BrandGuard AI

BrandGuard AI built from scratch
Final look
Final look
Final look
Final look
Final look

Inspiration

Did you know that nearly every brand violation in design is discovered after the design is already finished?

Teams still rely on PDFs, shared docs, and manual reviews to catch brand mistakes. Colors are slightly off. Fonts are inconsistent. Text breaks brand tone. These issues are usually found late, leading to rework, delayed publishing, and frustrated creators.

We realized the problem was not that users lacked brand guidelines. The problem was that brand rules were passive while design was active.

BrandGuard AI was inspired by a simple idea: brand rules should work like guardrails, not checklists. If a mistake is predictable and easy to fix, the tool should catch it instantly and help correct it before the design is published.

What it does

BrandGuard AI is an Adobe Express add on that evaluates brand compliance while a design is being created.

It analyzes the canvas in real time and generates a Brand Compliance Score from 0 to 100, giving users an immediate signal of whether their design is safe to publish. Alongside the score, it highlights clear issues such as missing content, layout imbalance, or brand voice violations.

Instead of only reporting problems, BrandGuard AI introduces fixes. For issues that can be safely corrected, users can apply fixes directly rather than manually searching through guidelines or reworking the design.

This turns brand compliance from a review step into a live design experience.

How we built it

We built BrandGuard AI as an Adobe Express Add on using the official Add on SDK.

Deterministic checks run inside the document sandbox to safely analyze layers, structure, and content without breaking the design. The UI communicates with the sandbox using runtime API proxies, ensuring changes are reflected immediately and securely.

AI is integrated through a backend analysis service that interprets natural language brand rules and identifies higher level issues such as tone deviation or risky wording. AI is optional but still added, though it never blocks the experience. When unavailable, the system falls back to reliable rule based logic.

This approach allowed us to demonstrate design intelligence while keeping the product stable and production safe.

Challenges we ran into

One of the biggest challenges was working within the constraints of the Adobe Express sandbox, where direct document mutations are intentionally limited.

Instead of forcing unsafe changes, we designed first added guided fixes that are scoped, predictable, and reversible. This ensured that the fixes respected platform constraints while still providing real value.

Another challenge was managing AI variability. We had to enforce strict output schemas and graceful fallbacks so that AI insights could enhance the experience without introducing instability.

Balancing speed, safety, and intelligence within a hackathon timeline required careful technical tradeoffs.

Accomplishments that we're proud of

We built a fully functional Adobe Express add on that reads live canvas data and evaluates it against user defined brand rules.

The Brand Compliance Score proved especially effective because users understood it instantly, without needing explanations or documentation.

We are also proud of the system design. BrandGuard AI is extensible by design and can evolve to even more advanced AI and ML powered compliance without breaking existing workflows.

Most importantly, we transformed brand compliance from static documentation into an active design companion.

What we learned

We learned that users do not want more brand rules. They want feedback at the moment they are designing.

Numeric and visual signals like a compliance score are far more effective than written guidelines alone.

From a technical perspective, we learned how to design fail safe AI systems that enhance rather than replace deterministic logic, especially within constrained platform environments.

What's next for BrandGuard AI

Next, we plan to extend the same engine to accessibility and regulatory compliance, including color contrast checks, readability for color vision deficiencies, and accessibility readiness.

We also see strong potential in batch fixes, approval workflows for non enterprise teams, and brand health analytics over time.

Long term, BrandGuard AI can become a design governance layer that ensures content is brand safe, accessible, and publish ready before it ever leaves Adobe Express.