Distyl

Distyl is an applied-AI company architecting the AI-native enterprise. Rather than layering automation onto broken processes, Distyl reimagines enterprise operations from the ground up with AI at the core, partnering with Fortune 500 organizations across Telecom, Healthcare, Manufacturing, Insurance, Retail, and Financial Services to design and operationalize AI transformations and deploy production-grade agentic AI systems in weeks. Its product suite includes Weave, Distillery, Context Mesh, Context Views, Journey, Personalization, and Apprentice. Founded by operators and researchers from Palantir, CIA, OpenAI, Google DeepMind, Tesla, NASA, Stanford, and MIT, and backed by Coatue, OpenAI, Lightspeed, Microsoft, and Khosla Ventures. Distyl is a services/platform company with no public developer API; this profile captures its published web surface. Distyl is SOC 2 certified and GDPR compliant.

Distyl is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Enterprise AI, Agentic AI, and AI Agents.

Distyl’s developer surface includes engineering blog and 7 more developer resources.

14.8/100 emerging ▬ flat Agent 0/100 human only saas Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0
0 APIs
CompanyArtificial IntelligenceEnterprise AIAgentic AIAI AgentsMachine-LearningHealthcareFinancial-ServicesTelecom

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0
Regulatory Posture applies to this provider. Its tags matched the Telecommunications 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/.
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 github.com/api-evangelist/distyl: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Security Posture 1

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

Distyl Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

Access & Security 2

Authentication, authorization, and security posture

Commercial 2

Pricing, plans, and the legal terms of use

Company 2

The organization behind the API

Source (apis.yml)

apis.yml Raw ↑
aid: distyl
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: []
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/distyl.png
name: Distyl
description: Distyl is an applied-AI company architecting the AI-native enterprise. Rather than layering automation onto broken
  processes, Distyl reimagines enterprise operations from the ground up with AI at the core, partnering with Fortune 500 organizations
  across Telecom, Healthcare, Manufacturing, Insurance, Retail, and Financial Services to design and operationalize AI transformations
  and deploy production-grade agentic AI systems in weeks. Its product suite includes Weave, Distillery, Context Mesh, Context
  Views, Journey, Personalization, and Apprentice. Founded by operators and researchers from Palantir, CIA, OpenAI, Google
  DeepMind, Tesla, NASA, Stanford, and MIT, and backed by Coatue, OpenAI, Lightspeed, Microsoft, and Khosla Ventures. Distyl
  is a services/platform company with no public developer API; this profile captures its published web surface. Distyl is
  SOC 2 certified and GDPR compliant.
url: https://raw.githubusercontent.com/api-evangelist/distyl/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- khosla-ventures
- lightspeed-venture-partners
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-18'
tags:
- Company
- Artificial Intelligence
- Enterprise AI
- Agentic AI
- AI Agents
- Machine-Learning
- Healthcare
- Financial-Services
- Telecom
tags_raw:
- Company
- Artificial Intelligence
- Enterprise AI
- Agentic AI
- AI Agents
- Machine Learning
- Healthcare
- Financial Services
- Telecom
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://www.distyl.ai/
- type: Blog
  url: https://www.distyl.ai/blog/all
- type: PrivacyPolicy
  url: https://www.distyl.ai/privacy
- type: TermsOfService
  url: https://www.distyl.ai/terms
- type: LLMsTxt
  url: llms/distyl-llms.txt
- type: Conformance
  url: conformance/distyl-conformance.yml
- type: Compliance
  url: conformance/distyl-conformance.yml
- type: DomainSecurity
  url: security/distyl-domain-security.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

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