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We started with prospect research, writing outreach, and handling replies. But I kept joining customer calls to help answer more basic questions: Who should we target? What should we offer? Why would someone care right now? What should we change when nobody responds?
I once paid an outbound agency $30,000 and got zero meetings in six months.
When we built AiSDR, I learned how easy it is to automate the emails while leaving the hardest decisions to the customer: who to contact, why now, and what to offer.
I liked the idea behind Ami AI, especially how quickly it tries to connect a product with a specific company and generate a relevant outreach angle.
I tried it with my product, FeelEase, and noticed one issue with how it interpreted the product before generating the message. It picked up some surface-level features correctly, like emotional check-ins, creative reflection, and local data storage, but missed the core positioning and differentiation.
FeelEase is more about giving people different ways to process emotions when they may not be ready to talk to someone through writing, drawing, metaphorical cards, and self- or AI guided reflection, notice the patterns over time.
Because that context was missed, the outreach felt quite generic and positioned FeelEase almost like a feature layer for digital health products.
A few things that might help in cases like this:
a short “This is how I understand your product” summary before generating outreach, with an option to adjust it;
a short “Why I think this company is relevant” explanation, so the user can see what connection Ami found;
maybe 2–3 possible outreach angles before generating the final message, so the user can choose the one that feels most relevant;
if Ami is unsure about the business model, something like “I understand FeelEase as a standalone consumer product is that correct?” could prevent the positioning from going in the wrong direction.
@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
@yuriy_zaremba Congrats on the launch! The positioning is sweet! Also, I like the adaptive behaviour of Ami, using Astra makes sense!
@yuriy_zaremba nice launch... the idea of the testing campaign ideas against the real promotion data is the interesting, and also the audience targeting part caught my attentions.
how quickly does it the usually detect that somethings is wrong???
@vipul_kumar1280, 2 weeks is the first check and 3 weeks is the final decision. Needs some volume to make a good decision
@yuriy_zaremba This is great,Excited to see how it works!
@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
Hi guys!
the product looks very interesting (and to be covering the biggest gap almost every "I am building Xxx" product has)!
I am not sure I understand where the contact data are coming from and if from my side, how do you handle any data from my side? If it is from the model seed, how do you handle quality of the contacts?
Looks awesome!
@foobar_beer thanks Jakub! The data is coming from a waterfall of over a dozen data vendors we work with including public web data scraping for live signals. We also triple-verify every contact for potential bounces, which is how we achieve a system-wide bounce rate <1%
@alina_karnaukh Hi Alina, thanks for the answer - so can those contacts be added to my list as (ideally double) opt-in contacts?
@foobar_beer, we have multiple vendors under the hood, including live scraping and 2 bounce providers. Data is the best you can get in the market. We've iterated on the setup for 3 years
@yuriy_zaremba Thanks for the update!
@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
@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
Congrats on the launch. I’m very interested to try it out because I’ve trialed a few outreach platforms lately and haven’t had much success. I put that down to the fact that I know very little about it, so I really like the built-in fix/recommendation feature. If it sends emails, how does it warm up the list? One thing I’ve learnt is about low réponses rates from cold outreach.
@you_x_you_i, list is warmer, because Ami always suggest a lead list that starts with a pain signal (new pricing page/new hire/M&A) or a social signal (post likes, profile views) and so people are already "aware of the problem" and are more likely to respond. On top of that we take care of all the infrastructure issues on email deliverability and LinkedIn side



Hello Eugenia! Thank you for such detailed feedback.
This was part of our latest update, and we’ll definitely keep iterating on the deep research and campaign creation flows to make them more user-friendly. You’ve raised some really valuable points. Thank you!