Model ML

Model ML is an AI-native platform for financial services that embeds an agentic "finance agent" into the tools professionals already use — Excel, PowerPoint, Outlook, its own app, and a firm's internal systems. It automates deliverables through Workflows, runs compound-intelligence analysis via Grids, performs document review and risk assessment, captures information with a Notetaker, and answers questions through Chat and agentic dashboards backed by real-time data connections. It targets investment banking, consulting, private equity and credit, and asset and wealth management. Model ML is a fintech company backed by QED Investors. The company publishes a trust center and a security program (ISO/IEC 27001, SOC 2 Type II, GDPR) but does not currently expose a public developer API, SDK, or API documentation surface.

Model ML is profiled on the APIs.io network. Tagged areas include Company, Fintech, Artificial Intelligence, Financial Services, and AI Agents.

Model ML’s developer surface includes engineering blog, support, and 7 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

14.4/100 emerging ▬ flat Agent 12/100 agent aware Front door AI 5/6 prominent Heartbeat 100/100 alive saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

0 APIs 1 MCP Servers

Company Fintech Artificial Intelligence Financial Services AI Agents Investment Banking Enterprise Document Automation

Kin Score

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

Composite quality — 14.4/100 · emerging

Contract Quality 0.0 / 21

Developer Ergonomics 1.2 / 17

Access Clarity 6.3 / 17

Operational Transparency 1.2 / 11

Contract Governance 0.0 / 10

Discoverability 4.4 / 9

Regulatory Posture 2.1 / 15

Agent readiness — 12/100 · agent aware

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 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 5 / 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 Banking & Open Finance 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 could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% 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):

Machine-Readable Contract +18 pts — api_specs includes an OpenAPI document
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
Machine-Readable Auth +10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey)
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

11 more unmet checks in the Agent Readiness table above.

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

Contract Quality scores 0.0 — up to +25.0 composite points
Developer Ergonomics scores 7.1 — up to +18.6 composite points
Access Clarity scores 36.8 — up to +12.6 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/model-ml/apis.yml: open an issue on github.com/api-evangelist/model-ml 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
Zoom App Marketplace and Partner Ecosystem (builders and partners on Zoom)	builds-on	26.8 (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 2

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.

Model Context Protocol (MCP)

measured — observed by APIs.io (verified)

OAuth 2.0 Protected Resource Metadata

measured — observed by APIs.io (verified)

MCP Servers 1

Model Context Protocol servers that expose these APIs to AI agents.

Model ML MCP Server

Remote MCP server at mcp.modelml.com over HTTP.

MCP SERVER

Security Posture 2

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

Model Ml Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Model Ml Trust Center

ISO/IEC 27001, SOC 2 Type II, GDPR

SECURITY

Resources

Access & Security 4

Authentication, authorization, and security posture

Security

TrustCenter

Compliance

DomainSecurity

Operate 1

Status, limits, changes, and where to get help

Support

Support

Commercial 2

Pricing, plans, and the legal terms of use

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: model-ml
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - security
  generated: '2026-11-06'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/model-ml.png
name: Model ML
description: Model ML is an AI-native platform for financial services that embeds an agentic "finance agent" into the tools
  professionals already use — Excel, PowerPoint, Outlook, its own app, and a firm's internal systems. It automates deliverables
  through Workflows, runs compound-intelligence analysis via Grids, performs document review and risk assessment, captures
  information with a Notetaker, and answers questions through Chat and agentic dashboards backed by real-time data connections.
  It targets investment banking, consulting, private equity and credit, and asset and wealth management. Model ML is a fintech
  company backed by QED Investors. The company publishes a trust center and a security program (ISO/IEC 27001, SOC 2 Type
  II, GDPR) but does not currently expose a public developer API, SDK, or API documentation surface.
url: https://raw.githubusercontent.com/api-evangelist/model-ml/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- qed-investors
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-20'
tags:
- Company
- Fintech
- Artificial Intelligence
- Financial Services
- AI Agents
- Investment Banking
- Enterprise
- Document Automation
tags_raw:
- Company
- Fintech
- Artificial Intelligence
- Financial Services
- AI Agents
- Investment Banking
- Enterprise
- Document Automation
- Financial-Services
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://www.modelml.com/
- type: Blog
  url: https://www.modelml.com/blog
- type: Security
  url: https://www.modelml.com/security
- type: TrustCenter
  url: https://trust.modelml.com/
- type: Compliance
  url: https://www.modelml.com/security
- type: TermsOfService
  url: https://www.modelml.com/legal/terms-of-service
- type: PrivacyPolicy
  url: https://www.modelml.com/legal/privacy-policy
- type: Support
  url: https://www.modelml.com/contact-us
- type: DomainSecurity
  url: security/model-ml-domain-security.yml
x-enrichment:
  date: '2026-07-20'
  status: enriched
  artifacts_added: 2
  pass: local-v1

Model ML API — frequently asked questions

Does Model ML have an MCP server?

Yes. APIs.io lists 1 MCP server for Model ML: Remote MCP server at mcp.modelml.com over HTTP.

Is the Model ML API ready for AI agents?

Model ML has a Kin Score of 14.4 out of 100 (emerging) and an Agent Readiness score of 12.2 (agent-aware), scored by API Evangelist on 2026-11-06.

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