About Us
At The Transparency Company
We’re on a mission to champion integrity in the online marketplace by empowering businesses to build trust through authentic customer relationships. In a digital landscape where opinions shape consumer decisions, we recognize the significant impact of review credibility on a business’s success.
That’s why we provide businesses with the tools to protect their reputation, align with the latest FTC regulations, and promote transparency as a core value. Founded with a vision to promote fairness and authenticity, The Transparency Company uses advanced technology to detect fake reviews and verify the integrity of online feedback. Our services go beyond detection – we work closely with businesses to help them build a trustworthy digital footprint, creating a level playing field for companies that value honest practices.
That’s why we provide businesses with the tools to protect their reputation, align with the latest FTC regulations, and promote transparency as a core value. Founded with a vision to promote fairness and authenticity, The Transparency Company uses advanced technology to detect fake reviews and verify the integrity of online feedback. Our services go beyond detection – we work closely with businesses to help them build a trustworthy digital footprint, creating a level playing field for companies that value honest practices.
Our team
Our team is composed of industry experts and thought leaders who bring extensive experience in digital compliance, marketing, and technology. We support a range of clients, from small businesses to large enterprises, who are committed to maintaining integrity in their online presence. Together, we’re building a community where businesses can confidently engage with their customers, knowing that their reviews reflect genuine feedback and foster real connections.
Curtis Boyd
Founder
Curtis Boyd is the founder of The Transparency Company. His expertise in Online Reputation Management gave The Transparency Company the direction for the technology.
Roman Grabar
Sr. DevOps Engineer
Roman is the right hand man behind the scenes, making the API's work and driving functionality to a very large data pipeline. He's more than a full-stack developer, he's family.
Rashid Ali
Front-End Developer
Rashid is one of the hardest working individuals, who refuses to say, " I can't do that." His commitment to his projects has been invaluable to our team.
Our Services
At The Transparency Company, we’re not just detecting fake reviews – we’re building trust in the online marketplace.
Review Auditing and Detection
Leveraging advanced technology to identify and flag fake reviews.
FTC Compliance Assistance
Providing tools and guidance to help businesses stay aligned with federal guidelines on review authenticity.
Trust Verification Programs
Certifications and audits to enhance credibility and attract informed consumers.
Our Process
What is our workflow?
1
Data collection
Hybrid Data Mining/API’s
We collect all the information we can from:
1. Review Content
2. Reviewer Profiles
3. Business Profiles
1. Review Content
2. Reviewer Profiles
3. Business Profiles
2
Data Analysis
Our Process
The aggregated data is analyzed by our server and evaluated based on pre-trained AI Models.
3
Data Synthesis
We build profiles
Based on the unique scores of each reviewer, we profile them based on known fraudulent profiles.
Our metrics
Profile Metrics
Profile data includes the behavioural data of a reviewer. The businesses they have reviewed, the types of businesses, the types of reviews they leave.
Distance Matrix Analysis
We look at each reviewer individually and look at all the businesses they have reviewed, then calculate the distances between all of those businesses.This helps us to understand a group of reviewers of a particular business, particularly about where they live and write reviews.
Reviewer Pod Analysis
The review pod analysis measures if there are large groups of reviewers who have reviewed the same businesses. It looks a lot like a private reviewer circle. This is often a sign of someone being paid or incentivized to publish reviews.
Reviewer Image Analysis
Every profile belongs to a unique human being, with unique access to images and where they source their profile pictures. Often times, review spammers will steal photos from celebrities from instagram and facebook. This is why we check reviewer images to understand a bit about the profile.
Content Metrics
Content Metrics are created from the content of the review itself. Not all reviews are created equal, and we look at them closely.
Natural Language Processing
As human beings we all have our own unique authorship style, the way we write sentences, ect. We use machine learning to identify unique authorship styles. This is helpful when looking for reviews written by the same author.
Sentiment Analysis
Fake reviews are generally higher in sentiment than real reviews, which is why we look at sentiment to make a prediction whether a review is real or fake. We also look at use of exclamation marks and other indications that show over the top positive sentiment.
Keyword Stuffing
We read review content and measure keyword density. This way we can understand if the business is stuffing keywords into the reviews in order to rank better for specific industry-related keywords. This is absolutely a sign of review fraud.
See our technology in action
Consumers are 15x more likely to have a negative experience from a company with fake positive reviews.
Try it now