ELU
Your analytics show drop-offs. ELU shows why and fixes it.
Details
- Categories
- AIDeveloper ToolsAnalytics & Monitoring
- Target Audience
- Product ManagersDevelopersStartups
- Platforms
- Web
About ELU
ELU helps teams go from user analytics to shipped product improvements in minutes instead of weeks. Today, teams spend weeks logging the right events, building dashboards, forming hypotheses, and eventually shipping a fix. While losing users the entire time. ELU connects to your analytics, database, and codebase, watches how users interact with your product, and finds the friction points they'd never catch on their own. It's like having a data analyst, a PM, and an engineer working together continuously to improve your product.
Product Insights
ELU integrates with analytics, databases, and codebases to automate the process of identifying and fixing user friction points on web platforms. It streamlines the transition from data insight to implementation for product improvements.
- Connects directly to existing analytics, databases, and codebases.
- Automates workflow from data analysis to shipping product fixes.
- Provides continuous cross-functional support across PM and engineering roles.
- Supports web platform monitoring and friction point discovery.
Ideal for: Startups, Product Managers, and Developers who need to convert user analytics into shipped product improvements rapidly.
Screenshots
Product Updates (1)
Looking for one founder to go deep with
We've been working with design partners and the lesson is clear: depth beats breadth. Best results came when we went all-in on one product with real users and real friction. So we're looking for one founder. Free access, direct line to the team. You have real users. You set up PostHog or HotJar thinking it'd give you answers. Instead you got more dashboards and session replays to sift through. Users are dropping off and you still don't know why. Or you vibe-coded your app, users are showing up, and you're flying completely blind. Either way, the only requirement is having real users. DM me or drop a comment.
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Comments (2)
Really like the framing here. Curious how deep the DB integration goes. Do you correlate slow query patterns with where users drop off? That link between database perf and user behavior is usually where the real root causes are hiding.
We built ELU because we kept losing users and couldn't figure out why fast enough. Dashboards showed the drop-off. They never showed the fix. So we built the tool that does both.