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Excellent tool for ML Monitoring with many out-of-the box solutions
What do you like best about the product?
Great to collaborate with; very responsive; really appreciate their OHs to help out with issues that pop up; many out-of-the-box solutions for different kinds of ML models which really helped us out given the wide variety of ML models we run at the company.
What do you dislike about the product?
Nothing major to mention! We got everything resolved and the team was very helpful.
What problems is the product solving and how is that benefiting you?
Data Drift and ML Monitoring
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Developed efficient solutions for optimizing ERP workflows through data analysis
What do you like best about the product?
One of the standout features of WhyLabs is its robust data observability capabilities. It provides continuous monitoring of data pipelines and ML models, allowing teams to quickly identify issues like data drift, model degradation, and training-serving skew. The platform's privacy-preserving integration ensures that data can be analyzed without moving or duplicating it, which is critical for maintaining security and privacy in sensitive industries like healthcare and finance
What do you dislike about the product?
One potential drawback of WhyLabs is its relatively limited user reviews and feedback due to its newness in the market, making it harder for potential users to gauge its real-world performance at scale. This lack of detailed reviews can raise concerns about its maturity and support infrastructure.Additionally, since it’s a newer platform, some advanced features might still be in development, and there could be steep learning curves for teams unfamiliar with observability tools in machine learning.
What problems is the product solving and how is that benefiting you?
Data quality issues: It helps detect and address data drift and data integrity problems early, which is crucial for maintaining accurate and reliable ML models
Reliable AI Monitoring with Some Complexity
What do you like best about the product?
I like the privacy preserving solutions for scaling AI models. I like that WhyLabs offer responsive support and detailed documentation.
What do you dislike about the product?
I dislike that the platform might be overly technical for users who are not well-versed in AI or data science
What problems is the product solving and how is that benefiting you?
WhyLabs helps me solve issues like data drift and performance degradation in my AI models. This is crucial because I am working with sensitive medical data.
Self-Serve Observability Platform
What do you like best about the product?
WhyLabs is the second observability platform I have ever used, and I can say the core features I like about the platform is that it is easy to set up and implement the features, the checks and metrics were already pre-loaded so I did not need to do much in configuring the application, and monitoring was not difficult to get started with. It also integrates well with the serving and data libraries we used for the production tutorial setup.
What do you dislike about the product?
Nothing so far, I only experienced a stability issues once (sometime in 2022), but support was able to help me quickly fix it.
What problems is the product solving and how is that benefiting you?
Since 2022, I have sparesely used WhyLabs to monitor the quality of datasets for one client and 2 customers (because it was not their core requirment but a nice piece of their stack to have).
whylogs seemed like the perfect choice for a consultant that clients did not want to entirely release their data to; I found that it only captures the profile and stats info instead of the raw data here.
Rcently, I started testing out LLM security features with LangKit and I cannot believe how quick it is to use. I followed a workshop few months ago that showed me how to detect jailbreak attempts and toxicity in LLM inputs and outputs using LangKit. Took that learning and now with a client's project, we have tested out logging the telemetary data from the evaluation to WhyLabs. Looks good so far, so once I upgrade the pricing limit for this client, we plan to scale our usage here. Excited about this one.
whylogs seemed like the perfect choice for a consultant that clients did not want to entirely release their data to; I found that it only captures the profile and stats info instead of the raw data here.
Rcently, I started testing out LLM security features with LangKit and I cannot believe how quick it is to use. I followed a workshop few months ago that showed me how to detect jailbreak attempts and toxicity in LLM inputs and outputs using LangKit. Took that learning and now with a client's project, we have tested out logging the telemetary data from the evaluation to WhyLabs. Looks good so far, so once I upgrade the pricing limit for this client, we plan to scale our usage here. Excited about this one.
Monitoring LLMs for succees!
What do you like best about the product?
The team behind WhyLabs is awesome. I like how easy it is to get started with their platform, their commitment to an open-source approach, and their active engagement with the AI community with regular workshops and education around cutting-edge monitoring and evaluation techniques.
What do you dislike about the product?
Having more flexibility in visualizations and easier ways to share them outside the product would be nice.
What problems is the product solving and how is that benefiting you?
I use WhyLabs to help keep a pulse on LLMs by monitoring valuable metrics such as jailbreak scores, sentiment, toxicity, and readability. This has helped me catch problems early and gives me some good metrics to compare when finetuning models or adjusting prompts.
WhyLabs Platform - offering intuitive insights into AI model behavior.
What do you like best about the product?
My experience with the WhyLabs Platform was enlightening, offering intuitive insights into AI model behavior and enhancing my understanding of AI observability. The best part of about the interface is its user friendly interface and comprehensive suite of analytics which provide valuable insights into AI model behavior and which would also enable a dashboard for data monitoring, model features. It also facilitates real time monitoring, ultimately enhancing efficiency of AI development processes. It also gives you the leverage to customise the model features as per the project requirement.
What do you dislike about the product?
Few advanced customisation options for analytics is not available as of now, but as informed it would be available soon as an update in the platform. So that solves the downside down the line.
What problems is the product solving and how is that benefiting you?
The main things which is being helped with is the data observability and monitoring. It could help me to effectively integrate and monitor the behavior of AI models, enabling to detect issues like data drift, model degradation and biases. This in turn helps in mitigating risks and optimizing model performance.
Easy Integration and Outstanding LLM Monitoring with WhyLabs AI Observatory
What do you like best about the product?
The foremost aspect that stood out for us was the ease of integration. It was quite straightforward, almost as same as the sample code to put LangKit into our LLM pipeline and upload it to WhyLabs. The getting-started docs were clear and concise. Even for companies with limited resources like ours, WhyLabs AI Observatory proves to be an accessible and easily adaptable solution.
What do you dislike about the product?
The data visualization tools are highly capable, although there is some learning curve to master it. However, their customer success and support team are responsive, helpful, and have consistently gone above and beyond to ensure that we utilize the platform to its full potential.
What problems is the product solving and how is that benefiting you?
The monitoring capabilities of WhyLabs AI Observatory are the main reason why we use it. We have very limited control of external LLM services. WhyLabs provides alerts and insights into those LLM models, enabling us to identify and address potential issues promptly.
Super powerful and simple
What do you like best about the product?
WhyLabs is so useful for debugging, maintaining, and developing production ML systems. It's portable, highly configurable, and provides unified visibility across a broad range of systems/services in a production ML ecosystem. It dramatically improves ML devops and is incredibly easy to get started. It integrates very easily with all the systems I've used, implementation is a breeze, and there's very low friction to get started. I've caught tons of issues using it.
What do you dislike about the product?
I don't really have any complaints about it, it does its thing incredibly well for my use cases.
What problems is the product solving and how is that benefiting you?
Visibility and observability that is unified across all stages of ML dev and ops: model training, development, deployment, testing, etc. Importantly it integrates with a broad range of systems/languages.
It accelerates development/deployment by provide great visibility.
For ops, it has caught so many super costly issues which everything else misses, especially things related to train/serve skew or semantic drift.
Seriously, it's a must-have for productionizing ML.
It accelerates development/deployment by provide great visibility.
For ops, it has caught so many super costly issues which everything else misses, especially things related to train/serve skew or semantic drift.
Seriously, it's a must-have for productionizing ML.
WhyLabs answers Why
What do you like best about the product?
WhyLabs Al is easy to understand and use. It enhances interpretability, making it easier for data scientists and machine learning engineers to understand model behavior
What do you dislike about the product?
More detailed dashboard would be more helpful
What problems is the product solving and how is that benefiting you?
It enable me monitoring and understanding the interaction between my data and model
Intuitive and user-friendly product.
What do you like best about the product?
I see so much potential how it can be applied to my own academic work. It's very friendly by providing easy-to-read plots and intuitive platform.
What do you dislike about the product?
I found some of the features very slow to display.
What problems is the product solving and how is that benefiting you?
I don't have any specific problem at the moment, but I see potential in using it to conduct a short text analysis as an exploratory method.
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