We built a fascinating platform, https://iko.ai, that allows you to train, track, package, deploy, and monitor machine learning models with real-time collaborative notebooks on your own Kubernetes clusters. Source: almost 2 years ago

Hi, Edwin. I'm in the process of integrating Stripe to https://iko.ai. I recently discovered Portal (https://stripe.com/docs/billing/subscriptions/integrating-customer-portal) and I thank you for that. Less code for me. I'm a bit ashamed to say, but I'm having trouble with checking if the customer has a valid subscription. I'm currently only storing the customer_id in the database and retrieving the information... - Source: Hacker News / about 2 years ago

That was one the reasons we do "bring your own compute" with https://iko.ai so people who already have a billing account on AWS, GCP, Azure, DigitalOcean, can just get the config for their Kubernetes clusters and link them to iko.ai and their machine learning workloads will run on whichever cluster they select. If you get a good deal from one cloud provider, you can get started quickly. It's useful even for... - Source: Hacker News / about 2 years ago

We built an internal platform to streamline this that allows us to train, package, deploy, and monitor models (very shameless plug for our product https://iko.ai that we started because I was tired of watching colleagues look from the window to see if their train was here because they had to come to the office to train their model on the "powerful machine" and they spent 6 hours in commute every day and at some... Source: about 2 years ago

We built https://iko.ai which offers real-time collaborative notebooks to train, track, package, deploy, and monitor machine learning models. Source: over 2 years ago

IMO the better paradigm is coming from enterprise applications like Anaplan. Cells are not the right abstraction to work with numbers. Most of the time you work with multi-dimensional quantities (eg revenue by product, geography, month). We’re working on a more approachable implementation of that paradigm at https://causal.app. - Source: Hacker News / 15 days ago

We're using Hypertune at https://causal.app for a few months now and it's been great! We have a few feature flags in there but also some more complex typed data for our onboarding modals. - Source: Hacker News / about 1 year ago

Congrats on the launch! We've been using Hypertune at Causal (https://causal.app) for the last few months and it's saved tonnes of engineering cycles letting me and our PM iterate directly on custom onboarding copy for different Causal templates, alongside more typical feature flag use-cases :). - Source: Hacker News / about 1 year ago

If you're particularly keen go onto some of the prep courses there are out there. wall street prep is one, there are other PE prep courses hawked on here for as little as 10 bucks. All are built around excel skills and learning DCFs. I recommend causal.app if you want to try to skip some of this and get forced into a tool. Source: about 1 year ago

Hi HN, I'm the founder of https://causal.app and the author of this post — Most of the finance content online is very textbook-y and overkill for early stage cos, so wanted this to be a 'no-nonsense' guide for founders/ops people that have to juggle a bit of finance stuff alongside everything else. We've helped lots of startups across different stages with finance stuff over the last few years through Causal, so... - Source: Hacker News / over 1 year ago