Bolster AI Difference
Large structured datasets and near-perfect AI models deliver online threat detection and response with unparalleled speed, scale, and accuracy.
Using AI to Detect Threats Since 2019
How Bolster LLMs and Computer Vision Works
Large Language Models
LLM models analyze vast amounts of text data to identify patterns, linguistic cues, and context indicative of fraudulent intent. With security prompts guided by our seasoned threat research team, these LLM models train on the evolving tactics used by attackers and recognize phishing and scam attempts in websites, emails, social media messages, and app stores and leverage RAG (retrieval augmented generation) to delivered automated, tailored takedowns.
Computer vision allows for image and video processing and can identify visual cues commonly associated with phishing and scam activities (i.e. fake logos, misleading website interfaces, or deceptive content.) Bolster then trains large image datasets with models that scrutinize web pages, social media pages, and app stores for anomalies, recognizing patterns consistent with real-life fraudulent activities.
Near Perfect AI Models
Here at Bolster, we have a commitment to perfection in AI deployment. Unlike many counterparts, Bolster adheres to a rigorous standard, refraining from deploying AI models until they attain near-perfect precision, recall, and F1 scores. This meticulous approach ensures that the models excel in accurately detecting and combating phishing, scams, and impersonations online. By demanding the highest confidence scores trained on millions of data points, Bolster sets the benchmark for AI detection and response.
How Bolster AI Stacks Up Against the Competition?
Unmatched Detection Powered by AI
Bolster’s detection capabilities are unmatched when it comes to speed. Leveraging artificial intelligence models with near-perfect precision, recall, and F1, Bolster can automatically identify phishing and scam content to understand true intent and brand infringement in less than 300 milliseconds – all with the highest accuracy rate.
150 TeraBytes Structured Data
6 Years Model Fine-Tuning
Large Language Models
GLUE NLP Score 84.7
Precision, Recall, F1 Scores = 1
Patented Detection Engine Built for Internet Scale
Bolster’s detection engine is powered by a headless browser infrastructure, a robust clustering and load balancing backbone, and the ability to analyze over 4 million records simultaneously.
Every record is analyzed for:
Document Object Model
Indicators of Compromise
Threat Intelligence Data
Redirects (up to 32)
Image or Text Variations
Accurate Identification with Threat Attribution and Modeling
By analyzing signals from both machine learning models and proprietary threat intelligence data, Bolster’s verdicts are based on comprehensive information with a false positive rate of 1 in 100,000 verdicts.
Bolster’s identifies threats with:
Open-Source Threat Feeds
Proprietary Threat Feeds
Automated Takedown Process for Easy Remediation
Bolster delivers a fully automated takedown process for malicious activity online through API integrations and Large Language Models (LLMs). Without relying on user-driven controls or manual input, Bolster averages a takedown speed of 60 seconds.
Bolster’s automates takedowns on the following:
18+ Social Media Platforms
800+ App Stores
Code Share Repositories
Forums & Blogs
If you’re just focused on takedowns, the damage is already done.
The best way to prevent damage to customers and your organization is to reduce the time to detect a threat. However, threat detection today mostly requires manual analysis by humans, making detection times take days or weeks.
What’s Your MTTD?
Bolster’s scalable and patented AI detection engine delivers industry-leading speed and accuracy, enabling the best mean time to response against phishing and scam attacks.
Records Analyzed by A.I. in a Full Browser Every Day
Malicious Records Taken Down in First 6 Hours of Going Live
False Positive Rate to Deliver the Highest Accuracy
Tool to Identify Malicious Typosquat Variants on the Web