Orbiter AI - Detect business issues without staring at a dashboard

@mskpw Hey Steven - the accuracy of alerting is really important to us and is something we work closely with our customers on. for each metric, we build a custom ML model that is adjusted to meet your needs (e.g. time to detection, sensitivity, etc.). happy to chat about it more! feel free to DM me at winston[at]getorbiter.com :)

@zhangwins yea I feel like accuracy is a huge pain point for me. If you can do it, then I'm all in haha! Super interested to hear more, I just sent you an email!

@keegan_huang That's right! part our long term vision is to enable teams to be more efficient so they can go more on offense.

@sumanyu_sharma thanks! Excited to hear this your thoughts and feedback on this as it sounds like you’ve thought about this place problem space! Our signal to noise ratio is one of our highest priorities, so I’m happy to chat more on that if you’d like! Please send us an email and we’ll get you set up :)

@markstevenwai Sentttttt

@kennahasson Thanks Kenna!

@matthew_liem awesome questions, appreciate it! Currently we support streaming data into analytics databases in Postgres, where some of customers actually get data posted every minute! We currently do not have connections to Kafka or NoSQL implementations but we're always interested to get more users onboard! Please send us an email and I'd love to chat more about your specific implementation.

@matthew_liem in terms of computing metrics from different sources, we support this! That's our main benefit of staying platform/database agnostic to enable really interesting joins across multiple databases. For example, if you had revenue in one db, and geographic order data in another, you could get automated monitoring and alerting for your revenue by region!

@grisha_gevorkyan Thanks Grisha! That was exactly our motivation for building Orbiter. Having to track pages and pages and pages of dashboards is so time-consuming in today's fast moving world.

@jakemor Thanks Jake! We're actually so pumped to solve this problem since we experienced it first-hand. Hard to imagine a world 5 years from now where metrics and dashboards aren't fully autonomous, monitoring themselves, and letting the user know when there's an insight (good, or bad)

@markstevenwai @zhangwins @liveink Origin stories eh, where do I begin 😂Mark and I worked at Tesla's on the growth team from pre-Model 3 days till the Cybertruck unveiling. The pain of not knowing what was broken at any given time was a huge pain. Tesla moved incredibly fast - there were dozens of features being shipped each week, new sales updates being launched and tweaked, and changes to plans across all parts of the org. That meant your features might be accidentally impacted when another team ships code, launches a new email campaign, tweaks the website, ... the list goes on. Elon is also just really good at finding out what's broken via Twitter. Add the two together, and you can imagine the kinds of fires that break out when you see that Elon email rolling through before anyone had caught a graph trend dipping. Winston also has similar stories from Doordash too - it's what happens when you have growing companies that are trying to push the bounds on responsiveness and attention to customers.

@markstevenwai @zhangwins @victor_zhang1 Thank you! This line is amazing "Elon is also just really good at finding out what's broken via Twitter."

@bbbunit hey! We support the following databases so far: Postgres, Mysql, MSSql, MariaDB, and Redshift. We're currently working on Bigquery, and Snowflake! What dbs do you use?

@bbbunit @victor_zhang1 What's the ETA on BQ?

@bbbunit @victor_zhang1 @sumanyu_sharma awesome to hear! BQ support is currently in testing, so sign up for access through our site and I’d love to get your feedback!

@emily_nhan we're here to help! Happy to hear more feedback specific to the monitoring problems you're facing!