
Advanced Matching Algorithm for Precise A/B Testing
klastroTest is Available on Many Areas!




“Unlock Your Design’s Potential: Increase sales with klastroTest.
klastroTest uses our unique matching algorithm that considers all features of user data.”


“No more propensity distance matching, No more cosine similarity and no need for server GPUs.
klastroTest uses a better solution to define your control and treatment groups. Also, klastroTest offers automatic calculations of ATE.
Your Apple Silicon laptop can run klastroTest faster than a server GPU“

klastroTest
Find your winning design with precise A/B testing for advertising and design
Why klastroTest?
While Propensity Score Matching (PSM) is a popular technique for reducing bias in observational studies, it has its own limitations. We do not use Propensity Score Matching. klastroTest observes all features of the input data and matches the control with treatment groups.
A/B Test Results in 3.6 Seconds? The Wait is Over!
In the fast-paced world of retail, timing is everything. Our solution, over thousand times faster than the traditional CPU based solution, delivers A/B test results in just about 3.6 seconds, empowering you to make real-time, data-driven decisions. Optimize campaigns daily and stay ahead of trends—no more waiting.
GPU Accelerated
Our benchmarks show our advanced solution processing matching tasks with tens of thousands of data points in about 3.6 seconds—something that takes traditional methods over 15+hours. Experience thousand times faster speeds with klastroTest*
*Experiment group: 45,192 x 12, Control group: 11,297 x 12 – Traditional solution: 15+ hours vs. klastroTest: 3.6 seconds
When the number of columns exceeds 100, Apple Silicon outperforms server GPUs by more than 2x.**
As dataset size grows, the performance gap only widens. Apple Silicon is so fast that cloud GPUs are simply unnecessary.
From personal to enterprise, we deliver the full speed of MPS acceleration in Python.
**Experiment group: 12,000 x 100, Control group: 12,000 x 100- server GPU took more than 20 secs to complete matching. (excluding network upload & download overheads bottleneck)
For Even Faster Results, Experience the Power of On-Premises Solutions:
On your Apple Silicon Mac, you can experience the blazing-fast speed of just 3.6 seconds for the same dataset-over thousands times faster than traditional CPU solutions! If you have a high-performance GPUs on severs, you can still complete the same task in as little as about 3.7-3.8 seconds. klastroTest is optimized for both cutting-edge Apple Silicon and NVIDIA GPUs, ensuring researchers, analysts, and developers can achieves results in record time with unmatched reliability.*
*This product is independent from and not affiliated with, endorsed by, or sponsored by Apple Inc. or NVIDIA Corporation. Benchmark results are based on internal tests conducted under standard conditions and may vary depending on hardware and software configurations.
Missing Confounders? Not a Problem
PSM relies on observed variables to estimate the propensity score, which represents the probability of an individual receiving a treatment. If crucial confounding variables are missing from the dataset, the propensity score will be inaccurate, leading to imperfect matching and biased treatment effect estimates.
In contrast, klastroTest ensures comprehensive matching without missing confounders, delivering more reliable treatment effect estimates.
Optimized for High-Dimensional Data Matching
As the number of variables increases, accurately estimating the propensity score becomes more complex. In high-dimensional data, the “curse of dimensionality” can hinder PSM’s ability to effectively match individuals, potentially increasing bias and reducing the efficiency of the analysis.
Howerver, klastroTest handles high-dimensional data with ease, avoiding the pitfalls of traditional methods.
Adaptable Matching Without Linear Assumptions
Many PSM implementations utilize logistic regression to predict propensity scores. Logistic regression assumes a linear relationship between the variables and the outcome. However, this assumption might not hold true in all cases, leading to inaccurate propensity score estimation and subsequent matching errors.
Unlike traditional methods, klastroTest requires no linear assumptions, ensuring flexibility and accuracy across diverse datasets.
klastroTest is Simpler
klastroTest is conceptually simpler and computationally less demanding than PSM. It doesn’t require complex modeling or estimation procedures, making it easier for researchers to implement. This can reduce the potential for errors and biases that can arise during the propensity score estimation process in PSM.
klastroTest is not Deep Learning
klastroTest does not require large-scale data training processes and delivers accurate results without the need for pre-existing training data. Unlike deep learning, it eliminates the need for data acquisition and preprocessing, saving both time and cost. Additionally, klastroTest provides more precise matching by analyzing multidimensional data, surpassing simple Euclidean distance or Cosine Similarity-based methods. This enables it to operate effectively even in high-dimensional data environments, delivering both accuracy and efficiency.

klastroTest
Get Your Perfect Control and Treatment Groups
Effectively Handles Multi-Dimensional Data
PSM primarily relies on a single propensity score, which may not fully reflect the nuances of multi-dimensional medical data. klastroTest accounts for correlations between variables when calculating distances. This allows for more accurate matching in multi-dimensional data by capturing the complex relationships between variables, such as patient demographics, comorbidities, and lab results.
Superior Covariate Balance
klastroTest effectively balances multiple covariates simultaneously. In contrast, PSM relies on a single propensity score, which may not guarantee balance for individual covariates. By achieving better covariate balance between treatment and control groups, klastroTest can further reduce selection bias and improve the accuracy of treatment effect estimation.
Facilitates Subgroup Analysis
klastroTest is particularly useful for analyzing specific patient subgroups. For instance, when investigating treatment effects in patients with severe disease, researchers can utilize klastroTest to identify and compare similar patients based on relevant characteristics. PSM, which focuses on the overall propensity score distribution, may not be ideal for such targeted analyses.
Automated ATE Calculation for Fast and Accurate Clinical Data Analysis
klastroTest automatically calculates the Average Treatment Effect (ATE), a key metric in clinical research, simplifying complex data analysis and providing rapid results. Traditional ATE calculation requires extensive manual work, including variable setup, complex algorithm application, and error checking. klastroTest automates this entire process, enabling researchers to perform faster and more accurate analyses.
As soon as matching is complete and treatment information is available, klastroTest calculates the ATE instantly, delivering results on the spot.
This feature saves researchers time and effort, providing reliable insights with remarkable speed.
🚀 KlastroTest Personal, Premium, and Enterprise Licensing – Scalable, Secure, and Optimized for Your Business
KlastroTest is designed to empower businesses with high-performance data analysis and A/B testing, delivering results in record time. Whether you’re a startup looking for cutting-edge analytics, a growing enterprise optimizing team workflows, or a large-scale organization requiring unlimited access, our flexible licensing model ensures the right fit for your needs.
License Type | Good For | Monthly Rate (EURO) | Monthly Rate (CAD) | Monthly Rate (USD) |
Personal | Individual users | €12.00 | CA$20.00 | $14.99 |
Premium (Startup) – 1 Person | Early-stage startups, small-scale operations | €90.00 | CA$140.00 | $99.99 |
Enterprise – 5 Member Team | Growing businesses, medium-sized enterprises, research groups | €230.00 | CA$380.00 | $265.00 |
Enterprise – Unlimited Members* | Large corporations, financial institutions, enterprise-level deployments | €480.00 | CA$750.00 | $530.00 |
Enterprise – Unlimited Members version will be shipped with the CUDA version along with the Apple Silicon version.
Premium and Enterprise – 5 Member Team versions come with the Apple Silicon Version only.
*This license permits an unlimited number of users within the same legal entity or local branch (e.g., one office, one business unit, or one registered company). It is ideal for enterprise teams, financial institutions, or large organizations that require broad internal access.This license does not cover multiple branches, global offices, subsidiaries, or affiliated companies. For global-scale or group-wide deployment, please contact us for Enterprise Global licensing options.
🚀 Experience the record-breaking speed of your laptop now!
KlastroTest harnesses the power of Apple Silicon to deliver unprecedented data analysis performance.
📌 KlastroTest Premium or Enterprise – Try Before You Buy
🔹 Experience full performance for 7 days, risk-free!
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Reg. No.: 373-81-03700
Representative: Yongwoo Jeong, CEO.
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