Newton Research
Newton Research builds a team of specially trained AI agents for marketing analytics. Pre-built or custom agents connect to a customer's existing data infrastructure, write and execute code, and automate analytics workflows — data exploration and preparation, audience management, Customer 360, planning and activation, cross-channel measurement and attribution, anomaly detection, yield management, and automated reporting — with data remaining on the customer's own instance. Founded by John Hoctor, Matthew Emans, and Steven Bennett, the company is backed by Bessemer Venture Partners and is a member of the NVIDIA Inception program. Newton states SOC 2, GDPR, and CCPA compliance. No public developer API surface is published as of this profile.
Index entry only — little beyond a description and a link, and nothing machine-readable enough for an agent to act on without a human reading the site first.
API Evangelist profiles Newton Research 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 — Newton Research scores 11.7/100 (minimal), 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 Newton Research
Each block below is one kind of artifact we hold for Newton Research. 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 Newton Research — 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.
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
Operate 1
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
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