Huski Blog
Huski.ai exists to make brand protection and growth easy with cutting-edge AI.
Here is why and how.
The WHY
Creativity is a precious core part of humanity, a brand is what makes a memorable impression of that creation on people. A brand differentiates one business, service, or product from another; it represents the prized innovation that starts any venture. It also conveys core values, builds trust, and provides personal connections between a business and its consumers.
As the wealth of data and demand for specialization increase, more long-tailed brand owners emerge. In other words, brand owners can gain significant traction by producing smaller amounts of a unique, well-crafted product or service. Consumer behaviors are shifting away from buying generic products that merely suffice. Instead, consumers wish to buy branded products that fit their ultra-personalized needs. A decade ago, a brand owner may only mean a Fortune 500 company like Apple or Nike. Today, a brand owner could be a social media influencer or an indie artist working from home. Tomorrow, you and I could have personal brands in the Metaverse. We could exchange innovations with cryptocurrencies and certify them with NFTs. The bar to become a brand owner is more achievable than it has ever been–and soon enough, the opportunity will be accessible to anyone.
Sounds fantastic, right? There’s only one catch: creating and maintaining a brand is not hassle-free. There have always been and will always be infringers on your creativity and innovations. Somewhere, someone may be working on things very similar to yours, knowingly or unknowingly, and maybe branding them in the same way.
So, brand owners always want to be aware of two things:
- Am I infringing on others’ brands?
- Are others infringing on my brand?
Answering these two questions is gruelingly hard. First, one must have the skillsets or tools to gather such information in the vast information space crossing commerce, marketing, branding, and litigation. It also requires deep knowledge across different domains, such as market space insights, products, intellectual properties, litigation practice, and so on, to understand the problem and find possible remediation solutions. These challenges make it difficult, if not impossible, for emerging brand owners to even think about affordable brand protection solutions. These obstacles lead to unequal opportunities for smaller brand owners to grow their brands and focus on innovation.
There needs to be an affordable solution to answer those two questions in order to help brand owners protect their brands and give them peace of mind to focus on innovation and enjoy the benefits of their creations.
This is why Huski exists.
The HOW
Our mission is to build the industry’s first and the best brand and insight search engine.
The goal is simple. The search engine is to identify where and how branded content is used in the eCommerce space in various formats, such as text, images, and even videos. The engine also generates actionable insights to help brand owners to understand the impact and take actions accordingly. Google is for organizing the world’s information, while Huski exists to organize (and understand) the world’s branding information.

This article further explains the tech behind it.
The WHO
We are a group of engineers and visionaries who made self-driving cars, combat decision engines, AI chips, recommendation systems, and more. As innovators ourselves, we strongly believe that hassle-free brand growth drives innovation forward, which in turn drives humanity forward.
We want to help individuals, professionals, and businesses of all sizes enjoy and benefit from the process of innovation.
It is paramount, it is fragile, and it is on us.
What Is Huski.ai?
PRODUCT INTRODUCTIONHuski.ai exists to make brand protection and growth easy with cutting-edge AI. Here is why and how. The WHY Creativity is a precious...
PRODUCT INTRODUCTION
If you own an online store, you might own a legal “time bomb” due to some of your products or marketing materials unknowingly infringing on others. But there is no easy way to find out.
If you are a trademark attorney, you might manually search for infringement cases to take on in eCommerce. But there is no easy way to let the cases fly to you.
Thanks to Huski’s brand search engine, these tasks are becoming increasingly simple.
First, go to www.huski.ai, and tell us which store you want to exam.

We support the following major marketplaces. Yes, we support “Shopify”, which means we support millions of independent sites in the Shopify ecosystem.

After submitting the analysis request, all you need is to wait for the report. Here is what’s going to happen.

After a while, you will get the most advanced brand infringement analysis report that covers the store of your selection and the products there got checked against millions of branded materials and other products.

Visit www.huski.ai to see what’s inside. Your peace of mind starts here.
ENGINEERING
When we create new things, we differentiate. To claim that differentiation, we iron a brand to it: a unique identifier that represents itself. To grow those new things we’ve created, we market its brand. We’ve been doing this for about 5000 years, from the ancient Egyptian artisans to the modern Metaverse content creators. Branding activities have always been and will always be a centerpiece of innovation and culture.
Currently, a brand could be a piece of text, an image, or a multimedia clip, which claims its uniqueness among others in the same domain and conveys its own ideas. Brand identity could appear in many forms online: product descriptions, social media posts, you name it, and the internet hosts a wealth of these brand images. When consumers view a brand’s image, they associate it with their preconceptions about the brand and how it compares to other brands. Successful branding creates positive relationships with consumers who carry a perception of the brand’s quality and trustworthiness. Creators want to know whether people feel good about their brand, whether there are copycats of their brand, whether they need to grow into new sectors, and so much more. However, the tools available today for brand creators to address those key questions are insufficient and short-term–like duct tape on a leaking pipe.
This is why we focus on developing a search engine for branding activities.
Challenges
Immediately, we’re facing a number of big technical challenges (existing tools are like duct tapes for a reason).
Data Challenges. We need a scalable data infrastructure to gather branding information. Our goal is bold and simple: our dataset should be large and specific enough to answer the following questions.
- How many brands are there in the whole world? How do they differentiate their brand image from others and convey their unique message? Which companies own them and what do they do? How each brand is perceived by its customers?
- What are all the products being sold on earth right now? What are their brands and how do they protect the brands?
- What is the knowledge graph that involves brand owners, sellers, products, infringement cases, attorneys and law firms look like, and how do we derive insights from this graph?
Unlike other vertical search engines, e.g, Google Scholar or Yahoo Finance, a brand search engine is much more challenging even at the data level. We must reach the far corners of the web to gather image, text, and multimedia data that are suitable. In addition to domain-specific data sources, we need to harvest information from the vast expanse of the web and establish our own standardized, dynamic, and heterogeneous dataset. This process is like getting the berries out clean from a chantilly cake. Precision and scalability are key.

Algorithmic Challenges. Brand recognition turns out to involve many fundamental challenges to the field of AI. I will elaborate on image and text respectively.
Brand Recognition in Images
Goal: Recognize any brand appearances in any given image
Challenges
- Class Explosion. Usually, object detection or recognition models deal with class numbers ranging from 1 ~ 1000. For example, in autonomous driving, the models are taught to recognize 20~30 traffic objects. In the great benchmark of MS COCO, there are 80 classes and 1K classes in the ImageNet. In our case, there are more than 1 million brands that appear in pictorial forms in the US alone. Moreover, it’s even difficult to collect enough training instances of them, let alone labeling a significant part of them. The table below summarizes the class explosion challenge.

2. Object Variety in Branding Images. First, there could be image/text hybrid, or even language hybrids. Second, the objects could be really abstract. Third, there could be distortion, angling, different lighting conditions, complex backgrounds, and so on. The model needs to be reliable against all of these conditions.
3. Appearance Variety per Brand. As it shows below, one brand concept could appear in a variety of forms. The concept is the same, however, the appearances could vary dramatically. The model must learn the fundamental themes of a brand’s concepts instead of colors or textures — as the majority of the pretrained benchmark models do.
Goal: Detect any mentions about a brand, its products, and the product features in any given text.
Challenges
- Context Matters. The majority of English words are actually registered brand marks. However, when we use the words, we don’t always refer to their branding meanings. Therefore, simple word matching would never work. Here is an example. (brand, product, and product feature being labeled with red, green, and blue respectively.)

2. Grammar Sometimes Does Not Matter. Especially in the eCommerce domain, a product title could be literally written as “chicago dogs zephyr patron hot dog grey adjustable strapback cap”, which breaks the majority of NLP models trained with normal grammar sentences.
3. Abbreviations are everywhere. For example, one could write “my new NB shoes are very comfortable. It says it only weighs 10 oz. Crazy!” Our model must learn the different names, including slang, of a brand in order to gather all instances of a brand’s usage.
Infrastructure Challenges. A comprehensive knowledge graph that provides insight into all brands, their products, and related companies is still in the works. Currently, Huski supports the largest knowledge graph in the field. However, there are millions of brand images that appear in image or text forms. There are also billions of products. All those entities form a graph with edges representing all kinds of relations that are consistently changing and growing. Being able to build and maintain such a dynamic knowledge graph and support low latency queries (e.g. 200ms) is another challenge to our data infrastructure.
Last but not least, we are a startup. It goes without saying that we need to be smart about solving all the above challenges while staying on budget. To say the least, it’s difficult.
Breakthroughs
Despite the challenges, we wouldn’t be writing this article if we haven’t advanced in all of those directions. In particular, we are proud to share a couple of breakthroughs that made the first branding search engine possible.
- We’ve found a way, without labeling any data, to reliably detect over 1,000,000 pictorial brands in real-life images. Learning by unsupervised show-and-tell, our model represents what’s possible at the frontier of computer vision. It learns to detect brands even in very challenging scenarios.


The model can also go further to recognize highly blurred, distorted, and textured brand materials. See how our model still recognizes the Monster logo when Google Image Search gives some irrelevant grey images.

2. We’ve found a way, without labeling any data, to reliably detect over 3,000,000 textual brands in texts. Our model recognizes the brand name, the product, and the product features in common English or product titles or descriptions. The model uses a new paradigm — named entity recognition with entailment learning — to classify brands. It also recognizes the context so that it wouldn’t blindly treat every word as “brand” simply because they appeared in a “brand mark database”. A few examples are as follows. (Color code: brand /product /product features)

3. Multitask search. We are also the first to introduce “multitask search” in a brand search engine. People can use the combination of image and text in one single query and get a unified search result. The picture below shows how we use it in a trademark registrability analysis. More applications of multitask search to come later.



4. We found a way to efficiently harvest branding data across all Internet, including central marketplaces such as Amazon, eBay, or independent places like Shopify sites. We also keep monitoring all brand/trademark registrations, lawsuits, and other dynamics within the US. Our knowledge graph is derived, by the AI breakthroughs, from such data and we are proud of serving the queries very efficiently.
Conclusion
Although we’re still in the early days of our search engine, we are very excited to see the future possibilities which could help creators discover their brand’s footprint, understand the contexts, and take actions to protect and grow their brands. The challenges are unique and exciting. The technologies are capable of enabling many things. And we are just getting started.
Visit www.huski.ai to find out more!