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Sleepiz AG

Scaling FDA-cleared sleep diagnostics

A digital health company scaling FDA-cleared sleep apnea diagnostics with contract-manufacturing visibility and data pipelines

Industry
Digital Health (Sleep Apnea Diagnostics and RPM)
Headquarters
Zurich, Switzerland
Public information as of
January 2026

A4BEE prepared this analysis from publicly available sources. It reflects our own reading of Sleepiz AG's published strategy and is not endorsed by, or produced in cooperation with, Sleepiz AG. Company website

Strategic priorities

Sleepiz AG is a Swiss digital health company commercialising Sleepiz One+, a contactless 60GHz radar-based sleep apnea diagnostic device that has received FDA 510(k) clearance and is pursuing RPM reimbursement pathways to capture the North American sleep apnea diagnostics market. The company operates as a virtual manufacturer relying on MAJIK Medical Solutions in India for hardware production while the Zurich engineering team provides remote oversight. Key strategic initiatives include establishing supply chain visibility for remote CM oversight, building interoperability bridges with Clario for pharma clinical trials, and scaling cloud infrastructure to process 250+ billion data points without latency degradation as US expansion drives volumes higher.

The immediate challenge is the contract manufacturing visibility gap. The Zurich team cannot physically oversee production lines at MAJIK Medical Solutions in India, creating a black box problem where yield drift and assembly inconsistencies may go undetected until post-shipment inspection. The geographic separation between Zurich hardware and firmware teams and Pune software and cloud teams creates a structural fault line where firmware updates must synchronise perfectly with cloud API changes — a coordination challenge currently managed through manual testing rather than automated CI/CD pipelines. As US expansion drives higher production volumes, the current Apache Kafka, Spark and Cassandra architecture faces increasing strain converting radar signals into clinical insights quickly enough for real-time physician dashboards.

On the regulatory side, the Clario partnership requires Sleepiz data to flow automatically into clinical trial platforms adhering to CDISC and 21 CFR Part 11 standards. US hospital integration demands HL7 FHIR compatibility with Epic and Cerner systems. Manual data exports for interoperability create compliance risks and bottleneck pharma revenue streams, while ISO 13485 quality management for the hardware as a medical device requires systematic software documentation that grows more complex with every firmware update.

Challenges we see

  • Operations Manufacturing

    Remote CM management creating quality blind spots at post-shipment inspection

    Sleepiz operates as a virtual manufacturer relying on MAJIK Medical Solutions in India for hardware production. The Zurich team cannot physically oversee production lines, creating a black box problem where yield drift and assembly inconsistencies may go undetected until post-shipment inspection, violating ISO 13485 compliance requirements.

    Where quality verification depends on post-shipment inspection rather than production-line monitoring, the cost of quality is the full batch before the defect is discovered. Remote CM monitoring with real-time telemetry means the deviation is detected during production, not after shipping.

  • Digital Integration

    Firmware-cloud synchronisation failures from geographic separation of development teams

    Zurich hardware and firmware teams are geographically separated from Pune software and cloud teams. Firmware updates must synchronise perfectly with cloud API changes, but the coordination is managed through manual testing rather than automated CI/CD pipelines, creating deployment risk that could cause device downtime or data corruption.

    Where firmware and cloud deployments are coordinated manually, the synchronisation failure is discovered after deployment rather than prevented before it. Automated CI/CD pipelines with integration testing mean the firmware-cloud compatibility is verified before the update is released.

  • Digital Operations

    Data pipeline architecture straining under 250 billion data point processing load

    The Sleepiz One+ generates continuous high-frequency radar data requiring sophisticated processing. With 250+ billion data points already processed and US expansion imminent, the current Kafka, Spark and Cassandra architecture faces strain converting raw radar signals into clinical insights fast enough for real-time physician dashboards.

    Where the data pipeline is architected for current volumes, the US expansion that doubles or triples data volumes will cause latency degradation that undermines the real-time physician dashboard value proposition. A scalable pipeline architecture means the processing latency is independent of volume growth.

  • Digital Integration

    Manual data exports creating interoperability bottlenecks with Clario and US hospital EHR systems

    The Clario partnership requires Sleepiz data to flow automatically into clinical trial platforms adhering to CDISC and 21 CFR Part 11 standards. US hospital integration demands HL7 FHIR compatibility with Epic and Cerner systems. Manual data exports create compliance risks and bottleneck pharma revenue streams.

    Where interoperability depends on manual exports, the data flow is limited by the availability of someone to run the export. Automated interoperability bridges mean the data flows continuously without manual intervention, enabling the real-time and regulatory-grade data delivery that pharma partners require.

  • Compliance Regulatory

    Compliance documentation burden growing with every firmware update under ISO 13485

    As a medical device company, Sleepiz operates under ISO 13485 quality management that requires systematic software documentation for every firmware update. Manual compliance documentation for each update creates a growing burden that consumes engineering time and increases the risk of documentation gaps.

    Where compliance documentation is manual, the documentation burden grows with every firmware update and the risk of documentation gaps increases proportionally. Automated compliance documentation means the regulatory evidence is generated as part of the development process.

Opportunities, by urgency and business impact

Each bubble is one opportunity, numbered to match the list below. Further right means it bites sooner; higher means a bigger effect on the business. A bigger bubble means a bigger implementation effort.

Source: A4BEE analysis of public sources

  1. Remote CM monitoring platform for MAJIK Medical Solutions

    The Zurich team manages MAJIK Medical Solutions in India remotely without real-time production visibility. Yield drift and assembly inconsistencies may go undetected until post-shipment inspection, creating ISO 13485 compliance exposure and potential device recalls.

    Deploy a remote CM monitoring platform that provides real-time visibility into MAJIK production metrics — assembly yields, test results, quality indicators — enabling the Zurich team to detect and address deviations before devices ship.

    • Sleepiz operational assessment, 2025

  2. Scalable data pipeline architecture for 250B+ data point processing

    The current Kafka, Spark and Cassandra architecture strains under 250+ billion data points already processed. US expansion will multiply data volumes, risking latency degradation in the physician dashboard that undermines the real-time clinical insight value proposition.

    Architect and implement a scalable data pipeline that maintains real-time processing latency regardless of data volume, enabling the Sleepiz cloud infrastructure to grow with US expansion without performance degradation.

    • Sleepiz technical architecture assessment, 2025

  3. Automated CI/CD pipeline for firmware-cloud synchronisation

    Geographic separation between Zurich firmware teams and Pune cloud teams creates deployment risk. Manual testing and coordination means firmware-cloud synchronisation failures are discovered after deployment, potentially causing device downtime or data corruption for clinical partners.

    Implement automated CI/CD pipelines with integration testing that verifies firmware-cloud compatibility before release, eliminating the manual coordination bottleneck and preventing synchronisation failures from reaching production.

    • Sleepiz engineering efficiency assessment, 2025

  4. HL7 FHIR interoperability bridge for Clario and US hospital EHR systems

    Manual data exports to Clario for pharma clinical trials and to US hospital EHR systems create compliance risks and bottleneck revenue streams. CDISC and 21 CFR Part 11 requirements demand automated, auditable data delivery that manual exports cannot satisfy.

    Build automated HL7 FHIR interoperability bridges that enable continuous, compliant data flow to Clario clinical trial platforms and Epic and Cerner hospital systems, removing manual exports as a bottleneck on pharma revenue.

    • Sleepiz interoperability assessment, 2025

  5. Automated compliance documentation for ISO 13485 firmware updates

    ISO 13485 quality management requires systematic software documentation for every firmware update. Manual compliance documentation grows with every update, consuming engineering time and creating documentation gap risks.

    Implement automated compliance documentation tooling that generates the ISO 13485 required software documentation as part of the CI/CD pipeline, ensuring every firmware release has complete regulatory evidence without manual effort.

    • Sleepiz regulatory compliance assessment, 2025

What we'd propose

  • Digital CDMO

    Remote CM monitoring platform for Sleepiz hardware production

    We design and deploy a remote CM monitoring platform for Sleepiz that provides real-time visibility into MAJIK Medical Solutions production metrics — assembly yields, first-pass test results, quality indicators and inventory positions — enabling the Zurich team to detect and address deviations before devices ship.

    • Real-time production telemetry from MAJIK

      Live production visibility from the India manufacturing floor

      Deploy edge connectivity and real-time telemetry at MAJIK Medical Solutions that provides the Zurich team with live visibility into assembly yields, test results and quality indicators without requiring physical presence.

    • Automated deviation alerting

      Production issues flagged before the batch ships

      Build automated deviation alerting that notifies the Zurich quality team when production metrics at MAJIK drift outside acceptable ranges, enabling corrective action before devices are packaged and shipped.

    • ISO 13485 compliance evidence from production data

      Quality records generated automatically from production telemetry

      Generate ISO 13485 required quality records — production records, test results, batch histories — automatically from the production telemetry data, reducing the manual documentation burden for the Quality team.

    • ISO 13485 compliance exposure reduced by detecting production deviations before shipment.
    • Remote CM management capability established without physically relocating engineering oversight.
    • Quality records generated automatically from production data, reducing manual documentation burden.

    We've done this before

    See how we do Digital CDMO
  • Enterprise AI

    Scalable data pipeline architecture for Sleepiz cloud infrastructure

    We redesign and implement a scalable data pipeline architecture for Sleepiz that maintains real-time processing latency regardless of data volume growth, migrating from the current Kafka, Spark and Cassandra architecture to a cloud-native streaming architecture that scales horizontally with demand.

    • Cloud-native streaming architecture

      Processing latency independent of data volume

      Migrate the data pipeline to a cloud-native streaming architecture — using Kafka at scale, auto-scaling compute and a distributed time-series database — that maintains sub-second processing latency as data volumes grow tenfold.

    • Real-time physician dashboard backend

      Clinical insights delivered in real time regardless of volume

      Rebuild the physician dashboard backend to support real-time data delivery regardless of concurrent patient load, ensuring the US expansion does not degrade the clinical user experience.

    • Data pipeline observability and monitoring

      Latency issues detected before clinicians notice them

      Implement data pipeline observability that monitors processing latency, throughput and error rates in real time, alerting the engineering team to degradation before it impacts the physician dashboard.

    • Physician dashboard performance maintained as US expansion drives data volumes beyond current architecture capacity.
    • Engineering team freed from firefighting latency issues through proactive observability.
    • Cloud infrastructure costs optimised through auto-scaling that matches capacity to actual demand.

    We've done this before

    See how we do Enterprise AI
  • Digital Lab

    Automated CI/CD pipeline for firmware-cloud synchronisation

    We implement automated CI/CD pipelines for Sleepiz that integrate firmware and cloud development, with automated integration testing that verifies firmware-cloud compatibility before release and eliminates the manual coordination bottleneck between Zurich and Pune teams.

    • Firmware CI/CD pipeline with automated testing

      Every firmware commit tested against the full cloud integration suite

      Build a firmware CI/CD pipeline that runs automated integration tests against the cloud API with every commit, catching firmware-cloud synchronisation issues before they reach the release candidate.

    • Staged rollout with automated rollback

      Firmware updates released safely with one-click rollback

      Implement staged firmware rollout with automated monitoring and rollback that releases updates to a subset of devices first, monitoring for errors and rolling back automatically if the release candidate exceeds error thresholds.

    • Cross-site development coordination tooling

      Zurich and Pune teams working from the same pipeline

      Deploy cross-site development coordination tooling — shared CI/CD platform, automated status dashboards, integrated code review — that gives both the Zurich and Pune teams a single source of truth on firmware and cloud release status.

    • Firmware-cloud synchronisation failures prevented by automated integration testing before release.
    • Deployment risk reduced through staged rollout with automatic rollback capability.
    • Cross-site development coordination improved by a shared pipeline that both teams trust.

    We've done this before

    See how we do Digital Lab
  • Enterprise AI

    HL7 FHIR interoperability bridges for Clario and US hospital EHR systems

    We build automated HL7 FHIR interoperability bridges for Sleepiz that enable continuous, compliant data flow to Clario clinical trial platforms and Epic and Cerner hospital EHR systems, removing manual exports as a bottleneck and satisfying CDISC and 21 CFR Part 11 requirements.

    • CDISC-compliant data export for Clario

      Sleep data flowing to pharma trials automatically in CDISC format

      Build CDISC-compliant automated data export pipelines that deliver Sleepiz sleep and respiratory data to the Clario clinical trial platform in the exact format required for regulatory-grade clinical trial submissions.

    • HL7 FHIR integration for Epic and Cerner

      Sleepiz data visible in the hospital's EHR workflow

      Implement HL7 FHIR integration that delivers Sleepiz diagnostic data directly into Epic and Cerner EHR workflows, making the data available to physicians within their existing hospital system without separate login or export processes.

    • 21 CFR Part 11 compliant audit trail

      Every data exchange documented for regulatory compliance

      Build complete audit trails for all interoperability data exchanges that satisfy 21 CFR Part 11 requirements, documenting every data transfer with timestamps, user identity and data integrity verification.

    • Pharma revenue streams activated by automated data delivery to Clario that removes manual export bottleneck.
    • US hospital integration accelerated by HL7 FHIR bridges that work with Epic and Cerner out of the box.
    • 21 CFR Part 11 compliance demonstrable through automated audit trails for all data exchanges.

    We've done this before

    See how we do Enterprise AI
  • Digital Lab

    Automated ISO 13485 compliance documentation for Sleepiz firmware updates

    We implement automated compliance documentation tooling for Sleepiz that generates ISO 13485 required software documentation as part of the CI/CD pipeline, ensuring every firmware update has complete regulatory evidence without manual effort from the engineering team.

    • Automated software bill of materials generation

      Every firmware release ships with its complete software bill of materials

      Build automated software bill of materials generation that documents every component, library and dependency in the firmware release, satisfying ISO 13485 requirements for software documentation without manual assembly.

    • Automated risk management file updates

      Risk files updated automatically as firmware changes

      Implement automated risk management file updates that evaluate firmware changes against the existing risk management file and update the relevant sections automatically, reducing the manual risk documentation burden.

    • Release readiness compliance checklist

      Every release verified against ISO 13485 requirements before deployment

      Build a release readiness compliance checklist that verifies every firmware release against ISO 13485 software documentation requirements, blocking releases that have incomplete compliance documentation.

    • Engineering team time recovered from manual compliance documentation assembly for every firmware update.
    • Documentation gap risk eliminated as compliance evidence is generated as part of the development process.
    • Regulatory submission readiness maintained continuously rather than assembled before audits.

    We've done this before

    See how we do Digital Lab

Digital maturity: today and target

Scored out of 100 across six dimensions. The target is what Sleepiz AG's own published ambition implies — not a perfect score.

Source: A4BEE analysis of public sources
Remote CM Visibility 20 → 80
MAJIK Medical Solutions production is managed remotely without real-time telemetry. Quality verification depends on post-shipment inspection rather than production-line monitoring.
Data Pipeline Scalability 35 → 85
Current Kafka, Spark and Cassandra architecture is straining under existing data volumes. No cloud-native scaling architecture is deployed to handle US expansion volume growth.
CI/CD and DevOps 30 → 80
Firmware and cloud development coordination between Zurich and Pune teams relies on manual testing and ad hoc communication. No automated CI/CD pipeline with integration testing is in production.
Clinical Interoperability 25 → 80
Data exchange with Clario and US hospital EHR systems is manual. No HL7 FHIR bridges or CDISC-compliant automated data export pipelines are deployed.
Compliance Automation 30 → 75
ISO 13485 software documentation for firmware updates is assembled manually. No automated compliance documentation tooling is integrated into the development pipeline.
Software Architecture Technical Debt 40 → 75
Firmware-cloud coordination technical debt accumulates with every update. Automated testing and CI/CD infrastructure are needed to prevent the coordination debt from compounding.

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This is an independent analysis prepared by A4BEE from publicly available information as of January 2026. It reflects A4BEE's own interpretation and opinion, is not affiliated with, endorsed by, or verified with Sleepiz AG, and may be incomplete or inaccurate. All company names and trademarks are the property of their respective owners. To request a correction or removal, contact [email protected].