# Brainient

**Canonical:** https://apis.io/providers/brainient/  
**Website:** https://brainient.com  
**APIs profiled:** 0

Brainient was a London-based advertising technology company founded in 2009 by Emi Gal that specialized in interactive video advertising and Dynamic Creative Optimization (DCO). Its platform made online video ads more personalized and interactive by matching creative to real-time context such as socio-demographics, geolocation, device, time of day, and weather. Brainient was acquired by Teads in September 2016 and folded into the Teads Studio division; the standalone Brainient brand and its brainient.com domain are now defunct. This profile was surfaced as a portfolio company of 500 Global and added to the API Evangelist network as a lead. No public API surface, developer documentation, or machine-readable specification was located for Brainient during enrichment.

## Kin Score — 5.0 / 100 (minimal)

Scored 2026-08-21 under rubric 0.12.0. Trend: flat (+0.0 from 5.0).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 0.0 |
| Commercial Clarity | 0.0 |
| Access Clarity | 0.0 |

## 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).

## Tags

Company, Advertising, AdTech, Video Advertising, Interactive Video, Dynamic Creative Optimization, Acquired, Defunct

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