We build reliable knowledge graphs 📈
Small Data. Big Outcomes.
Gain new insights from fresh perspectives. Ride the wave of AI innovation and elevate your company's analytics securely to new heights.
Core Features of Our Graph-Based Analytics
We provide professionals with a powerful AI-focused, graph-based modeling environment to extract highly detailed and specific insights from complex data.
Automatic Cleaning and Preprocessing
Save time, stay Correct.
Multimodal Data Handling
Regardless of your data's medium, we've got you covered.
Catalogue Data for Future Predictive Modeling
Give you a leg up in predictive tasks via structured categorization.
Reliability Guarantees for Data Representation
Data decisions have impacts - our metrics evaluate the trustworthiness of your data's ability to address your end goal.
Interactive RAG Interface
Converse with your data.
Visualization Suite and Report Generation
Seeing is believing, communicate effectively through visualizations.
Dynamic Processing via Reliability Metrics
Krv Analytics empowers businesses to harness the power of their data. Our solutions simplify high-dimensional, sparse datasets, enabling domain experts to see into the black box of machine learning.
Sensitivity Analysis for Preprocessing
Reliability metrics reveal how changes in data preprocessing impact machine learning outcomes. By quantifying sensitivity, they help users identify preprocessing choices that lead to consistent, trustworthy results.
Ensuring Robust Decision-Making
With reliability metrics, businesses can assess whether their data can reliably answer critical questions. If ML results drastically change due to preprocessing, these metrics guide users toward identifying the most dependable configurations.
Stear Clear Of
Analysis Paralysis
Beyond graph advantages — like uncovering hidden patterns, enabling non-technical insights, and making data searchable — we keep pace with new methods while shielding users from choice overload.
LLMs Have Limits
LLMs, RAG, and predictive ML tools are transforming industries, but they struggle with small, niche, sparse, high-dimensional, and noisy datasets — typical of real-world data, especially for smaller organizations. Industry professionals can't get quality analytics by simply uploading a local CSV to ChatGPT.
With Krv, now they can. Tabular knowledge graphs bring the accessibility, sophistication, and interpretability of LLMs and RAG to high dimensional, sparse datasets.
Effortless, Sophisticated, and Reliable Data Preprocessing and Exploration for SME's
Unlike traditional solutions that require deep technical expertise or large data teams, our tool empowers SMEs to use cutting-edge machine learning techniques with minimal setup.
No PhD in Data Science Required.
The Curse of Dimensionality is Knocking at our Door
Effective data cleaning, preprocessing, and representation are crucial for extracting insights, especially with small, industry-specific datasets. While research offers many methods, not everyone has the expertise to navigate them. With so many options, making reliable choices is a challenge — even for data scientists.
Our tools automate the machine-learning data handling for you. Save time and understand the trustworthiness of your data's ability to address your end goal.
Graphs make complex data relationships easy to understand and explore. They let you connect the dots—literally—between different pieces of information, uncovering patterns and insights that might otherwise go unnoticed. With our tool, you don't need a background in machine learning or technical expertise. Just upload your tabular data (like a CSV file), and we'll turn it into a visual knowledge base. From there, you can explore connections, run optimized searches, and quickly link your documents to your data, helping you make smarter decisions without the heavy lifting.