SaaS Metrics
Product Positioning & Context
Debug and monitor AI agent failures in minutes. Trace every run, catch hallucinations and ungrounded answers that traditional monitoring misses, and see exactly what went wrong. Reduce token waste, improve agent quality, and ship faster with support forNET, Python, and JavaScript.
Related Ecosystem & Alternatives
Discover adjacent products, open-source repositories, and developer tools sharing similar technical architecture.
Deep-Dive FAQs
What is Progress AI Observability?
Progress AI Observability is a digital product or tool described as: Trace, evaluate, and improve AI agents in production
Where did Progress AI Observability originate?
Data for Progress AI Observability was aggregated directly from the Product Hunt community ecosystem, representing raw developer and early-adopter sentiment.
When was Progress AI Observability publicly launched?
The initial public indexing or launch date for Progress AI Observability within our tracked developer communities was recorded on August 7, 2026.
How popular is Progress AI Observability?
Progress AI Observability has achieved measurable traction, logging over 154 traction score and facilitating 15 recorded discussions or engagements.
Which technical categories define Progress AI Observability?
Based on metadata extraction, Progress AI Observability is categorized under topics such as: SaaS, Software Engineering, Artificial Intelligence.
What are some commercial alternatives to Progress AI Observability?
Our semantic intelligence engine identifies potential commercial alternatives in the SaaS space, such as Navige, which offers overlapping value propositions.
How does the creator describe Progress AI Observability?
The original author or development team describes the product as follows: "Debug and monitor AI agent failures in minutes. Trace every run, catch hallucinations and ungrounded answers that traditional monitoring misses, and see exactly what went wrong. Reduce token waste,..."
Community Voice & Feedback
I assume if I want to monitor how Claude Code works, then I have to use Fiddler? (I love Fiddler)
@yochev Congratulations. And happy product launch.
Really like how this makes “successful but wrong” agent runs visible. Tracing the full flow and tying it to evals is a powerful combination.
Hey Product Hunt 👋I’m Lyubo, the Product Manager behind Progress AI Observability. We know a lot of teams are building AI agents now. The first demo comes together quickly but then you try to run it in production and things get more complicated. Traditional monitoring can tell you that an app is running, but it usually can't explain why an agent chose a particular tool, ignored useful context, entered an expensive loop or produced an answer that looked convincing but was wrong. We built Progress AI Observability to give engineering teams that missing visibility. We want to move teams from “something went wrong” to understanding why it happened, what needs to change and whether the next version is actually better. You can start tracing in minutes with support for .NET, Python, and JavaScript/TypeScript. There’s a free plan, and no credit card is required. We'd love to hear your feedback on:What’s hardest to debug once an agent reaches production?Which signals are most useful to you: traces, evaluations, latency, token usage, or cost?What would you need to see before using this with a production agent?Thanks for checking it out 🙏- Lyubo and the Progress AI Observability Team
Discovery Source
Product Hunt Aggregated via automated community intelligence tracking.
Tech Stack Dependencies
No direct open-source NPM package mentions detected in the product documentation.
Media Tractions & Mentions
No mainstream media stories specifically mentioning this product name have been intercepted yet.
Deep Research & Science
No direct peer-reviewed scientific literature matched with this product's architecture.