Percolata website screenshot

Percolata

Percolata is a Palo Alto, California predictive-analytics company that applies machine learning to help retailers optimize labor scheduling and marketing spend. Its platform forecasts hourly sales, in-store traffic, and takeout demand to drive staffing optimization and marketing budget allocation, with published claims of 4x higher forecast accuracy, 10-20% same-store sales lift, and a forecast-accuracy guarantee. Named customers include 7-Eleven, Uniqlo, and Telefonica. The company is backed by Andreessen Horowitz (a16z) and Google Ventures (GV). Percolata does not publish a public developer portal or REST API reference; its retail platform is delivered as a managed product with custom application integration. The percolata.com marketing site is now served by Wix, which provisions a live, first-party Model Context Protocol (MCP) endpoint and an llms.txt for agentic access to public site content.

Percolata is profiled on the APIs.io network. Tagged areas include Company, Retail, Analytics, Machine-Learning, and Predictive Analytics.

Percolata’s developer surface includes support and 6 more developer resources.

🌐 Visit website 📡 Source on GitHub
6.1/100 minimal ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0
0 APIs 1 MCP Servers
CompanyRetailAnalyticsMachine-LearningPredictive AnalyticsWorkforce OptimizationMarketing Optimization

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0
Composite quality — 6.1/100 · minimal
Contract Quality 0.0 / 25
Developer Ergonomics 0.0 / 20
Access Clarity 0.0 / 20
Operational Transparency 0.3 / 13
Contract Governance 0.0 / 12
Discoverability 5.7 / 10
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
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.
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/percolata: 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 →

MCP Servers 1

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

Percolata MCP Server

MCP SERVER

Security Posture 1

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

Percolata Domain Security

TLSv1.3 · HSTS

SECURITY

Resources

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

MCPServer
MCPServer
 LLMsTxt
LLMsTxt

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization
GitHubOrganization

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity
DomainSecurity

Operate 1

Status, limits, changes, and where to get help

Support
Support

Commercial 1

Pricing, plans, and the legal terms of use

PrivacyPolicy
PrivacyPolicy

Company 1

The organization behind the API

Website
Website

Source (apis.yml)

apis.yml Raw ↑ 
aid: percolata
deliveryModel:
  model: unknown
  open_source: false
  commercial: false
  callable_host: false
  label: Delivery model not determined — needs a product licence on record
  confidence: low
  source:
  - none
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - url: http://percolata.com
    status: 301
    note: declared website redirects to https://percolata.wixsite.com/percolata — a different registrable domain (percolata.com
      -> wixsite.com), possible rename or acquisition (probed 2026-09-03, roadmap#169)
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/percolata.png
name: Percolata
description: Percolata is a Palo Alto, California predictive-analytics company that applies machine learning to help retailers
  optimize labor scheduling and marketing spend. Its platform forecasts hourly sales, in-store traffic, and takeout demand
  to drive staffing optimization and marketing budget allocation, with published claims of 4x higher forecast accuracy, 10-20%
  same-store sales lift, and a forecast-accuracy guarantee. Named customers include 7-Eleven, Uniqlo, and Telefonica. The
  company is backed by Andreessen Horowitz (a16z) and Google Ventures (GV). Percolata does not publish a public developer
  portal or REST API reference; its retail platform is delivered as a managed product with custom application integration.
  The percolata.com marketing site is now served by Wix, which provisions a live, first-party Model Context Protocol (MCP)
  endpoint and an llms.txt for agentic access to public site content.
url: https://raw.githubusercontent.com/api-evangelist/percolata/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- a16z
- gv
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-20'
tags:
- Company
- Retail
- Analytics
- Machine-Learning
- Predictive Analytics
- Workforce Optimization
- Marketing Optimization
tags_raw:
- Company
- Retail
- Analytics
- Machine Learning
- Predictive Analytics
- Workforce Optimization
- Marketing Optimization
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: http://percolata.com
- type: GitHubOrganization
  url: https://github.com/percolata
- type: MCPServer
  url: mcp/percolata-mcp.yml
- type: LLMsTxt
  url: llms/percolata-llms.txt
- type: DomainSecurity
  url: security/percolata-domain-security.yml
- type: Support
  url: https://www.percolata.com/contact-form
- type: PrivacyPolicy
  url: https://www.percolata.com/terms-of-policy
x-enrichment:
  date: '2026-07-20'
  status: nochange
  artifacts_added: 0
  pass: local-v1

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