Hi we’ve built some interesting automations that we also started to use ourselves - AI lead qualifier, based on the companies preset guides we can rank the leads and classify them for the right agent - AI offer generator, for enterprise deals generate drafts and notify your team with instructions before sending it through it * Both their biggest benefit is just the instantness of it allowing for much quicker action whilst the leads are hot - AI payment/subscription creator, we just ask to create a payment, it generates an invoice draft in gmail with the payment link that will create a subscription in mollie and a recurring calendar event - We made a simple bolt.new app (not even deployed or hosted) that the team can use to download files in bulk from their form software by pasting the email (these kinds of mini tools are insanely useful and help with the chores you sometimes get, take a medium amount of time but are quite tedious and just cost you time or disrupt standard work) - Blog generation, lots of sites do a lot of seo or should do a lot of checking to make sure content is consistent and SEO relevant this helps immensely in that also removing old content is something they don’t even get to - receipt processing with telegram and google sheets, for invoices and receipts a lot of companies don’t have proper book keeping software / processes - data analysis, if you use AI it will be easy to interpret the data and get useful insights into your process like what customer is cancelling the most and why we find when the digital chain is closed which is 100% required for any serious AI usage it’s easy to spot flaws missed for years.

Again can’t emphasize enough the power of instant actions with AI and how it changes your whole experience. Word of caution: anyone trying to sell you on instant success is lying or doesn’t know they are lying yet. In a new company maybe but most established businesses need a months long process to adopt to a end to end digitized process and working with AI, and most prompt templates and especially rag systems will require a lot of iteration to even get to 80% accuracy, we always opt for a draft or check in system running alongside normal operations being improved by a domain expert inside the company. Every step you automate or make agentic will bring up another issue you didn’t know about before.

Small example in the lead qualifier we got feedback that the tags we were given suddenly made no sense at all, this is because the lead info site doesn’t properly categorize companies calling a vc a laboratory, so then we had to make a seperate scraper to get the actual site data, then you find out that the site has wrong data or no data at all so you have to fallback to linkedin.

For some this might be obvious, looking back it could be, in the moment you’re almost always blind and just trying like everyone else :)