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Softlaunch is a fast, reliable, real-time feature flag platform for shipping safely and controlling rollouts without redeploys.
Backed by a global CDN, evaluations are low-latency and resilient to network hiccups. Flags live in a real-time database, so changes land everywhere the instant you make them — in your app and on every open dashboard. And because each organization gets its own database, your data stays isolated, scales without limit, and can run on your own infrastructure when you need to.
Every surface is first-class: open-source SDKs for every language you ship in, a scriptable CLI, in-app dev tools, and an interface coding agents can drive. Free forever, with no usage caps.
mbuzz is multi-touch attribution for technical marketers who've stopped trusting their dashboard. Here's the thing nobody selling you attribution wants to say out loud: every tool runs a model under the hood, and the number it reports isn't "the data." It's that model's opinion of the data. Same touchpoints, different model, completely different "best channel."
mbuzz runs eight of them at once. First-touch, last-touch, linear, time-decay, position-based, Markov, Shapley, data-driven. You can compare them, argue with them, and write your own in a SQL-like DSL if none of the stock eight fit how your business actually works.
Softlaunchmbuzz.co's answer:
Every attribution tool runs a model under the hood and reports its number like it came from physics. mbuzz is the only one that shows the model. Eight of them side by side, plus a SQL-like DSL to edit or write your own. You stop arguing about which channel works and start arguing about which model you should trust.
mbuzz.co's answer:
Dreamdata, HockeyStack, and Northbeam all ship with a proprietary "data-driven" model you can't see inside. You pay $1,400–$5,000 a month to trust their math. mbuzz runs eight models you can inspect, lets you edit the logic in a SQL-like DSL, keeps your data exportable on every plan, and starts at $0. For a $1–100M company spending $20K–$1M a month on ads, that's the difference between renting an attribution tool and owning an attribution stack.
mbuzz.co's answer:
Technical marketers, marketing ops, growth engineers, and data-savvy CMOs at startups and mid-market SaaS, DTC, fintech, and healthtech companies spending $20K–$1M a month on paid media. Specifically the ones who've stopped trusting their dashboard — who want to audit the math themselves, not hear "trust our algorithm."
mbuzz.co's answer:
Years of wrestling with the limitations of various existing solutions, platform-inflated ROAS, and enterprise attribution tools that cost more than the budgets they were measuring. Every tool I tried picked one model and hid the math. I wanted to compare models, argue with them, and write my own rules — so I built one. mbuzz is the attribution platform I wished existed when I was trying to explain channel performance to a CFO who didn't believe the Meta pixel.
mbuzz.co's answer:
Ruby on Rails (backend + dashboard), PostgreSQL, Sidekiq for background jobs, Stimulus/Turbo for the frontend. Open-source SDKs in Ruby, Node, Python, and PHP. Deployed via Kamal on DigitalOcean.
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