Lily AI
Lily AI, Inc. is a retail product-intelligence company whose platform, Lily Max, enriches e-commerce product catalogs so that products are legible to advertising platforms, search engines, onsite search, and AI shopping agents. Agents identify gaps in a retailer's product data, generate consumer-centric attributes and copy, run controlled tests against a holdout, and deploy the winning enrichments across Google Merchant Center feeds, Meta Commerce Manager catalogs, AI discovery and agentic commerce surfaces, and onsite PDP, search, and faceting. Lily AI sells to enterprise retailers, brands, and agencies and positions itself as a layer over the existing commerce stack rather than a replacement for a PIM or feed manager. The company raised a $25M Series B with participation from Canaan Partners, Conductive Ventures, Sorenson Ventures, and NEA. As of this enrichment pass Lily AI publishes no public developer portal, API reference, OpenAPI definition, SDKs, or GitHub organization; the platform is delivered as a managed enterprise service with onboarding handled through sales.
More than an index entry, but the surface is still mostly links rather than artifacts — the cohort most likely to move a full band from modest, well-targeted work.
API Evangelist profiles Lily AI the way a machine reads it — 1 machine-readable artifact, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Lily AI scores 19.0/100 (emerging), with a separate agent-readiness read of 0/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Lily AI
Each block below is one kind of artifact we hold for Lily AI. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
Security Posture 1
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Resources
Every other property we hold for Lily AI — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 1
Portal, sign-up, and the first successful call
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 1
Pagination, idempotency, versioning, errors, and events
Access & Security 1
Authentication, authorization, and security posture
Operate 3
Status, limits, changes, and where to get help
Commercial 3
Pricing, plans, and the legal terms of use
Company 4
The organization behind the API
Other 1
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/lily-ai · machine-readable index on apis.io