Biodock

Biodock is an AI platform that makes deep learning easy to train, run, and interpret on biological and microscopy images, dramatically accelerating R&D image analysis. Researchers upload microscopy images, label and train fully-automated deep AI models in a visual labeler (no code required), and run those models across large datasets to segment, classify, and quantify objects such as cells - producing results comparable to flow cytometry along with downloadable object-level and aggregate data. Biodock is used by academic labs and Fortune 500 biopharma and life-science organizations, and is SOC 2 Type II and ISO 27001 certified. Beyond the visual app, Biodock exposes a public REST API (beta) for uploading files to the Biodock Filesystem, submitting analysis jobs against published pipelines, tracking job progress, and downloading results and segmentation masks - so analysis can be scripted and integrated into internal tools and imaging pipelines.

Biodock publishes 4 API contracts indexed on the APIs.io network, including Analysis Jobs API, Auth API, Files API, and 1 more. Tagged areas include Company, Artificial Intelligence, Machine Learning, Image Analysis, and Microscopy.

The Biodock catalog on APIs.io includes 1 Spectral governance ruleset.

Biodock’s developer surface includes documentation, signup flow, engineering blog, support, and 19 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

49.4/100 developing ▬ flat Agent 22/100 agent aware Front door AI 5/6 prominent Heartbeat 94/100 alive saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

1 published contract 2 Agent Skills

Company Artificial Intelligence Machine Learning Image Analysis Microscopy Life Sciences Biotechnology Computer Vision Cell Analysis Research

What this lets a business do 1

Business capabilities this provider's published APIs can perform, derived from its own contracts. Browse all capabilities →

AI Model Services

AE-110

Analysis Jobs

POST /analysis-jobs

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 49.4/100 · developing

Contract Quality 9.7 / 19

Developer Ergonomics 8.8 / 15

Access Clarity 6.5 / 15

Operational Transparency 2.6 / 10

Contract Governance 1.6 / 9

Discoverability 5.5 / 8

Regulatory Posture 4.5 / 15

Create-or-Update Ergonomics 1.1 / 10

Agent readiness — 22/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 7 / 7

Rate-Limit Signaling 0 / 7

Typed Event Surface 0 / 6

Agent Skills 5 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the Health regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Create-or-Update Ergonomics applies to this provider. This API accepts writes, so it carries 10 points of the composite. It is scored from the published contracts themselves: whether a caller can create-or-update in one call, whether the write accepts a key the caller already holds, and whether the response says which branch ran. Without that, every write needs a search-and-branch in front of it, and the first time that check is skipped a duplicate record is created. Scored against the observed mean rather than raw — a provider at the catalog average is unchanged by this facet, not penalised by it.

The six quality facets above are damped to 75 points between them, because the conditional facet above carries the other 25. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 75% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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Agent readiness — checks not met, largest first (exact, from this profile):

MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0
Rate-Limit Signaling +7 pts — OpenAPI responses document X-RateLimit-* / RateLimit headers (verified), else a rate_limits artifact or RateLimits link (documented)

9 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Contract Quality scores 51.7 — up to +12.1 composite points
Access Clarity scores 43.4 — up to +11.3 composite points
Contract Governance scores 18.2 — up to +9.8 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from the provider profile at artifacts.apis.io/biodock/apis.yml: open an issue on github.com/api-evangelist/biodock to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
ONVIF Video Analytics (video surveillance, edge cameras, computer vision)	standard	17.2 (thin)	-	-

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

Standards implemented 1

Standards this provider implements or carries. De facto ones are profiled and measured by the API Commons; formal ones come from the standards directory and are linked by the provider's own tags. The evidence column says how each claim was established — not that it was made.

OpenAPI

measured — observed by APIs.io (published)

APIs 4

Individual APIs this provider publishes, each with its own machine-readable definition.

Biodock Analysis Jobs API

Submitting, tracking, and downloading analysis jobs

Biodock Auth API

API key verification

Biodock Files API

Uploading and listing Biodock Filesystem items

Biodock Pipelines API

Listing published analysis pipelines

Open Collections 4

Open, tool-agnostic API collections (OpenAPI-derived and Bruno).

Biodock Public Analysis Jobs API

OPEN COLLECTION

Biodock Public Analysis Jobs Auth API

OPEN COLLECTION

Biodock Public Analysis Jobs Files API

OPEN COLLECTION

Biodock Public Analysis Jobs Pipelines API

OPEN COLLECTION

Agent Skills 2

Packaged agent skills for driving this provider's APIs from an AI assistant.

Manage the Biodock Filesystem

AGENT SKILL

Upload images and run a Biodock analysis

AGENT SKILL

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs.

Biodock API Rules

58 rules · 56 errors 1 warnings 1 info

SPECTRAL

OpenAPI Overlays 1

Overlays applied on top of this provider's contracts. Each card says who wrote it: a document the provider publishes, or one API Evangelist derived or generated.

Biodock Public Api Overlay

4 actions · update · biodock-public-api-openapi.yml

DERIVED

Security Posture 4

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Biodock Authentication

apiKey · 1 scheme

SECURITY

Biodock Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Biodock Vulnerability Disclosure

Hackerone · contact published

SECURITY

Biodock Trust Center

SOC 2 Type II, SOC 3, ISO 27001

SECURITY

Resources

Get Started 3

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

SignUp

SignUp

Login

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

X-MCPServerCandidate

X-MCPServerCandidate

LLMsTxt

LLMsTxt

AgentSkill

AgentSkill

Design & Contract 2

Pagination, idempotency, versioning, errors, and events

Lifecycle

Lifecycle

Conformance

Conformance

Access & Security 5

Authentication, authorization, and security posture

Security

Security

Compliance

Compliance

TrustCenter

TrustCenter

VulnerabilityDisclosure

VulnerabilityDisclosure

DomainSecurity

DomainSecurity

Operate 2

Status, limits, changes, and where to get help

StatusPage

StatusPage

Support

Support

Commercial 2

Pricing, plans, and the legal terms of use

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Company 3

The organization behind the API

BlogRSS

BlogRSS

Website

Website

Blog

Blog

Other 2

Properties that don't map to a standard resource type

CapabilityMap

CapabilityMap

Overlay

Overlay

Source (apis.yml)

aid: biodock
name: Biodock
description: Biodock is an AI platform that makes deep learning easy to train, run, and interpret on biological and microscopy
  images, dramatically accelerating R&D image analysis. Researchers upload microscopy images, label and train fully-automated
  deep AI models in a visual labeler (no code required), and run those models across large datasets to segment, classify,
  and quantify objects such as cells - producing results comparable to flow cytometry along with downloadable object-level
  and aggregate data. Biodock is used by academic labs and Fortune 500 biopharma and life-science organizations, and is SOC
  2 Type II and ISO 27001 certified. Beyond the visual app, Biodock exposes a public REST API (beta) for uploading files to
  the Biodock Filesystem, submitting analysis jobs against published pipelines, tracking job progress, and downloading results
  and segmentation masks - so analysis can be scripted and integrated into internal tools and imaging pipelines.
url: https://raw.githubusercontent.com/api-evangelist/biodock/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- a16z
x-tier: stub
x-tier-reason: portfolio-lead
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: true
  label: Hosted service · you call their endpoint
  confidence: high
  source:
  - openapi
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - authentication
  - security
  generated: '2026-11-06'
  method: derived
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-10-06'
image: https://cdn.prod.website-files.com/63213d26df394911486f698e/637bb41c1cac3a4ded2e9f23_SEOImage.jpg
x-docs-platform: gitbook
x-docs-platform-confidence: high
x-docs-platform-checked: 2026-09-20
tags:
- Company
- Artificial Intelligence
- Machine Learning
- Image Analysis
- Microscopy
- Life Sciences
- Biotechnology
- Computer Vision
- Cell Analysis
- Research
tags_raw:
- Company
- Artificial Intelligence
- Machine Learning
- Image Analysis
- Microscopy
- Life Sciences
- Biotechnology
- Computer Vision
- Cell Analysis
- Research
- Machine-Learning
- Computer-Vision
apis:
- aid: biodock:biodock-analysis-jobs-api
  name: Biodock Analysis Jobs API
  description: Submitting, tracking, and downloading analysis jobs
  humanURL: https://docs.biodock.ai/public-api/overview
  baseURL: https://app.biodock.ai/api/external
  tags:
  - Analysis Jobs
  properties:
  - type: OpenAPI
    url: openapi/biodock-analysis-jobs-api-openapi.yml
  - type: Authentication
    url: authentication/biodock-authentication.yml
  - type: Conventions
    url: conventions/biodock-conventions.yml
  - type: DataModel
    url: data-model/biodock-data-model.yml
  - type: Documentation
    url: https://docs.biodock.ai/public-api/overview
  - type: APIReference
    url: https://docs.biodock.ai/public-api/resources
  - type: GettingStarted
    url: https://docs.biodock.ai/public-api/authentication
  - type: Examples
    url: https://docs.biodock.ai/public-api/examples
- aid: biodock:biodock-auth-api
  name: Biodock Auth API
  description: API key verification
  humanURL: https://docs.biodock.ai/public-api/overview
  baseURL: https://app.biodock.ai/api/external
  tags:
  - Authentication
  tags_raw:
  - Auth
  properties:
  - type: OpenAPI
    url: openapi/biodock-auth-api-openapi.yml
  - type: Authentication
    url: authentication/biodock-authentication.yml
  - type: Conventions
    url: conventions/biodock-conventions.yml
  - type: DataModel
    url: data-model/biodock-data-model.yml
  - type: Documentation
    url: https://docs.biodock.ai/public-api/overview
  - type: APIReference
    url: https://docs.biodock.ai/public-api/resources
  - type: GettingStarted
    url: https://docs.biodock.ai/public-api/authentication
  - type: Examples
    url: https://docs.biodock.ai/public-api/examples
- aid: biodock:biodock-files-api
  name: Biodock Files API
  description: Uploading and listing Biodock Filesystem items
  humanURL: https://docs.biodock.ai/public-api/overview
  baseURL: https://app.biodock.ai/api/external
  tags:
  - File
  tags_raw:
  - Files
  properties:
  - type: OpenAPI
    url: openapi/biodock-files-api-openapi.yml
  - type: Authentication
    url: authentication/biodock-authentication.yml
  - type: Conventions
    url: conventions/biodock-conventions.yml
  - type: DataModel
    url: data-model/biodock-data-model.yml
  - type: Documentation
    url: https://docs.biodock.ai/public-api/overview
  - type: APIReference
    url: https://docs.biodock.ai/public-api/resources
  - type: GettingStarted
    url: https://docs.biodock.ai/public-api/authentication
  - type: Examples
    url: https://docs.biodock.ai/public-api/examples
- aid: biodock:biodock-pipelines-api
  name: Biodock Pipelines API
  description: Listing published analysis pipelines
  humanURL: https://docs.biodock.ai/public-api/overview
  baseURL: https://app.biodock.ai/api/external
  tags:
  - Pipelines
  properties:
  - type: OpenAPI
    url: openapi/biodock-pipelines-api-openapi.yml
  - type: Authentication
    url: authentication/biodock-authentication.yml
  - type: Conventions
    url: conventions/biodock-conventions.yml
  - type: DataModel
    url: data-model/biodock-data-model.yml
  - type: Documentation
    url: https://docs.biodock.ai/public-api/overview
  - type: APIReference
    url: https://docs.biodock.ai/public-api/resources
  - type: GettingStarted
    url: https://docs.biodock.ai/public-api/authentication
  - type: Examples
    url: https://docs.biodock.ai/public-api/examples
common:
- type: CapabilityMap
  url: capabilities/biodock-capability-edges.yml
  name: Biodock Business Capability Map
- url: https://blog.biodock.ai/rss/
  type: BlogRSS
- type: Website
  url: https://www.biodock.ai/
- type: X-MCPServerCandidate
  url: mcp/biodock-mcp.yml
  note: 'Renamed from MCPServer 2026-09-03 (roadmap#247): the manifest self-describes as status: candidate — a tool list derived
    from the published API contracts, not an existing server. The scorer already read the manifest and reported mcp_server
    correctly; the MCPServer type was crediting the artifact-type surfaces with a server that does not exist.'
- type: Overlay
  url: overlays/biodock-public-api-overlay.yaml
- type: DeveloperPortal
  url: https://docs.biodock.ai/
- type: Documentation
  url: https://docs.biodock.ai/
- type: SignUp
  url: https://app.biodock.ai/signup
- type: Login
  url: https://app.biodock.ai/
- type: Blog
  url: https://blog.biodock.ai/
- type: StatusPage
  url: https://biodock.statuspage.io/
- type: Support
  url: https://www.biodock.ai/contact
- type: TermsOfService
  url: https://www.biodock.ai/termsprivacy
- type: PrivacyPolicy
  url: https://www.biodock.ai/termsprivacy
- type: Security
  url: https://www.biodock.ai/security
- type: Compliance
  url: https://www.biodock.ai/security
- type: TrustCenter
  url: https://www.biodock.ai/security
- type: LLMsTxt
  url: llms/biodock-llms.txt
- type: Lifecycle
  url: lifecycle/biodock-lifecycle.yml
- type: Conformance
  url: conformance/biodock-conformance.yml
- type: VulnerabilityDisclosure
  url: security/biodock-vulnerability-disclosure.yml
- type: DomainSecurity
  url: security/biodock-domain-security.yml
- type: AgentSkill
  url: skills/_index.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

Biodock API — frequently asked questions

Does Biodock have an API?

Yes. APIs.io lists 4 APIs from Biodock, including Biodock Analysis Jobs API, Biodock Auth API and Biodock Files API, and 1 more.

Is there an OpenAPI specification for the Biodock API?

Yes. APIs.io indexes 4 OpenAPI specifications for Biodock, each linked for download from this page.

How do I authenticate with the Biodock API?

Biodock uses bearer-token authentication (apiKey · 1 scheme). The details are profiled on APIs.io as Biodock Authentication.

Is the Biodock API ready for AI agents?

Biodock has a Kin Score of 49.4 out of 100 (developing) and an Agent Readiness score of 22.1 (agent-aware), scored by API Evangelist on 2026-11-06.

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