Brand Context Protocol (BCP) and Vashor are both answers to the same problem: AI and growing content volume make it harder for a brand to stay itself. They work at different layers. Brand Context Protocol is a format for writing a brand down so that people and AI models can both use it, with generation skills and a brand check built around it. Vashor is an independent check for advertising: it judges ad copy and targeting against the brand’s declared strategy before an ad goes live, and never writes the copy.
This page compares them as fairly as we can. Information about Brand Context Protocol comes from its makers’ public description at craft.wild.as/bcp, checked in October 2026.
What Brand Context Protocol is
According to its makers, the design studio Wild, BCP is “one place that holds everything that makes a brand itself, written so a person and an AI can both use it.” Key points from their description:
- An open format. A structured, markdown-based way of documenting a brand, published openly for anyone to use, with consulting from the studio available to build it out.
- A “brand truth” for AI. The format sits between the model and the tools a team uses, so that AI outputs draw on the same brand definition.
- Generation skills. Skills that use the brand definition to produce on-brand outputs such as landing pages, decks, ads and emails.
- Brand Check. A step that scores outputs against the brand for conformance.
- Broad tool coverage. Described as model-agnostic and deployable into design, office and email tools.
What Vashor is
Vashor is a brand governance platform for advertising:
- It structures the declared strategy. A brand’s positioning, audience, voice and prohibitions are turned from a static document into a structured store that ads can be judged against.
- It checks before spend. Each ad is checked against that strategy before it goes live, starting inside the Google Ads console.
- It checks copy and targeting. The check covers whether the message and the audience it is aimed at match the strategy.
- It explains, it doesn’t rewrite. Vashor returns a level (bad, ok, good, with a reference score) and comments on what mismatches the strategy and why. It never generates the copy.
- It is independent of the source. The same check applies whether the ad came from an in-house specialist, an agency, a template or any AI tool.
The core difference: who judges the output
Both approaches agree that a brand needs a usable, structured definition. Where they differ is in how output is judged.
In BCP, generation and checking live in the same system: skills produce outputs from the brand truth, and Brand Check scores those outputs. That is a coherent design for teams that produce most of their content through one AI workflow.
Vashor is built on the opposite principle: the check is separated from generation entirely, so it can judge copy it didn’t write and has no stake in. We explain why we think that separation matters in brand compliance tool vs AI copy generator. In short: a system tends to approve its own patterns, and most ad copy in a real account comes from many sources at once, not from one workflow.
Side by side
| Brand Context Protocol | Vashor | |
|---|---|---|
| What it is | Open format for documenting a brand, plus generation skills and a brand check | Independent check for advertising |
| Main job | Give people and AI a shared brand definition to create from | Judge each ad against the declared strategy before it runs |
| Generates content | Yes, through skills | No, never |
| Checks content | Yes, scores outputs (Brand Check) | Yes, that is its only job |
| Checks copy from other sources | Not described | Yes: specialists, agencies, templates, any AI tool |
| Advertising focus | General content (pages, decks, ads, emails) | Paid advertising, starting in Google Ads; copy and targeting |
| Form | Open format; consulting from the studio | Software product |
Which one fits which situation
BCP fits teams that want to write their brand down in an open, AI-readable format and produce content through AI workflows that draw on it, across design, documents and email.
Vashor fits teams whose risk sits in paid advertising: many ads, written by many hands, going live daily, where someone needs an independent verdict on each one before budget is spent. Multi-brand retailers advertising other companies’ brands are a typical case, as are brands whose ads are written by agencies.
They can work together. A well-structured brand definition, in any format, makes an independent check more precise. A team could hold its brand truth in a BCP-style file and still want an independent check at the point where ads are published.
FAQ
What is Brand Context Protocol?
Brand Context Protocol is an open, markdown-based format created by the design studio Wild for documenting a brand so that both people and AI models can use it. Its makers describe generation skills that produce on-brand outputs and a Brand Check that scores outputs against the brand.
Is Vashor an alternative to Brand Context Protocol?
Partly. Both address brand consistency in the AI era, but at different layers. BCP focuses on a shared brand definition and AI-assisted creation. Vashor focuses on independently checking advertising, from any source, against the brand’s strategy before it runs.
Does Vashor generate content like Brand Context Protocol’s skills?
No. Vashor never writes or rewrites copy. It judges copy written by people, agencies or AI tools and explains what doesn’t match the strategy.
Can you use Brand Context Protocol and Vashor together?
Yes. A structured brand definition helps any check be more precise, and an independent check at the point of publication covers ads that come from sources outside a single AI workflow.
Information about Brand Context Protocol is based on its makers’ public page, checked in October 2026, and may have changed since. See how Vashor checks your content →