Hey everyone! I'm Haseeb, a full-stack developer from India.
I recently built Pulseboard, an AI-powered uptime monitoring platform for developers, startups, and small teams. It monitors websites and APIs, sends instant email alerts, provides public status pages, and includes Vigil, an AI assistant that helps explain why an incident happened instead of just telling you something is down.
I started building Pulseboard because I felt existing monitoring tools often stop at "your site is down." During incidents, I always wanted more context without jumping between dashboards and logs, so I wanted to build something that could actually help developers understand what likely went wrong.
I'm still in the early stages, so the feedback I'd value most is around onboarding, the overall user experience, and whether the AI incident analysis is genuinely useful or just a nice-to-have. If you have a few minutes to try it out, I'd really appreciate your honest thoughts.
Looking forward to connecting with other founders and learning from the community!
SuperBased
Think Wispr Flow-style dictation + AI-powered screen capture in one tool
Comments (5)
Welcome to the community, Haseeb 🙋🏻♂️
Monitoring can really become a pain especially for a developer who is monitoring several digital properties. And I can see how having the alerts explained adds a real value. Curious, is Vigil pulling from logs or is it analyzing patterns from the monitoring data itself?
Hi Olga! Great question—you've touched on one of the core ideas behind Vigil AI. 🎯
Right now, Vigil AI analyzes telemetry patterns from the monitoring data itself, including response times, HTTP status codes, connection failures, latency trends, and other monitoring signals to understand what is happening during an incident.
One design principle that's really important to me is what I call the Zero-Hallucination Guardrail. Vigil is intentionally constrained to the telemetry and evidence available during an incident. If the data points to a network timeout, it won't invent a database failure or another unsupported explanation. If there isn't enough evidence to determine a likely cause with confidence, it clearly communicates that instead of guessing.
The goal is to help developers move from "something is broken" to "here's the most likely explanation based on the available evidence, and here's what to investigate next"—without having to piece together raw monitoring signals themselves.
As PulseBoard evolves, I also plan to add deeper integrations with infrastructure and observability tools so Vigil can use even richer context where available.
It sounds like you are very passionate about making it a really good quality product. And that's bold to set the guardrail for Vigil AI to admit if it doesn't know the root cause of the issue. AI hallucinations can often send you down the wrong rabbit hole during an incident. Looking forward to seeing the deeper integrations as they come!
Thank you so much Olga and,
Yes I am very passionate about my platform and recently added AWS and github integrations so our Vigil AI can get more info about the repo or AWS CodeCommit to figure and dive deeper into the logs and specify the error.
Do check it out....
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