Deepchecks Monitoring takes the open source testing experience all the way to production: enabling you to send data over time, explore system status and receive alerts on problems that arise over time.

Continuously validate LLM-based applications including LLM hallucinations, performance metrics, and potential pitfalls throughout the entire lifecycle from pre-deployment and internal experimentation to production.🚀

Thanks @kevin for hunting our LLM Evaluation solution 😊 👋 Hey, ProductHunt community I am Shir, co-founder and CTO of Deepchecks. At Deepchecks, we’ve built a pretty special solution for LLM Evaluation and are thrilled to launch it today on ProductHunt! When we launched our open-source testing package last year, we quickly received an overwhelming response with over 3K stars 🌟 and more than 900K downloads! After the launch of our NLP package in June, we noticed that an incredible amount of the feedback calls we were having about the NLP package were asking for help with evaluating LLM-based apps. 🤯 After creating an initial POC and getting feedback from various companies, we gained the confidence we needed to dive deeply into the LLM Evaluation space. And yes, turns out it’s a pretty big deal. 🚀 As we began working on the LLM Evaluation module, we’ve arrived at some important learnings that teams are struggling to figure out answers to these questions while deploying their LLM apps: - Is it good? 👍 (accuracy, relevance, usefulness, grounded in context, etc.) - Is it not problematic? 👎 (bias, toxicity, PII leakage, straying from company policy, etc.) - Evaluating and comparing versions (that differ in their prompts, basemodels, or any other change in the pipeline) - Efficiently building a process for automatically estimating the quality of the LLM interactions and annotating them - Deployment lifecycle management from experimentations/development, staging/beta testing, to production. Deepchecks LLM Evaluation solution helps with- ✅ Simply and clearly assess "How good is your LLM application?" 🔀 Track and compare different combinations of prompts, models, and code. 🔍 Gain direct visibility into the functioning of your LLM-based application. ⚠️ Reduce the risk during the deployment of LLM-based applications. 🏛 Simplify compliance with AI-related policies and regulations. We're also hosting a launch event today at 8.30 AM PST today, feel free to sign up to interact with the Deepchecks team and see a live demo: https://www.linkedin.com/events/... Apply for Deepcheks LLM evaluation access: https://deepchecks.com/solutions... 😊 Would appreciate any questions, and hope to see you there!

Congrats on your launch 🚀 great stuff!

@shirch Congratulations on the launch team, best of luck today ♥️🦄

@hay_day3 thanks my friend!

Excited for the launch! 🎉

@asdivyansh Such a pleasure to have you with us on this journey

@asdivyansh yup it’s a big deal ❤️

I've been loving every release from this team. Can't wait to try this one out.

@on thanks so much! Looking forward to hear your thoughts :)

@on can’t wait for the feedback!

I like the approach. Easy to use and democratizing our dev world.

Deepchecks is one of the coolest MLOps tools on the market. Period. I've struggled a lot with monitoring, and this tool hits all the major pain points. Kudos!

I like the approach. Easy to use and democratizing our dev world.

Deepchecks is one of the coolest MLOps tools on the market. Period. I've struggled a lot with monitoring, and this tool hits all the major pain points. Kudos!

Deepchecks Monitoring

Open Source Monitoring for AI & ML

Open Source Monitoring for AI & ML

Deepchecks Monitoring

Open Source Monitoring for AI & ML

Open Source Monitoring for AI & ML

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