# Mould Detect > AI-powered mould detection for Australian homes: point a phone camera at a suspect wall and get a plain-language risk read in sixty seconds, backed by a live weather and humidity data platform. Mould Detect is built agent first: the same data is available to AI agents through Mycelium, an MCP server (https://mcp.moulddetect.ai/mcp) and the Mycelium CLI. Full text of every page in Markdown: https://moulddetect.ai/llms-full.txt ## Docs - [AI Vision](https://moulddetect.ai/ai-vision/): How the AI mould-identification model works — a binary detector plus a genus classifier, trained on lab-verified specimens, with a 29-term glossary of the vision and mycology terms involved. - [Agents and MCP](https://moulddetect.ai/agents/): Mycelium Network, the Mould Detect MCP server (mcp.moulddetect.ai) and the Mycelium CLI terminal agent, giving AI assistants eight read-only tools for mould growth index, weather, flood, air quality and photo checks. Machine-readable summary: https://mycelium.moulddetect.ai/llms.txt - [Why Mould Detect](https://moulddetect.ai/why-mould-detect/): Live Australia-wide mould-growth risk map plus the case for early detection, drawing on national damp and mould prevalence data. - [FAQ](https://moulddetect.ai/faq/): Twenty direct answers on mould and health, identification, and natural treatment and remediation, for homeowners, renters, landlords and specialists. - [About](https://moulddetect.ai/about/): Who Mould Detect is — a cross-disciplinary team of environmental scientists, remedial builders and technology founders, and the company's commitments. ## Guides (Mould Edu) - [Know what you are looking at](https://moulddetect.ai/learn/#the-species): Identification guide to the five indoor mould species that matter most (Stachybotrys chartarum, Aspergillus, Penicillium, Cladosporium, Alternaria), their appearance and health risk. - [Clean it safely, or know when not to](https://moulddetect.ai/learn/#safe-cleaning): When a mould patch is DIY-cleanable versus when it needs a professional, and how to clean without spreading spores or harming yourself. - [Take away the moisture, take away the mould](https://moulddetect.ai/learn/#prevention): Root-cause prevention — humidity and ventilation practices that stop mould recurring after cleaning. - [Effective without the harsh fumes](https://moulddetect.ai/learn/#natural-solutions): Natural, non-toxic treatment options for mould and their limits compared with chemical products. ## Commercial - [Pricing](https://moulddetect.ai/pricing/): Mould Detect's tiers — a Free tier that stays free, plus Essential, Business, Professional and Enterprise plans for specialists needing more scans, more properties and defensible reporting. Single source of tier truth. - [For Specialists](https://moulddetect.ai/for-specialists/): Product page for building inspectors, remediators, builders, plumbers, cleaners, environmental health experts, occupational hygienists and laboratories — sixty-second scans, white-label reports, insurer-ready data. - [Investors](https://moulddetect.ai/investors/): The market, the lab-verified data moat behind AI mould detection, the subscription and data model, and how to request the investor deck. ## Audiences - [For Homeowners and Renters](https://moulddetect.ai/homes/): A plain-language mould risk read from one photo in under 60 seconds, compared with 7 to 14 days for a laboratory test; decision support that points to lab testing when certainty is needed, never a replacement for it. - [For Insurers](https://moulddetect.ai/insurers/): Mould as a claims-exposure risk (the Texas claims precedent), Awaab's Law (what it requires of social landlords in England, its timeframes, its planned extension to private rentals, Scotland's equivalent for social and private landlords, and what it could mean for insurers), sick building syndrome, and how independent environmental data, IoT sensing and the Mould Atlas risk engine could support prevention and parametric cover. No insurer contract exists today. - [For Partners](https://moulddetect.ai/partners/): Current partners and their status (CDES, Cloud Assembly, AWS, Spotless Interior Cleaning, Riteflo, ACRA, Nature's Defence, Brock University), and for contract cleaners, plumbers, shower fitters, bathroom installers, building and mould inspectors, occupational hygienists and laboratories: the weather and environmental data in the app, capture images and environmental data, and add Mould Detect's mould detection, environmental, weather and AI agent APIs to your own products. - [For Developers](https://moulddetect.ai/developers/): The data API at data.moulddetect.ai (mould growth index, daily forecast, current conditions, ERA5-Land history, GloFAS flood, CAMS air quality, site and hazard layers), a real request example, and links to the full reference at https://environment.moulddetect.ai/docs/. - [For IoT and Embedded Devices](https://moulddetect.ai/iot/): The prototype ESP8266 sensor board posting into the environmental data lake on a sensor-agnostic schema, build phases 1 to 4, and the sensing diffuser planned as a 2027 prototype. ## Legal - [Terms of Use](https://moulddetect.ai/terms/): How Mould Detect may be used during early access — acceptable use, content, liability and governing law. - [Privacy Policy](https://moulddetect.ai/privacy/): What MouldDetect Technologies Pty Ltd collects across the website, data APIs, Mycelium Network and iOS app, retention periods, overseas disclosure, access and complaints, and the health disclaimer (updated 31 October 2026). ## Key Facts - Product: an app that scans a photo of a suspect wall and returns a plain-language mould-risk read, in Australia. - Markets: launching in Australia to prove the approach and the technology; the United Kingdom is the planned next market (where Awaab's Law sets repair deadlines), then Canada and the US at Series A. - Platform loop: four steps on one platform, Prevent · Protect · Detect · Correct. "Correct" means correcting the conditions and the growth, through laboratory testing and remediation partners; every outcome returns to one data lake. - Data platform: a proprietary weather, humidity-history and flood-severity API (the "Data Moat") powering live mould-risk, humidity and ventilation panels shown on the site. - AI model: a two-instrument approach — binary mould/no-mould detection plus genus classification against lab-verified specimens. - Audiences served: homeowners and renters, specialists and professionals (building inspectors, remediators, plumbers, cleaners, environmental health experts), insurers, investors, partners (including occupational hygienists and laboratories), developers, AI agents, and IoT and embedded device builders. Each has its own page, linked above. - Awards: The Ventures Australia 2026 Finalist; FRWRD Special Prize "For Building a Future that Improves Lives" (Sydney, 22 October 2026). - Headquarters: Sydney, Australia (Mould Detect Technologies Pty Ltd). ## For AI agents - [Mycelium developer portal](https://mycelium.moulddetect.ai/): free beta keys, setup for Claude Code, Claude Desktop, Codex, Cursor and any MCP client. - [Mycelium docs and tools reference](https://mycelium.moulddetect.ai/docs/): the eight read-only tools, the result envelope and limits. - [Mycelium llms-full.txt](https://mycelium.moulddetect.ai/llms-full.txt): the developer docs in Markdown. - Mycelium CLI: `curl -fsSL https://mycelium.moulddetect.ai/install.sh | sh` (macOS, Linux; Windows download on the portal). ## Contact - Website: https://moulddetect.ai - Investor enquiries: the form at https://moulddetect.ai/investors/#investor-enquiry (financial projections, unit economics and seed round details are shared directly with investors, not published) - General and privacy contact details: see https://moulddetect.ai/terms/ and https://moulddetect.ai/privacy/