SQL-Configurable Alerting and Ticketing – Beyond Zapier and Zendesk

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Hey HN Community, I'm excited to share something we have been working on for over the past few months: Locale.ai. Its heart and soul lie in its SQL-configurable nature. You can directly connect Locale to your databases, data warehouse, or any SaaS tool that you use internally and craft custom alerts and ticketing conditions with SQL queries. The issues also get resolved on their own as we can detect them through data. Before starting Locale, we worked across companies and managed tons of cron jobs with email reports, slack alerts for customer success operations and product. It’s a tool born out of our problems of missing issues because of noisy slack channels, faulty cron jobs, airflow and constantly refreshing dashboards. Locale identifies moments that need your attention based on the rules you set, and alerts the right people at the right time. These alerts then become tickets sent across Slack, WhatsApp, Jira or anywhere your team works so that you can track for resolution and enable escalation if not solved. Whether you're in product, operations, sales, marketing, or any other team, Locale adapts to your unique workflows. It's designed to give you the power to define precisely what you want to monitor and how you want to be alerted across multiple channels, as long as you have the data captured for it. Would love to hear your feedback, suggestions, or any cool ideas on the possible use cases for Locale. We're a small team determined to make this tool as user-centric as possible, so your input is invaluable to us. Check it out here https://locale.ai . Looking forward to your thoughts and discussions!

Visit product View on Hacker NewsDec 12, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, user, email · Missing: mac, agents, macos

93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: excited, lua, ide · Missing: https docs, just released, exist

67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

20%20% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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