Anthony Alaribe
APItoolkit: Using Merkle Trees and LLMs to Detect the UnDetectable in Software Monitoring
#1about 1 minute
The high cost of undetected breaking changes
A real-world example from Delivery Hero shows how a minor migration error with missing fields resulted in a $2 million loss.
#2about 1 minute
Why incident response is slowed by information overload
When systems break, teams are swamped with too many logs, metrics, and messages, making it difficult for humans to diagnose the root cause quickly.
#3about 1 minute
Using Merkle trees and LLMs to detect anomalies
Merkle trees condense millions of logs into unique signatures to identify new patterns, while LLMs analyze these changes to determine if they are critical or breaking.
#4about 1 minute
An observability platform with conversational AI
APIToolkit is an observability platform that analyzes requests, logs, and traces in real-time to provide context and allow conversational debugging.
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