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Open Beta — v1.0.0

Open Transparency

Security & Privacy Overview · Last Updated: 2 September 2026

We believe the people who store their health data with us deserve to know exactly what we do with it, how we protect it, and where we currently fall short. Methos is now in open beta — this page describes the product as it actually runs today, including the parts that are still missing, and is updated with every release.

Release status: Open Beta. The service is publicly available, free of charge, with a limited feature set. The stable release is the milestone at which subscriptions (paid features) are introduced; it may bring updated Terms of Service, Privacy Policy, and Data Processing Consent, which you will confirm again. Commitments on this page phrased as "before the stable release" refer to that milestone.

Beta data migration: data stored during the Open Beta will be migrated to the stable release.

1. Mission & Purpose

Methos is a personal data vault and MCP server. It is not a health application, a medical application, or a diagnostic tool. Its sole purpose is to provide a secure, encrypted, self-sovereign store for your personal data — including health and biometric data — and to expose that data back to you through an open, standardised protocol (Model Context Protocol), so you can query and use your own data within any AI agent or tool of your choosing.

Agent access is authorised with standard OAuth 2.1 flows — authorization-code with PKCE (your agent registers itself and you approve its access on a Methos consent screen) and client-credentials for server-to-server API keys. Access is scoped per data category and revocable at any time (see section 3).

Methos itself performs no health analysis, gives no health advice, and makes no clinical assessments. All interpretation of data is the responsibility of you and the external tools or agents you choose to connect.

What Methos does

  • ✓ Accepts your uploaded data (lab reports, DNA files, wearable exports, manual entries) and stores it in encrypted form
  • ✓ Normalises and anonymises applicable documents, then vectorises them for semantic retrieval — content stays in encrypted storage, the vector index holds no readable text
  • ✓ Exposes your data via MCP tools you can connect to any AI agent
  • ✓ Provides curated, non-personal common knowledge (genomic reference data, published studies) as separate read-only MCP tools
  • ✓ Will integrate with Apple Health, Oura, and similar platforms (planned — not yet available)

What Methos never does

  • ✗ Provide health diagnoses, clinical assessments, or medical recommendations
  • ✗ Analyse or interpret your health status
  • ✗ Make automated decisions with legal, medical, or clinical consequence
  • ✗ Act as a medical device under any regulatory framework
  • ✗ Sell or share your health data with any third party
  • ✗ Use health data for marketing, advertising, or profiling

2. Data Handling & Encryption

What we collect

Health and biometric data is a special category under GDPR Art. 9 and is treated accordingly. We process only what you explicitly provide or authorise:

  • Health & biometric data (lab results, DNA files, HRV, sleep, heart rate)
  • Wearable & sensor data (Apple Health, Oura, Whoop — integrations not yet available)
  • User-authored content (notes, goals, supplement logs, training plans)
  • Identity & authentication data (email, passkey credentials, anonymised internal user ID)
  • Technical metadata (access logs, consent records, processing activity logs)

Within the service, each ingested item is additionally assigned a fine-grained data category (e.g. blood samples, genetic data, lifestyle, medical history, wearable data, body composition, nutrition, mental health, medications, supplements, allergies, personal care, reproductive health, vaccinations, family history, sleep, stress, plus an admin-reviewed "other" bucket). This classification is technical — it drives the ingestion pipeline, MCP access-key scoping, and audit logging — and does not define separate consent scopes (see "Consent model" below). When you upload data of a kind the category set does not yet cover, the item is held under an AI-proposed label pending administrative review: the administrator sees only the proposed category label, never the item's content, and either maps the item to an existing category or accepts it under the proposed label.

Legal basis

  • → Explicit consent (Art. 6(1)(a) and Art. 9(2)(a)) — for all health and biometric data. Consent is freely given, specific, informed, and revocable at any time — given once at account activation by confirming the Data Processing Consent as a whole.
  • → Performance of contract (Art. 6(1)(b)) — for data strictly necessary to provide the service (authentication, account management).
  • → Legal obligation (Art. 6(1)(c)) — for records we must keep by law (e.g. accounting records).
  • → Legitimate interest (Art. 6(1)(f)) — for records kept to protect rights and legitimate interests (logs, complaint records).

Only data you explicitly upload or authorise for import is stored. It is used solely to provide the service to you. No cross-user profiling is performed on individual health data; anonymised aggregate metrics may be derived for internal service quality monitoring.

Encryption model

  • → In transit: TLS 1.3 or higher on all communications — including the channel between your client and our backend.
  • → Server-side envelope encryption: Your data is sent to the backend over TLS — the client does not perform the encryption. On the backend, a dedicated crypto engine encrypts each item under its own data-encryption key (DEK), then wraps that DEK with a key-encryption key (KEK) held in HashiCorp Vault (transit secrets engine). Only the wrapped DEK is stored alongside the ciphertext; the KEK never leaves Vault, and the platform never holds the plaintext key material. Plaintext exists only transiently in backend memory during processing.
  • → Encrypted Envelopes throughout: No plaintext personal data is written to event streams, databases, or object storage — they carry data exclusively as encrypted envelopes. Normalised content is split into deterministic chunks, each encrypted individually under its own DEK.
  • → The vector index is the honest exception: the embedding vectors in the vector database are not encrypted — semantic search wouldn't work otherwise. But the index holds only the vector plus three identifiers (a chunk reference, profile id, and data category): no text, no document content, no encryption material. Vectors are computed exclusively from normalised, PII-stripped content you approved, and the index is fully derived — it can be wiped and rebuilt from the encrypted chunks at any time, and is useless without them.
  • → One root key per user: Each user has their own root key, created at account activation and held in HashiCorp Vault as a non-exportable Transit key. Every operation that touches it — wrapping and unwrapping data keys, key derivation, HMAC — is performed by Vault's Transit API inside Vault itself: our services send data in and get results back, never the key. So the root key doesn't just never leave Vault — it can't. Purpose-specific keys (data encryption, metrics pseudonymisation) are derived from it inside Vault, so compromising one derived key never exposes the others. Deleting the root key makes all of that user's encrypted data permanently unreadable (crypto-shredding) — this is how account erasure is implemented.
  • → Biometric metrics are stored under a pseudonymised ID (an HMAC derived from the user's root key), decoupled from your account identity. Rotation of this pseudonymised ID is planned to further limit longitudinal re-identification.

Honestly: this is not end-to-end encryption. Methos manages the keys — you don't hold them. That means the platform can technically decrypt your data. This is a deliberate design decision: server-side processing (vectorisation of your documents, retrieval by your MCP agent) has to work without you being online, and none of it would be possible with keys only you hold. In the current phase, Vault admin access — and with it the technical ability to decrypt — is held by a single person, the founder (see section 6). We would rather tell you this plainly than imply a zero-knowledge model we don't have.

The guardrails: Vault is the sole authority for key material, accessed under least-privilege policies. User identity exists only as a signed request context created once at the trust boundary — it is never taken from a request's payload, so a request can never act as another user. Every cryptographic operation and every data access is written to an audit log.

Data locality & hosting

All user data is stored and processed on a self-hosted Kubernetes cluster at the company's premises in Brno, Czech Republic — within the European Union. No data is transferred outside the EU in the normal course of operations. AI inference runs in EU Azure regions (see section 4). The cluster currently runs on two nodes, with a third prepared but kept powered off — partial hardware redundancy, not full high availability. This arrangement is temporary by design: the target setup (multi-node or managed EU hosting) will be decided based on how the service grows during the Open Beta, and any future hosting provider will be contractually bound to EU data locality.

Sub-processors

No personal data is shared with third parties for commercial or analytical purposes. The following processors receive data under a Data Processing Agreement — this is the complete list (infrastructure is self-hosted, so no hosting provider is involved):

ProcessorRoleData received
Microsoft Azure AI FoundryAll AI model inference (categorisation, normalisation/anonymisation, embedding, ancillary non-health uses). EU regions only (Sweden); no training on customer data.Document content during ingestion; normalised, de-identified text only for embedding
PaddlePayment processing and subscription billing as Merchant of Record (card data, VAT, invoicing). Keeps Methos out of PCI-DSS cardholder-data scope.Billing details only: name, email, payment/tax information. No health, biometric, or vault data.
SparkPostTransactional email delivery (login magic links, service notifications). EU sending region only.Email address, email content, and delivery metadata only. No health, biometric, or vault data.

Data retention

Deleting your account always deletes all of your data. Audit logs (processing records, consent records, access logs) are retained independently, for the period required by law. A tiered retention model for long-lived data (daily resolution for 3 months, monthly aggregates to 1 year, yearly aggregates beyond) is designed but not yet implemented, and the handling of stored data when a paid feature is cancelled — as distinct from closing the account — will be defined before paid features are introduced.

Your GDPR rights

Access (Art. 15)

Implemented

Erasure (Art. 17)

Implemented — delete account

Consent withdrawal

Implemented — delete account

Portability (Art. 20)

Planned — export in scope for MVP

Rectification (Art. 16)

Planned

Restriction (Art. 18)

Planned

Objection (Art. 21)

Applicable

Consent model

  • → Consent is obtained once, at account activation: you confirm the Terms of Service, Privacy Policy, and Data Processing Consent together, each as a whole. There are no per-category consent toggles.
  • → Data categories are a technical classification, not consent scopes. Adding or changing a category does not require a new agreement; the agreements change only when the processing itself materially changes (e.g. a new sub-processor or the introduction of paid features), with advance notice as described in the Terms of Service and Privacy Policy.
  • → Every consent event and every access to personal data is written to an immutable audit trail (timestamp, data category where applicable, stated purpose, user identifier).

3. Authentication & Agent Access

Two distinct credential types exist, for two distinct access paths: you signing in, and your AI agent reading your data without a human session.

You: no passwords, ever

  • → Magic link is the default sign-in for every account: a single-use, short-lived token sent to your registered email, invalidated the moment it is used. No password is stored, transmitted, or required — and there is no password reset flow to attack.
  • → Passkeys (FIDO2/WebAuthn) are supported and encouraged. Once you register one, it becomes your primary login and the magic-link fallback is no longer offered by default. Passkey credentials are stored in the Methos account database and never leave our trust boundary; all WebAuthn verification is performed in-house, with no third-party passkey service.
  • → An anonymised internal ID is generated at account activation and used in processing logs, decoupling audit records from your direct identifiers.

Your agent: standard OAuth, scoped, instantly revocable

  • → Authorization Code + PKCE for standard MCP clients (e.g. Claude, Open WebUI). The client discovers Methos via .well-known metadata and registers itself dynamically — which grants nothing on its own. Access is bound on a Methos consent screen where you pick exactly one profile and the data-category scopes to grant (nothing is preselected; an empty grant is refused). Only PKCE S256 is accepted; your browser session is never shared with the agent.
  • → Client credentials for server-to-server use: you create a profile-scoped API key with a name, allowed scopes, and expiry. The secret is shown exactly once and stored only as a Vault Transit HMAC — never in cleartext.
  • → Tokens carry no authority. Access tokens (1 h) contain no profile or scope claims. On every MCP call, the stored key or client is looked up server-side — so revoking a key, editing its scopes, or its expiry takes effect immediately, regardless of any token's remaining lifetime. A token can never grant more than the scopes you configured.
  • → You manage API keys and authorised clients (list, edit scopes, revoke) from the account portal.

Security events logged: successful and failed authentication attempts, license validation failures, authorisation failures, data access, modification, and deletion operations, root-key operations, and every encryption and decryption event. Each entry records the actor (user, AI agent, or system), data category, timestamp, and operation type.

Responsible disclosure: there is no bug bounty programme yet. If you discover a vulnerability, please email [email protected]. Reports are reviewed manually; there is no guaranteed response time at this stage, and responsible disclosers are acknowledged publicly with their consent.

4. AI & Algorithmic Transparency

Methos is not an AI health application. Inside the data pipeline, AI is used for exactly three technical functions, and nothing else. None of them interprets health data, gives advice, or makes decisions with clinical, legal, or medical consequence.

FunctionDescriptionUsed
Data categorisationWhen you submit data, an AI model reads the content and determines a category (e.g. blood test, DNA file, training plan, wearable export, lifestyle note). The category gates the rest of the pipeline. Content classified as suspicious is quarantined and processed no further. For a normalisable category, the original content is encrypted and persisted before normalisation proceeds.Yes
Normalisation & anonymisationFor applicable document categories, an AI model transforms the raw document into normalised, structured text and strips direct identifiers (PII). You review and confirm or correct this normalised content before anything is embedded — only normalised, de-identified content you have approved proceeds to the embedding step.Yes
Embedding / vectorisationOnce confirmed, the normalised text is split into deterministic chunks and each chunk is converted into a vector representation stored in your personal vector index (which holds vectors and isolation identifiers only — no readable text; see section 2), enabling semantic search across your own data. The text itself stays envelope-encrypted in the database.Yes
Health interpretationAssessing whether a metric or result is normal, good, or badNever
Medical recommendationsGenerating clinical guidance, diagnoses, or treatment suggestionsNever
Automated health decisionsAny automated decision with clinical, legal, or medical consequenceNever

The MCP server exposes data retrieval tools only. Retrieval is vector similarity search over your own vault — it returns stored records, not AI-generated answers. All interpretation, analysis, and decision-making is performed by you or by external AI agents you have independently chosen to connect. Methos has no visibility into or control over what those agents do with the data they retrieve.

Human-in-the-loop at ingestion

  1. 1.You submit data (file upload or manual text entry). The content is transmitted to the backend over TLS-secured gRPC.
  2. 2.An AI model reads the content and determines a data category. Content classified as suspicious is quarantined and processed no further.
  3. 3.For a category that is normalised, the original content is encrypted and persisted first. An AI model then produces the normalised, anonymised form (PII stripped).
  4. 4.You are shown the normalised content and must explicitly confirm it, correct it, or cancel. Nothing is chunked or embedded before this confirmation.
  5. 5.Only after you confirm is the normalised content encrypted, split into chunks, and stored; each chunk is then vectorised and the entry is marked searchable.

The AI output at steps 2–3 is a categorisation and normalisation proposal only. It carries no health interpretation and has no effect on the retrievable representation until you review and approve it at step 4.

DNA / genetic data takes a different path. It does not go through this AI pipeline at all — it is neither normalised nor embedded into the vector store, but stored separately and exposed through dedicated MCP tool(s). DNA ingestion is currently disabled; when enabled, the initial scope is limited to short consumer reports (e.g. 23andMe, Ancestry), with full sequencing reports (VCF) deferred to a later phase.

Ancillary AI use (no health data). Two further uses exist that never touch stored user data: a lightweight model normalises a free-text interface-language preference to an ISO code (the only input is the short string you typed), and an in-product help assistant serves short, page-specific help text from a fixed server-side knowledge base, translated into your language. The help assistant is not an autonomous agent — it has no conversation memory, performs no reasoning over personal data, executes no actions on your behalf, and has no access to the database or any user data.

Models used

FunctionModelAccess
CategorisationClaude HaikuAzure AI Foundry
Normalisation and anonymisationClaude SonnetAzure AI Foundry
Embedding / vectorisationtext-embedding-3-largeAzure AI Foundry
Language normalisation (no health data)Claude HaikuAzure AI Foundry
Help translation (no health data)Claude HaikuAzure AI Foundry

Model versions are pinned at deployment and reviewed periodically. No model receives personal data beyond the specific content required for the operation in progress.

Where AI runs: All AI inference is performed through Microsoft Azure AI Foundry, under Microsoft's Data Processing Agreement (incorporating EU Standard Contractual Clauses). Models are deployed only in EU Azure regions (Sweden), so inference stays within the European Union. Categorisation and normalisation models receive the document being ingested for the duration of that operation; only normalised, de-identified content is sent to the embedding model.

No training on your data: Your content is never used to train, fine-tune, or improve any AI model — neither by us nor by the model provider under the Azure AI Foundry Data Processing Agreement.

Transparency & human oversight: You are always informed when a feature is powered by AI and when your data is being AI-processed. AI output is assistive only — you must review and explicitly approve the normalised result before anything is embedded, so a human always stays in control.

5. Regulatory Position

Methos is a data storage and retrieval infrastructure. It does not have a medical purpose and does not fall within the scope of medical software regulations — it performs no diagnostic, monitoring, or clinical function. Health data stored in Methos is treated identically to any other user document; the system has no domain-specific knowledge of its medical meaning.

FrameworkStatus
GDPR (EU 2016/679)Fully applicable — primary data protection regulation
EU AI ActApplicable — system assessed as minimal-risk category
EHDS — European Health Data Space (EU 2025/327)Not currently applicable — Methos is not an EHR system, claims no EHR interoperability (so the voluntary wellness-app label/registration regime does not apply), and is excluded as a microenterprise from secondary-use data-holder obligations. Re-assessed if any of those change
Medical software / MDR (EU, US)Not applicable — no medical purpose, no diagnostic, monitoring, or clinical function
CCPA (California)Applicable to California users; compliance not yet assessed — legal review planned
HIPAA (USA)Not currently applicable — no clinical or covered entity relationships

EU AI Act assessment: The AI functionality in Methos (document categorisation, normalisation, and embedding) falls in the minimal-risk category. It performs no high-risk function as defined in Annex III of the Act. There is no AI-based decision-making with impact on individuals' health, safety, or fundamental rights.

Our role: Methos is a deployer of AI, not a provider of the underlying models. We use general-purpose models exclusively through Microsoft Azure AI Foundry, so model-provider obligations under the Act rest with the upstream provider, governed by Microsoft's Data Processing Agreement.

AI audit logging: Every AI operation is recorded in the same GDPR audit-log pipeline, capturing the operation type, model identifier, prompt version, input type (text or file) and size, output size, duration, retry count, success/failure status, timestamp, and a pseudonymised subject reference. Audit logs never contain raw user data or prompt content. Logs are retained for auditability and are not used for model training or profiling.

Legal documents: Stable versions of the Terms of Service, Privacy Policy, and Data Processing Consent (versioned by their "Last updated" date) have been finalised following legal review and are published alongside this report; they are linked from the product interface. The Methos codebase is proprietary and not open source.

6. What We Haven't Done Yet

Honest open-beta status. This list shrinks with each release.

  • ○Wearable integrations: Apple Health, Oura, and similar — planned, not yet implemented
  • ○DNA / genetic data: Ingestion currently disabled. Enabling it is a near-term priority; first scope is short consumer reports (23andMe, Ancestry), stored separately and exposed via dedicated MCP tools; full sequencing (VCF) deferred
  • ○Payments & subscription tiers: Paddle selected as payment provider (Merchant of Record); tiers and pricing not yet defined. The Open Beta is free of charge; subscriptions arrive with the stable release
  • ○Data retention: Tiered resolution (daily/monthly/yearly) designed but not implemented; long-term policy under review; handling on paid-feature cancellation to be defined before paid features launch. Account deletion always deletes all data
  • ○User rights flows: Erasure and consent withdrawal available via account deletion; portability (export), rectification, and restriction flows planned for MVP
  • ○Infrastructure redundancy: Two-node self-hosted cluster with a third node prepared but powered off — partial redundancy, not full high availability. Full redundancy or managed EU hosting planned before the stable release
  • ○Single-person infrastructure access: All infrastructure secrets and Vault admin access are currently held by one founder — a single point of trust; multi-person access control and a formal key ceremony are planned before the stable release
  • ○Pseudonymised metrics ID rotation: Not yet implemented — planned to reduce longitudinal re-identification risk
  • ○Third-party pen testing: Not yet conducted; planned before the stable release. Internal security reviews are ad-hoc — a regular cadence is planned
  • ○Formal disclosure policy & bug bounty: Voluntary via email for now — structured policy planned; bug bounty considered when budget permits
  • ○CCPA compliance: Not yet assessed — legal review planned
  • ○Governance: Founding team only; no external board or oversight body. A formal structure will be established as the project scales

Contact

Questions, concerns, or responsible disclosures: [email protected]

Operated by Methos BiOS s.r.o. (IČO 24921424), Černého 834/32, Bystrc, 635 00 Brno, Czech Republic (European Union). Registered with the Regional Court in Brno, file ref. C 151197.