AI that optimizes LLM applications by tuning prompts and models
AI-powered LLMOps for developers
From development to production across data management, evals & fine-tuning.
Log all your LLM calls to compare and find the best prompts, store feedback, collect latency & usage metrics. Perform analytics & compliance monitoring of LLM apps
Integrate Log10's GitHub app into your CI/CD workflow to continuously monitor the health of your LLM apps. Get notified when anomalies are detected. Option to run locally via cli
Optimize your LLM app via a rich debugger, automatic evaluations, and AI-powered tuning of prompts and models
Easy programmatic integration
Just call log10(openai) and use the OpenAI client library as before
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from log10.load import log10
import openai
log10(openai)
completion = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[
{
"role": "system",
"content": "You are the most knowledgable Star Wars guru on the planet"
},
{
"role": "user",
"content": "Write the time period of all the Star Wars movies and spinoffs?"
}
]
)
Debug, compare and improve prompts & models
Build LLM-powered apps 10x faster and more reliably with Log10
We're passionate about AI and are committed to its safe, reliable & productive use
CEO & Co-founder
Arjun's career spans research in brain-machine interfaces, building AI processors and AI sidekicks. He previously co-founded Nervana Systems (acq. Intel for $408M) and XOKind (an AI travel agent startup). He was a VP for AI Software & Research at Intel where he launched and led several open source AI projects and enterprise engagements.
CTO & Co-founder
Nik was most recently Head of Product at MosaicML (acq. Databricks for $1.3B). Prior to that he worked at Intel and Mesosphere on building Distributed Systems, and at Adobe on the Virtual Machines and Compilers team. He co-founded CustomerDB, a startup applying AI to product management.