Catch Suspicious Sessions Before They Become Incidents
The Challenge: Logs Are Noisy. Attackers Are Subtle.
Security teams deal with massive volumes of session activity data, and identifying malicious behavior is often like finding a needle in a haystack.
- Patterns evolve constantly, making static rules brittle
- ML models can flag anomalies, but rarely explain why
- Time-consuming analysis slows down response efforts
What if your team could upload a session log and instantly get a classification—with a plain-English explanation of what's suspicious and why?
The Solution: Intelligent Session Analysis with FoundationaLLM
FoundationaLLM is a platform—not a SaaS tool—that runs securely inside your environment and empowers you to build custom agents capable of integrating with your ML models, databases, and internal systems. These agents are LLM-agnostic and tool-agnostic, meaning you can bring your own models (GPT-4, Claude, open-source, etc.) and define external tools using plain language to fit your specific needs.
FoundationaLLM integrates seamlessly with your fraud detection workflows by combining LLM reasoning with external ML models. The result: a system that doesn't just flag malicious sessions—it explains them.
And because it's built to run with your infrastructure and tools, FoundationaLLM gives you rapid deployment, lower total cost of ownership, and trusted scalability without custom dev work.
How It Works
Input a Session Log – Upload a CSV with user activity.
Classify the Session – FoundationaLLM forwards the log to a pre-trained model to determine if it's normal or malicious.
Embed & Compare – If malicious, a second model encodes the session and compares it to known threats using vector similarity.
Explain & Recommend – The most similar malicious pattern is retrieved, and FoundationaLLM explains the anomaly clearly and contextually.
The Technical Hurdles
and How We Solve Them
Many fraud tools stop at a binary result and provide limited or no context.
FoundationaLLM retrieves similar past threats and reasons through the anomaly in plain English.
Teams struggle to tune and trust black-box ML systems.
Our agent gives explainable, transparent answers that analysts can verify and act on.
Logs live in different formats and locations.
FoundationaLLM works with standard session logs (e.g., CSV) and can integrate into your toolchain using API connectors.
The Business Impact: More Clarity, Less Guesswork
Accelerated Triage – Classify and explain threats in seconds, not hours—improving response time and reducing analyst workload.
Explainable Decisions – Get human-readable reasoning for every detection—building trust in automation and supporting audit readiness.
Higher Precision – Leverage canonical patterns to reduce false positives—lowering investigation costs and improving analyst efficiency.
Enterprise-Grade Control – Fully deployed in your Azure environment for compliance and control—ensuring data governance and speeding time to value.
Why FoundationaLLM?
Connects to your ML classifiers and session encoders
Finds and compares to known malicious patterns using embeddings
Explains anomalies in natural language
Deploys securely inside your Azure environment
Built for the enterprise—from day one
Ready to Catch Fraud Before It Spreads?
Let FoundationaLLM turn session logs into clear security insights—with fast, explainable fraud detection.
From session logs to insight. From anomaly to explanation.
Get in Touch