Launching today
Ami AI
Lovable for getting customers
520 followers
Lovable for getting customers
520 followers
Most outbound dies on one decision: who to write to this week. Ami has already made it 17,707 times and kept score. Built on GPT-6 Astra and every one of those campaigns, it reads your website, picks the buyers who actually convert, and plans backwards from the number you need: leads, senders, weeks. If the list you asked for won't work, it says so before it builds anything. Approve the plan and it runs the outreach, watches every campaign, and fixes what slips. 19,854 booked meetings behind it.
@yuriy_zaremba I love that it suggests fixes while the campaign is running instead of waiting for a depressing post-mortem, such a nice way to so solving congrats for launch team🙌
@vikramp7470, thank you! Yes. This is key. It checks performance weekly and suggests to make adjustments to make sure campaign works
@tehreem_fatima5, all the greatest changes are ahead
@yuriy_zaremba Congrats on the launch! The positioning is sweet! Also, I like the adaptive behaviour of Ami, using Astra makes sense!
@dimneo, thank you! Astra made all the difference in terms of performance
Looks promising! Congrats on launch! What tools do you offer to control the quality of leads brought with your outreach? I see stats as Total response rate and Positive response rate, can you elaborate?
@liya_bondarenko thanks! We usually measure success against Positive reply rate and Meetings booked count, as well as Influenced pipeline. With outreach it can easily turn into an associated conversion story - someone clicks the outreach and then comes back in a month directly, so influenced pipeline is a good way to track the impact, especially with products that have long decision-making cycles
@liya_bondarenko, there are 3 filters: (1) lead list creation - it's agentic, not based on filters, so the goal is to discover people, who have a pain you can solve, not just a random list; (2) the messaging profile - you configure (with Ami) what is the offer and whether AI should qualify incoming leads, (3) iteration - as positive replies start coming in - you can fine tune both messaging and lead list to make sure you're getting qualified leads.
On the metrics side - response rate is everyone who responded, including saying "no/unsubscribe, etc.", while positive response is "yes, let's talk".
We also track pipeline influenced and $$$ closed won, because we are so focused on results
How does Ami know that the list I asked for won't work. Where is her judgment coming from?
@maryna_synychenko, great question. Ami is trained on almost 18k campaigns we've run over 3 years AND on top of it scans what's latest and greatest in GTM every week, so it has experience and acts as an expert which is why it can push back on bad ideas
Hey team! One thing that drives me crazy with AI is how agreeable it is. I can give it a pretty questionable idea and it’ll still find a way to tell me it’s great 😂
Can Ami actually tell me when I’m onto something bad?
@new_user_112af36f66, yeah. It's very non-agreeable. It focuses only on things that it knows will work. We specifically trained it to be like that, because many customers that we've worked with - were doing what they felt was right and failing
Back in 2023 when all the AI SDR hype started, this is the tool everyone was hoping to see. Nearly 1 in 2 people on a sales demo I ran asked for recommendations on how they should run outreach, or tips, or what specifically not to do. Now with Ami we do have the tool people have been requesting all along because it has the knowledge of thousands of campaigns, and that's my favorite part because I can be a stupid human with subjective judgement knowing the AI has my back and won't let me launch the campaign that will cause more damage than good.
@alina_karnaukh, true. People didn't know where to start and they still don't. I am glad we built Ami and I hope it will change this trend and will help founders be more successful with sales and focus on building
Here's a little story from one of the Ami makers:
my part started on customer calls, figuring out “what do we try next?” manually. we’d talk through the audience, rethink the angle, pick something to test. then do it all again on the next call. while we’re still talking about what ai might eventually take off our plates, I’m watching ami take on work i know very well.
and what i like most is the confidence behind its recommendations. I do trust them because I recognize the real campaigns, tests, and customer situations that helped shape them + can ask why it’s suggesting something and assess the reasoning. I wouldn’t romanticize all the manual testing, but seeing those lessons become useful to customers through ami makes it feel worth it
@tetiana_khanas, so true. We did the classic start up thing here. We had people do the job until we collected enough experience and data to have AI do it equally well or better. So grateful to be building Ami with you