In 2025, managing subscriptions isn't just about tracking payments, it's about understanding your habits and making smarter financial decisions.
Subsavio isn't your typical subscription tracker. It goes beyond basic monitoring by analyzing your usage patterns, identifying underutilized services, and providing actionable insights to help you decide which subscriptions are truly worth keeping.
One pattern I keep seeing is that logging starts out useful, then gradually becomes inconsistent, noisy, expensive, and harder to trust. Field names drift, context goes missing, dashboards get polluted, and sometimes sensitive data ends up in places it never should have reached.
The deeper problem seems to be that most teams try to fix logging after the data has already entered downstream tools. By then, the cost, risk, and cleanup burden are already there.
I m curious how other teams handle this. What breaks first in practice: naming consistency, missing required context, sensitive fields in logs, alert noise, or ingestion cost? I m building in this area and want to learn where current approaches still fall short.
I ve been working on a new macOS app called Daydreamer.
It started from a very simple feeling: during busy workdays, I often forget to pause. Not in a dramatic burnout way, just in the quiet I ve been staring at the screen for too long way.
Most break reminder apps I tried felt too cold or too mechanical. They reminded me to stop, but they didn t make me want to stop.
If you're building anything in real estate, proptech, or lending -- this might save you months of work.
We just open-sourced our MCP (Model Context Protocol) server that connects AI agents like Claude, Cursor, or any MCP-compatible tool to ReadyPermit's property intelligence API.
What it does:
- Any AI agent can now look up zoning, flood risk, permit requirements, setbacks, and buildability for any US address
I'm building Comparoute because I noticed something frustrating when working with truck routing APIs: the same origin-destination pair gives you wildly different results depending on which provider you use.
The problem:
If you're building logistics software or managing a fleet, you're probably locked into one routing provider. But Trimble (PcMiler), HERE Maps, and TomTom can differ by 20-50 miles on a cross-country route and those
differences compound into real money (fuel, tolls, driver hours).
Every tool your agency uses knows only its own slice of work. Slack sees messages. Asana sees tasks. Notion sees docs. None of them talk to each other and you pay the switching tax every single day.
We built Kobin to replace all four in one tab: inbox, tasks, vault, CRM, and a client portal all connected and sharing the same data.
The part we're most proud of is the AI layer. It's not a chatbot bolted on top. It reads your live tasks, messages, CRM pipeline, and files before it does anything. Type @AI turn this into a task and it checks team workload, fuzzy-matches relevant files from your vault, assigns the right person, and creates the task all in one call. No prompt engineering. No copy-pasting between tools.
Early founding plan is $49/month for 5 seats. The average agency we've talked to was spending $283/month across their fragmented stack.
We re nextX AG. We ve been building AI infrastructure for environments where reproducibility and auditability matter as much as raw capability: regulated workflows, on prem / private cloud, and air gapped deployments.
Today we re packaging everything under one umbrella: AQEA Engine.
I ve spent the last few weeks obsessed with one goal: making a React-based site that doesn't feel "heavy". We all know that React can be a beast when it comes to mobile performance, so I decided to push it to the absolute limit.
I m happy to share that my portfolio project, WebDev Compass, finally hit a stable 100/100 on Desktop and 95+ on Mobile.
