# Newton Research

**Canonical:** https://apis.io/providers/newton-research/  
**Website:** https://www.newtonresearch.ai/  
**APIs profiled:** 0

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.

## Kin Score — 12.6 / 100 (emerging)

Scored 2026-08-19 under rubric 0.12.0. Trend: flat (+0.4 from 12.2).

| Facet | Score |
|---|---|
| Discoverability | 57.4 |
| Contract Quality | 0.0 |
| Governance | 18.2 |
| Contract Governance | 18.2 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 4.8 |
| Commercial Clarity | 18.4 |
| Access Clarity | 18.4 |

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (1)

- **Newton Research Domain Security** — TLSv1.3 · HSTS · DMARC

## Plans (1)

- **Newton Research Plans Pricing**

## Tags

Company, Ai Ml, Marketing Analytics, MarTech, AdTech, AI Agents, Data Science, Analytics

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/newton-research/). Scores are computed from the provider's own public artifacts under a published rubric.