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Myco

Updating the operating model

Industry
Biotechnology
Public information as of
January 2026

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

Strategic priorities

Myco operates across 4 stated priorities, with the most concrete near-term plan anchored on rapid manufacturing at scale.

Achieving "units of seconds" cycle times through proprietary thermo-pressing technology, enabling price parity with EPS and eliminating the grow-in-mold bottleneck that limits competitors.

Delivering a -1.305 kg CO₂e/kg cradle-to-gate footprint through upcycling of agricultural waste (sawdust, hemp), creating measurable Scope 3 benefits for B2B clients.

Strategic partnership with SEMA engineering to deploy semi-automated production systems achieving 300% capacity gains and 5-8x worker productivity improvements.

Challenges we see

  • Operations Manufacturing

    Production Scale-Up from Pilot to Industrial

    MYCO operates from an 800 m² facility in Bzenec and is preparing for Series A funding to build a second-generation pilot line with 10x capacity. The transition from semi-automated pilot scale to full industrial throughput (15 pads/second) requires significant engineering and control system upgrades.

    Scaling biological manufacturing introduces variability risks; without durable process control, inconsistent quality could damage B2B relationships where every corner pad must fit precisely into cardboard boxes.

  • Digital Manufacturing

    Biological Process Variability Control

    Mycelium growth is inherently biological and variable. The SEMA machine introduced industrial control loops (pressure, temperature, time), but as MYCO scales to modular "mini-factory" deployments at customer sites, maintaining repeatability across distributed production becomes critical.

    Crop failure or contamination in the facility could halt production. Biological variability without real-time monitoring may result in batch rejections and customer attrition.

  • Compliance Regulatory

    Digital Product Passport (DPP) Compliance

    The EU's Ecodesign for Sustainable Products Regulation (ESPR) mandates Digital Product Passports for packaging, requiring QR-coded traceability of material composition, origin, and disposal instructions. MYCO's automated production via SEMA enables data logging, but a comprehensive digital traceability system is not yet implemented.

    Inability to provide DPP-compliant data could exclude MYCO from premium B2B contracts with multinational corporations subject to strict ESG reporting requirements.

  • Operations Integration

    Multi-Site Orchestration for Modular Deployment

    MYCO's 2025 roadmap includes containerized "modular turnkey solutions" deployable directly at customer sites (e.g., inside a Foxconn factory). This distributed manufacturing model requires centralized orchestration of remote production units while maintaining quality and traceability.

    Without a unified IT/OT architecture, managing distributed mini-factories will create operational silos, inconsistent data, and quality control blind spots.

  • Digital Operations

    Quality Assurance for High-Value Applications

    MYCO's FixPack serves high-precision applications like Meopta optical prisms and Camea industrial sensors, where compressive strength and ESD safety are critical. Current quality validation relies on manual inspection and post-production testing.

    Where inline quality monitoring (e.g., computer vision) could allow defective products to reach customers, eroding trust in high-margin custom molding segments.

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. Production Automation Gap

    MYCO's rapid forming technology is revolutionary but the current semi-automated SEMA machine represents first-generation automation. Scaling to 15 pads/second requires next-generation control systems with precise PLC orchestration and closed-loop feedback.

    Deploy advanced industrial automation frameworks with real-time process control, enabling consistent quality at scale while reducing labor dependency in the expanding modular factory network.

  2. Biological Process Monitoring Deficit

    Mycelium cultivation involves complex biological parameters (moisture, temperature, contamination risk) that vary across substrate batches. Current monitoring lacks integrated real-time dashboards for proactive intervention.

    Implement IoT sensor networks with advanced KPI visualization to transform biological process data into actionable insights, enabling predictive maintenance and contamination prevention.

  3. Traceability and Compliance Data Silos

    EU regulations (PPWR, ESPR, Green Claims Directive) require auditable data on material origins, carbon footprint, and disposal pathways. MYCO has LCA data but lacks an integrated platform for Digital Product Passport generation.

    Build an ontology-driven data platform that consolidates production data, LCA metrics, and batch traceability into a compliance-ready Digital Product Passport system.

  4. Distributed Manufacturing Control

    MYCO's containerized mini-factory strategy will deploy production units at customer sites globally, but there is no unified architecture for remote monitoring, orchestration, and quality assurance across geographically dispersed assets.

    Design a scalable IT/OT architecture with centralized orchestration and edge computing capabilities to manage distributed manufacturing while maintaining quality standards and real-time visibility.

  5. Quality Control Vision Gap

    High-value FixPack applications for optical and electronic components require precise quality validation. Current manual inspection cannot scale with rapid forming speeds and risks human error in critical measurements.

    Deploy computer vision systems for inline quality inspection, detecting defects, dimensional accuracy, and surface consistency in real-time at production speeds.

What we'd propose

  • Digital CDMO

    Industrial Automation & Control System Upgrade

    Design and implement next-generation PLC-based control systems to orchestrate MYCO's rapid forming production lines, enabling precise control of pressure, temperature, and timing parameters for consistent quality at 15 pads/second throughput.

    • OT/IT convergence

      Pull sensor and controller data off the line into a shared data plane in real time.

      DETAIL

    • Batch intelligence

      Golden-batch comparison and deviation detection running on the same data plane.

      DETAIL

    • Production release flow

      Closed-loop between QA, MES, and ERP so batch record review and release follow the data, not the paperwork.

      DETAIL

    • Shorter lead time from data capture to decision.
    • Records that audit on their own, not on inspection day.
    • Scale without adding the same headcount.

    We've done this before

    See how we do Digital CDMO
  • Digital Lab

    Real-Time Bioprocess Monitoring Platform

    Deploy an integrated IoT sensor network with advanced visualization dashboards to monitor biological cultivation parameters, enabling proactive contamination detection and process optimization across all production stages.

    • Unified data backbone

      Connect instruments and LIMS into a single data spine so QC and CDMO records are queryable across sites.

      DETAIL

    • Paperless workflows

      Move lab execution from paper to instrument-captured records with full audit trail.

      DETAIL

    • Continuous QC release

      Review-by-exception dashboards that flag only the records needing scientist attention.

      DETAIL

    • Shorter lead time from data capture to decision.
    • Records that audit on their own, not on inspection day.
    • Scale without adding the same headcount.

    We've done this before

    See how we do Digital Lab
  • Enterprise AI

    Digital Product Passport & Compliance Platform

    Build an ontology-driven data platform that consolidates production batch data, LCA metrics, and material traceability into an automated Digital Product Passport system compliant with EU ESPR and PPWR requirements.

    • Ontology layer

      A shared semantic model so lab, process, and quality data describe the same things the same way.

      DETAIL

    • Predictive models

      Models trained on the historical data plane that flag deviations before they become scrap.

      DETAIL

    • Decision surfaces

      Single pane of glass that surfaces model output to the right role at the right moment.

      DETAIL

    • Shorter lead time from data capture to decision.
    • Records that audit on their own, not on inspection day.
    • Scale without adding the same headcount.

    We've done this before

    See how we do Enterprise AI
  • Digital CDMO

    Distributed Manufacturing Orchestration Architecture

    Design a scalable IT/OT architecture enabling centralized monitoring and control of geographically distributed mini-factory deployments, ensuring consistent quality standards and real-time operational visibility across all production sites.

    • OT/IT convergence

      Pull sensor and controller data off the line into a shared data plane in real time.

      DETAIL

    • Batch intelligence

      Golden-batch comparison and deviation detection running on the same data plane.

      DETAIL

    • Production release flow

      Closed-loop between QA, MES, and ERP so batch record review and release follow the data, not the paperwork.

      DETAIL

    • Shorter lead time from data capture to decision.
    • Records that audit on their own, not on inspection day.
    • Scale without adding the same headcount.

    We've done this before

    See how we do Digital CDMO
  • Digital CDMO

    Inline Quality Inspection with Computer Vision

    Deploy AI-powered computer vision systems for real-time quality inspection of formed mycelium products, detecting dimensional deviations, surface defects, and structural inconsistencies at production speeds.

    • OT/IT convergence

      Pull sensor and controller data off the line into a shared data plane in real time.

      DETAIL

    • Batch intelligence

      Golden-batch comparison and deviation detection running on the same data plane.

      DETAIL

    • Production release flow

      Closed-loop between QA, MES, and ERP so batch record review and release follow the data, not the paperwork.

      DETAIL

    • Shorter lead time from data capture to decision.
    • Records that audit on their own, not on inspection day.
    • Scale without adding the same headcount.

    We've done this before

    See how we do Digital CDMO

Digital maturity: today and target

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

Source: A4BEE analysis of public sources
Process Automation 45 → 85
SEMA partnership delivered 300% capacity gain but next-gen 15 pads/sec line requires advanced PLC orchestration and closed-loop control systems.
Data Integration 35 → 80
Production data exists in silos; LCA data separate from batch records; no unified platform for Digital Product Passport generation.
Real-Time Monitoring 40 → 85
Basic temperature/pressure controls implemented via SEMA; lacks comprehensive IoT sensor network and predictive analytics for contamination prevention.
Quality Assurance 30 → 75
Manual inspection dominates; no inline vision systems for dimensional/surface verification at scale production speeds.
Compliance Readiness 50 → 90
ISO-compliant LCA completed; PPWR/ESPR Digital Product Passport infrastructure not yet deployed; audit-ready traceability gaps.
Scalability Architecture 25 → 80
Single-site operation; containerized mini-factory strategy requires distributed IT/OT architecture not yet designed.

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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 Myco, 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].