
Prepare documentation completeness, coding readiness, and pre-submission review context.
INSTITUTION RUNTIME
Micromeet AI Care Command Center
Give teams one governed place for patient context, queues, human checkpoints, audit, and approved writeback.
INTEGRATION LAYER
Agent Browser · Integration Intelligence
Run workflows across existing HIS, EMR, LIS, booking, claims, and messaging systems.
Continuous care infrastructure logic
01
Clinical work
Reports, consultations, patient questions, bookings, device signals, and claim documents.
02
Shared context
One patient context that care teams and AI agents can use with governance.
03
Human checkpoints
Doctors and institution teams confirm clinical and operational decisions.
04
Existing systems
Approved integration paths connect HIS, EMR, LIS, booking, claims, and messaging systems.
05
Reusable assets
Workflow trace, feedback, evaluation, and templates improve the next deployment.
Continuous Care Runtime

From Clinical Work
to Continuous Care Journeys

Reports, consultations, patient questions, booking requests, telemedicine sessions, device signals, and claim documents stay connected to the same governed patient context, with doctor review and approved writeback where needed.

Shared patient context
Doctor-reviewed journeys
Existing systems stay source of record
What Micromeet Does

Run Your Workflows as Governed AI Workflows

Micromeet turns your intake, reporting, documentation, follow-up, claims, and operations into AI workflows your team runs with shared patient context, doctor review, human confirmation, and a full audit trail.

Service Capacity

Faster report turnaround for high-volume checkup and specialty reporting
AI Scribe / V2N returns documentation time after consultations
Guided intake prepares intake, booking and missing-information queues
Clear work queues help nurses, front desk, and care teams prioritize next actions
Existing teams serve more patients at the same governance standard

Quality & Governance

Doctor confirmation stays the clinical decision point
Source-linked knowledge keeps clinical and training outputs grounded
Standard templates keep reports, notes, and claims consistent
Audit trail preserves consent, review, and handoff records

Continuity & Governance

Care Loop turns reports and consultations into follow-up, recheck, and long-term management
Patient records stay consistent across departments and partner institutions
Referral coordination connects primary care, specialists, and hospitals
Claim Readiness strengthens pre-submission documentation where evidence is the bottleneck
Product & Platform

Current Product System, Five Distinct Layers

Daily workflow entries create clinical context; Care Loop and Claim Readiness turn it into continuity and claim preparation; AI Care Command Center is the institution runtime; Integration Intelligence connects existing systems; Healthcare Agent Platform is the architecture foundation.

01Layer 01Day-to-day workflow entries
MCU CoPilotAI Scribe / V2NIntake workflows
02Layer 02Patient continuity & claim preparation
Care LoopClaim Readiness
03Layer 03Institution runtime
AI Care Command Center
04Layer 04Integration layer
Agent BrowserIntegration IntelligenceApproved writeback
05Layer 05Architecture foundation
Micromeet Healthcare Agent Platform
Architecture · Integration Intelligence

AI Agents Inside the Systems You Already Run

Through a customer-authorized Agent Browser, our agents work inside your existing HIS, EMR, LIS, booking and payer screens — reading the context you approve, drafting the work, and writing back only what your staff confirm. Your systems stay the source of record, with Micromeet connecting as an enhancement layer to existing workflows.

Read approved context→AI drafts→doctor approves→write back→audited
Agent Browser · inside your screens

A customer-authorized, controlled workspace. Agents act only inside approved systems, pages and workflows — with domain boundaries, permission scope, audit records, and human confirmation on every high-risk write.

Institution runtime · AI Care Command Center

AI Care Command Center is the institution-side runtime for coordinating approved Micromeet workflows. It sits above the Healthcare Agent Platform and works with existing systems as the source of record.

Micromeet Healthcare Agent Platform · run, observe, improve

Micromeet Healthcare Agent Platform is the architecture foundation for governed agent runs, shared context, approvals, audit, evaluation and continuous improvement across workflows.

Integration Intelligence

Field engineers plus UI / API / workflow mapping discover and validate your workflow context — so approved integration scope is defined in weeks and reused across sites, with permission boundaries and audit records.

Enhancement layer for existing systems Human approval on every write Full audit & run replay Your HIS / EMR stays source of record
Governed AI Operations

How Micromeet Runs AI Safely in Healthcare

Micromeet runs agents through a controlled operating model: approved context, clinical rules, system boundaries, human checkpoints, and traceable evidence for every workflow.

01
Context
The patient information an agent may use — identity, timeline, reports, encounters, clinical signals, device data — assembled per task.
02
Clinical knowledge
The medical rules it follows: signal thresholds, guideline versions, red flags, escalation and care-pathway logic.
03
Architecture
The system boundary: workflow state, task queues, role workspaces, connectors, and a source-of-truth map for safe write-back.
04
Governance
What runs automatically versus what needs human approval — consent, role permissions, release control, doctor review, full audit.
05
Evidence & convergence
Every workflow leaves a traceable, QA-checked record, and each deployment promotes what worked into reusable templates.
Micromeet AI › Entry Points › MCU CoPilot

MCU CoPilot

From weeks to days: under doctor review, report generation, quality control, risk stratification, company reports, and post-report patient management run as one workflow.

The Problem
High-volume MCU programmes stall when report writing and QC stay manual; uneven report quality limits patient trust and caps how many clients an institution can serve.
The Solution
MCU CoPilot standardizes checkup data, drafts doctor-reviewed reports, stratifies risk, generates batch company reports with year-over-year comparisons, and hands high-risk patients into Care Loop.

Leadership Priorities

Move report generation from weeks to days
Raise MCU report quality and consistency
Improve team operating efficiency
Expand institutional MCU service capacity
Improve patient satisfaction after report delivery

Institution Value

Turnaround From weeks to days against baseline
Report quality Standardized structure, doctor review, exception checks
Capacity ceiling More reports and corporate clients on the same team
Post-report value Risk stratification, company reports, Care Loop handoff
From weeks to days
Risk stratification
Company reports
Care Loop handoff
Micromeet AI › Entry Points › AI Scribe / V2N

AI Scribe / V2N

Efficiency and record quality together: helps doctors produce standardized electronic records faster while preserving doctor confirmation and institutional governance.

The Problem
Physicians lose time writing records, and inconsistent note quality weakens institution operations, data quality, and post-visit continuity.
The Solution
AI Scribe / V2N captures physician speech and produces standardized electronic record drafts, decision context, and follow-up cues for doctor confirmation.

Two Value Pillars

Reduce doctor documentation burden
Shorten encounter-to-record turnaround
Standardize record structure and field quality
Enable high-quality notes within consultation time
Improve continuity and patient confidence

Operational Value

Doctor efficiency Less time spent on writing
Institution efficiency Faster record completion and fewer handoff gaps
Record quality Standardized structure and doctor-reviewed content
Patient value Clearer summaries, follow-up, referral context
Micromeet AI › Continuity › Care Loop

Care Loop

Care Loop turns one report or visit into a governed continuity workflow — one record across clinical review, follow-up queues and institution service fulfilment. AI prepares the work; people make the decision.

Clinical review queue
AI findings, evidence chain and a risk queue enter the doctor review workspace.
ECG, BP, reports, symptoms and wearable trends merge on one timeline.
Clinical conclusions and recheck plans are confirmed by doctors.
Follow-up operations
Report explanation, risk summary, recheck reminders and follow-up plans, presented readably.
Patients enter scenario pathways — hypertension, cardiovascular, diabetes, oncology follow-up or fall prevention.
Device binding and data return support continuous observation.
Institution service fulfilment
Service-package configuration, benefit activation, fulfilment progress and exception tickets.
Risk-cohort stratification, follow-up completion and recheck-loop closure.
Monthly service reports, audit records and measurable operating indicators.
The conversion engine
Report / MCU · consult / AI Scribe / V2N · device alert · referral → report explanation → doctor-reviewed next step → recheck / referral → monitoring → long-term management — one report or visit becomes a packaged, repeatable service.
Governed by design
Review context for doctors. Software describes the observed data; the doctor directs the next step and signs.
Micromeet AI › Connected Care › Devices & Remote Monitoring

Connected Care, Device to Doctor

Hardware is the front-end sensing layer of continuous care. Devices feed the patient record by scenario; the same governed workflow layer turns trends into doctor-reviewed action. Devices observe; doctors decide.

S1Hypertension
BP monitor, smart ring and optional ECG enter follow-up queues.
S2Cardiovascular
Holter, ECG patch, BP and night vitals form the evidence chain.
S3Weight & metabolic
Body scale, body composition and behaviour data support long-term management.
S4Diabetes
BGM, CGM, urine and biochemical tests support risk stratification.
S5Oncology follow-up
WBC, SpO2, urine and biochemical POCT support out-of-hospital follow-up.
S6Elderly home safety
Fall detection, SOS, location and family / service response create a safety loop.
Device service package
Selected by clinical scenario, certification and replicability — with onboarding, follow-up queues, abnormal review, local spares and after-sales in one operating system.
Evidence boundary
Wearable trends support continuous observation; rhythm judgments such as AF route to ECG patch, Holter, 12-lead ECG and a doctor's review.
Micromeet AI › Institution Workflow › Claim Readiness

Claim Readiness

Micromeet helps prepare more complete, reviewable and coding-ready claim documentation before submission — turning records captured through AI Scribe / V2N, MCU, and institution workflows into audit-traceable claim packages.

From encounter context to a claim-ready package
Encounter context → ICD / procedure suggestion → Completeness check → Claim risk flag → Coder / casemix queue → Claim-ready export
Institution workflow roles
Clinical documentation teams
More complete documentation before submission, with clearer accountability for claim preparation.
Coding & casemix teams
A priority queue surfaces claims that need human coding review and keeps the evidence trail attached.
Operations & finance teams
Evidence packages and review queues are organized for internal checks before payer submission.
Coder- and doctor-confirmed. Micromeet prepares claim-ready context from records you already capture; coders and clinicians confirm the codes and sign, while final payer adjudication remains with the payer.
Deployment Foundation

Deployment Foundation for Regulated Healthcare

Micromeet deploys in cloud, hybrid, or on-premise models, with data control, security, service resilience, and procurement needs agreed institution by institution.

Data Sovereignty

Patient data boundaries by jurisdiction
Role-based access and consent logs
Institution-approved retention policies
Audit-ready data handling

Cloud / Hybrid / On-Premise

Deployment chosen by policy and workload
Supports private clinical environments
Hybrid inference for multi-site operations
Works with your current systems

AI Compute Capacity

Right-sized compute for documentation, reports, and claims
Edge options for sensitive workloads
Scales from first workflow scope to multi-site institutional adoption
Cost profile managed by workload class

Secure Hospital Network

Network segmentation for clinical systems
Secure access between departments
Redundancy and failover planning
Operational monitoring for uptime

Clinical Storage & Backup

Structured and unstructured clinical records
Backup, retention, and recovery planning
Support for institution document archives
Designed for clinical audit needs

Service Resilience

Service levels defined by deployment model
Operational support and incident process
Usage, performance, and exception monitoring
Expansion criteria after first workflow review
Representative Institution Workflow Patterns

Three Workflows Micromeet Supports

Workflow pattern A

High-Volume Checkup Operations — MCU CoPilot

Leadership issue: multi-week report backlog limits employer reporting, abnormal-result follow-up, and population-health visibility.

• Micromeet value: automated report drafting with doctor review
• KPIs: turnaround, review completion, abnormal-result follow-up
Workflow pattern B

Claim Documentation Readiness — Claim Readiness

Leadership issue: evidence, coding context, and document completeness are inconsistent before submission.

• Micromeet value: claim-readiness check before submission
• KPIs: review readiness, reviewer load, audit evidence completeness
• Human confirmation remains required
Workflow pattern C

Continuous Care Coordination — AI Care Command Center + Care Loop

Leadership issue: referrals, patient context, and post-visit actions are fragmented across departments, institutions, and patient-management teams.

• Micromeet value: shared patient record, queue ownership, referral continuity
• KPIs: coverage, continuity, governance readiness
• Supports controlled institutional rollout

All client identities are anonymised per disclosure policy. Case details are presented as representative institution workflows.

Start with a Focused Workflow

Microware Group · 1985.HK
Micromeet AI for governed healthcare
Workflow Assessment
First Workflow Scope
Enterprise SLA
Doctor-in-the-loop Governance

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