Agile Loop

Agile Loop L.L.C. is a London-founded enterprise AI company (founded 2023, backed by 500 Global) building Large Action Models — action-first foundation models trained on thousands of software interfaces so AI agents can operate any user interface and execute multi-step workflows end-to-end from natural-language instructions. Its product suite spans Sector Fusion (telecom network analytics), an Intelligent Evaluation Platform (AI scoring and fraud detection), LLM Ops (governance for LLM applications), an Aviation Ops Suite, and SAM-X (natural-language Excel automation), alongside the open-source Synapse Copilot toolkit for connecting LLMs to APIs and an embeddable Copilot widget for SaaS products. Agile Loop publishes no public OpenAPI, developer portal, or versioned client SDKs at the time of this profile.

Agile Loop is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, AI Agents, Large Action Models, and LLM.

Agile Loop’s developer surface includes engineering blog and 13 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

9.1/100 minimal ▬ flat Agent 0/100 human only Front door AI 6/6 dominant Heartbeat 0/100 dormant library Full breakdown ↓
scored 2026-11-13 · rubric v0.28.0 · Show this score on your site →

0 APIs

Company Artificial Intelligence AI AgentsLarge Action ModelsLLM Automation Enterprise AI Foundation Models

Kin Score

Kin Score How this is scored →
scored 2026-11-13 · rubric v0.28.0

Composite quality — 9.1/100 · minimal

Contract Quality 0.0 / 21

Developer Ergonomics 1.2 / 17

Access Clarity 2.2 / 17

Operational Transparency 2.1 / 11

Contract Governance 0.0 / 10

Discoverability 4.1 / 9

Regulatory Posture 0.5 / 15

Agent readiness — 0/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 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 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 AI & Biometrics 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 Ask about this →
MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship Ask about this →
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author Ask about this →
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) Ask about this →
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) Ask about this →
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes Ask about this →

13 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 Ask about this →
Developer Ergonomics scores 7.1 — up to +18.6 composite points Ask about this →
Access Clarity scores 12.8 — up to +17.4 composite points Ask about this →

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.

Not sure how this applies to your stack? Ask about any one item. Kin Lane reads every question, looks at your profile and your situation, and replies with what a fix would take — scoped to that one area, priced up front, yours whether you ship it or not. Ask a question →

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/agile-loop-llc/apis.yml: open an issue on github.com/api-evangelist/agile-loop-llc 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 →

Privacy & Data 1

Its role, the data it processes, retention and transfers, quoted from its own privacy page.

Agile Loop

16 quoted statements, read from Agile Loop's own page on 2026-11-09.

PRIVACY

Security Posture 1

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

Agile Loop Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Build 3

SDKs, sample code, and the tooling you integrate with

Packages

Packages

GitHubOrganization

GitHubOrganization

SourceCode

SourceCode

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 3

Status, limits, changes, and where to get help

IssueTracker

IssueTracker

Releases

Releases

Discord

Discord

Commercial 1

Pricing, plans, and the legal terms of use

PrivacyPolicy

PrivacyPolicy

Company 5

The organization behind the API

Website

Website

About

About

Blog

Blog

LinkedIn

Twitter

Twitter

Other 1

Properties that don't map to a standard resource type

DataProcessing

DataProcessing

Source (apis.yml)

aid: agile-loop-llc
name: Agile Loop
description: Agile Loop L.L.C. is a London-founded enterprise AI company (founded 2023, backed by 500 Global) building Large
  Action Models — action-first foundation models trained on thousands of software interfaces so AI agents can operate any
  user interface and execute multi-step workflows end-to-end from natural-language instructions. Its product suite spans Sector
  Fusion (telecom network analytics), an Intelligent Evaluation Platform (AI scoring and fraud detection), LLM Ops (governance
  for LLM applications), an Aviation Ops Suite, and SAM-X (natural-language Excel automation), alongside the open-source Synapse
  Copilot toolkit for connecting LLMs to APIs and an embeddable Copilot widget for SaaS products. Agile Loop publishes no
  public OpenAPI, developer portal, or versioned client SDKs at the time of this profile.
url: https://raw.githubusercontent.com/api-evangelist/agile-loop-llc/refs/heads/main/apis.yml
deliveryModel:
  model: library
  license_evidence:
    not_product:
    - agile-loop/synapse-copilot
  open_source: unknown
  commercial: false
  callable_host: false
  label: Library · distributed through package registries, no callable service
  confidence: low
  source:
  - repository-not-product
  generated: '2026-09-25'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - security
  generated: '2026-11-13'
  method: derived
image: https://agileloop.ai/agile-loop-logo.svg
x-type: company
x-source: vc-portfolio
x-backed-by:
- 500-global
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-17'
tags:
- Company
- Artificial Intelligence
- AI Agents
- Large Action Models
- LLM
- Automation
- Enterprise AI
- Foundation Models
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: IssueTracker
  url: https://github.com/Agile-Loop/Synapse-Copilot/issues
- type: Releases
  url: https://github.com/Agile-Loop/Synapse-Copilot/releases
- type: DomainSecurity
  url: security/agile-loop-llc-domain-security.yml
- type: Packages
  url: packages/agile-loop-llc-packages.yml
- type: Website
  url: https://agileloop.ai
- type: About
  url: https://agileloop.ai/about
- type: Blog
  url: https://agileloop.ai/blogs
- type: PrivacyPolicy
  url: https://agileloop.ai/privacy-policy
- type: GitHubOrganization
  url: https://github.com/Agile-Loop
- type: SourceCode
  url: https://github.com/Agile-Loop/Synapse-Copilot
- type: LinkedIn
  url: https://www.linkedin.com/company/agileloop/
- type: Twitter
  url: https://x.com/AgileLoopAI
- type: Discord
  url: https://discord.com/invite/Yv6wTEAKyf
- type: DataProcessing
  url: privacy/agile-loop-llc-privacy-policy.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence
x-legal-name: Agile Loop L.L.C.

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