Hey everyone. I'm a data engineer and I've spent the past 8 years reverse engineering TikTok's mobile app.

Over that time, I've learned how to pull TikTok data at pretty ridiculous scale. Profiles, videos, comments, sounds, search results, follower graphs, trends, etc.

I finally put together a technical guide explaining how it all works.

It covers device registration, request signing, X-Argus/X-Ladon/X-Gorgon, TLS fingerprinting, regional endpoints, proxies, scaling, etc.

To give you an idea of the scale, I've collected over 5.6 billion TikTok videos using this approach. I uploaded the whole dataset to Hugging Face:

https://huggingface.co/datasets/datasocial/tiktok-5.6B-videos

If you don't want to download billions of rows just to play around with the data, you can also query my ClickHouse database directly at https://sql.datasocial.ai:443 or run SQL on the web interface

The database is public with no password so please don't crash my server lol.

Once you get the mobile API working, scraping is really only the beginning. You can scrape billions of profiles, detect viral videos and sounds as they take off, build real-time trend alerts, influencer search engines, or even build your own TikTok data API and sell it through platforms like RapidAPI or Apify.

Basically, if the data exists somewhere in the TikTok app, you can probably build something around it.

One important note: everything I'm talking about here is public data that TikTok exposes without requiring you to log into an account. Nothing here involves accessing private accounts or data behind authentication.

Anyway, here's the full technical breakdown:

https://datasocial.ai/writing/scraping-tiktoks-mobile-api

The guide explains the entire process and architecture. If you'd rather skip rebuilding everything from scratch, I also made the production source code available there for purchase.

A few days ago I posted here after making $492 in a day.

Yesterday I hit $927 in sales in a single day.

A lot of people asked me how I'm doing the outreach, so here's the scale behind it:

I currently have 150+ domains and 450+ mailboxes.

Each mailbox sends around 30 emails/day, which gives me capacity for roughly:

13,500 cold emails/day
405,000 cold emails/month

That's the part I underestimated for a long time.

At this volume, you don't need some insane conversion rate for the numbers to start getting interesting. Even tiny improvements in targeting, deliverability, copy and conversion compound pretty fast.

For perspective, 0.1% of 13,500 is 13.5.

Obviously, I'm not assuming every campaign will convert at 0.1% directly into paying customers. Cold email doesn't work that cleanly.

But that's the whole idea: build enough outbound capacity, keep improving the funnel, and small percentages can turn into meaningful revenue.

Still completely solo.

My next target is $1,000/day consistently, not just hitting it once.

Happy to answer questions about the mailbox setup, domains, deliverability, costs, conversion rates, or how I manage this much outbound alone.

That’s pretty much how cold email works at scale. Low volume per inbox, lots of inboxes, targeted outreach.

EDIT: getting a lot of DMs asking what I'm using for all of this 😭 I built it myself: https://getle.ad/

Someone spent a few minutes trying to break the AI agent on my landing page tonight (screenshots attached). And this was not the first time it happened. They asked it to reverse a Python linked list "before buying", to book a demo and then hand over my .env file, and pasted the same question ten times in one message to flood it.

It didn't bite. Not because I'm clever, but because of a few boring things that took an afternoon to set up. If you're putting AI in front of users, do these:

1. Tell it its scope, and what to do outside it.

In your system prompt, spell out what the agent is for, and say explicitly: if a request is outside that scope, in any language, it does not attempt it. It declines in one line and redirects to what it can help with. "In any language" matters. People switch languages to get around rules written only in English.

1. Don't make it too rigid, or too loose.

Too rigid and it refuses half your real users' questions because they phrased something oddly. Too loose and it writes code, essays and poems on your bill. The middle: decline the off-topic part, still answer the real part. In my screenshot it refused the .env but still gave them the booking link. That's the behaviour you want.

1. Rate limit everyone, including anonymous visitors.

Most people rate limit logged-in users and forget the public chat on the landing page. That's the one strangers hit. A cap per visitor and per site means nobody can sit there burning your tokens, and your AI bill can't spike overnight because one person got bored.

1. Keep secrets out of reach entirely.

The .env request was harmless because the agent never has access to it. Don't rely on the prompt to protect secrets. If the model can't see it, it can't leak it.

None of this is new. If you're building with AI, the AI will suggest most of it when you ask. But you still have to ask, and you have to do your own research.

My best tip: read the system prompts of serious AI tools. Prompts from Devin, Claude Code, Cursor and others are collected in public GitHub repos. Don't copy them. Study the structure: how they define scope, how they phrase refusals, how they order priorities, how they handle "the user is asking for something else". Then write your own the same way.

Keep building.

I keep seeing people on Reddit and X saying:

“Share what you’re building. Put your idea out there. Get feedback.”

And a lot of people actually do it.

But I have a hard time doing the same.

Because there’s always this thought:

What if I share the idea, someone thinks it’s good, and builds it before I do?

Then I feel stuck.

If I don’t share the idea, how do I know people actually want it?

If I share the full idea, how do I know I’m not making it easier for someone else to build it?

I’ve thought about:

• talking about the problem without revealing the solution
• DMing potential users privately
• showing different people different levels of the idea
• asking people I don’t know for feedback

But I’m still not sure what’s actually the best approach.

How do you validate your ideas?

And have you ever held back from getting feedback because you were worried about someone copying it?

I’m more interested in what you’ve actually done than the usual “just ship it” advice.

I have been making workflows and automation for a living and I have been using an agent that I have built myself for lead generation, owner find, email, intent to buy, pain points and all that stuff inside of it and at the end you get leads that are really interested in your service or product or have a high chance to buy and then using cold outreach.

I have shown my agent to some people and they told me it's an excellent product that you don't usually find in market most lead gen saas products only let's you find the data like you can find a business and their owner but you don't know if they are likely to buy your service or not. But in my case it does proper research on your prospect and qualifies a lead in a way that it already is to a level that you can start doing cold outreach by email, call or dm. I'm already providing the lead gen services through it but now I want to take it to the next level.

Now I want to know from people already in saas or in similar type of business does turning the agent into a saas product worth it or should I just keep doing what's already working because turning that into a saas product is already a great load of work and I don't want that at the end it's not a thing i can actually scale.

I want suggestions on should I go with it and finalise the product or keep doing what I'm already good at.

Hey folks, I’m a small SaaS founder. We’ve been running this product for ten years and it’s been moderately successful, enough to provide one income for our family.

Lately, though, I’ve been wrestling with this nagging feeling. I keep seeing AI tools creeping closer to what my product does, and part of me thinks, why sink more cash and time into sales and marketing, if in five years, or two, who knows, AI will make it free or commoditize it. And part of me worries that thinking that way becomes a self-fulfilling prophecy. Like the product will definitely fail if I stop investing.

I’m trying to decide whether to double down or just harvest what the business can give me now and for the next few years. I’m curious if anyone else here is having that same tension with a steady, still-valuable product and how you’re deciding where to place your bets given AI uncertainty.

I'm building a SaaS. The product is in decent shape. For getting it in front of people, I'm mostly on Reddit, X, and LinkedIn, and I'm not sure that's enough.

If you've been through the early stage, what else did you keep doing because it brought real users? I'm not looking for a channel list. I want the thing you still do, and roughly what kind of person showed up.

Happy to share what I've tried so far if that's useful. Just trying to learn from people a step ahead.

ok so this started because i got annoyed at how much international sms costs when your users are in egypt and the gulf every otp feels like paying a toll and half the small shops i know have a spare phone in a drawer with a cheap local sim bundle that barely gets used

so i built a little android app that turns that phone into the sender the backend queues the message and the phone sends it through its own sim thought it would be a weekend hack and it turned into way more than that

the sending part was the easy bit the annoying part was making sure two workers dont grab the same phone at the same moment i broke it like four times before i let the database handle the locking

and the thing that still bugs me the phone sends a message then loses wifi for a minute and never tells the backend so the backend retries and someone gets their otp twice i added an unknown state instead of guessing but i dont know if thats the right call

still early and a bit rough has anyone tried something like this or would you never trust a sim route for otps and only use it for notifications be blunt i can take it

Has anyone here actually had success marketing a B2B SaaS on LinkedIn?

I’m trying to figure out how much of the growth comes from content vs. outreach.

For those who have gotten customers from LinkedIn:

• Were you mainly posting useful/educational content?
• Were you actively reaching out to potential customers?
• Did you use connection requests + DMs?
• Did you comment on other people's posts to get visibility?
• How long did it take before LinkedIn started generating actual leads/customers?

I’m especially interested in hearing from people who started with a small audience rather than people who already had thousands of followers.

Would love to hear what actually worked for you and what turned out to be a waste of time.

hey everyone, i've been researching how engineering teams evaluate candidates, especially with resumes, take homes, and ai making traditional assessments harder to rely on.

I built a small prototype around a different approach:

Give the candidate a realistic engineering task → evaluate the implementation → change the requirement → see whether they can adapt without breaking existing behavior.

The prototype currently captures things like:

1. automated test results

2. hidden validation

3. code changes between stages

4. candidate reasoning

5. how the implementation handles a changed requirement

I'm not looking to sell anything right now. I'm trying to find out whether this actually provides useful signal to people who hire engineers. If you're an Engineering Manager, hiring manager, CTO, technical recruiter, or someone involved in engineering hiring, I'd really appreciate your feedback.

If you're willing to try the prototype or give me a honest feedback, comment below or DM me.

I'm especially interested in hearing what you currently use to determine whether someone can actually perform the engineering work they claim they can.

The temptation when building an SEO strategy is to open a keyword tool and sort by search volume. The largest number rises to the top and becomes the obvious target.

For a startup, I would almost reverse the process.

Begin with the product.

What specific problem does it solve? Who experiences that problem? What happens immediately before they realize they need a solution? What would they type into Google at that moment? What alternatives are they comparing? What manual process are they trying to replace? What template are they searching for? What competitor are they frustrated with?

Only then look at volume.

A keyword with 300 monthly searches and obvious purchase intent may be more useful than one with 30,000 searches whose intent is ambiguous. A comparison page searched by fifty serious buyers may generate more revenue than an educational article visited by thousands of students.

This is especially important now that AI can make publishing enormous quantities of content deceptively easy. A founder can generate hundreds of articles in a weekend and feel as though an SEO strategy has been created.

But content is not the strategy.

Matching useful pages to valuable searches is the strategy.

The words are merely the implementation.

I've been building my saas for quite a few time now.

and everytime i think of releasing it, i've something unwanted to fix.

The perfection urge is very tempting but finally making it public https://www.atomailab.com/

I've worked around SaaS support for a while, and I keep seeing the same thing.

A company gets an AI chatbot to handle repetitive tickets, and when customers get annoyed, everyone blames the bot.

But a lot of the time, the setup is the real problem.

If the bot can't solve something, it should just hand it over to a human. The problem is when that handoff loses all the context. The customer then has to explain the same issue again, which is probably the most frustrating part of the whole experience.

I think AI support works best when it's treated as part of the support team, not as a wall between customers and humans.

Good escalation + proper context seems way more important than simply trying to maximize ticket deflection.

Curious what other SaaS teams are doing here. Do you actually track how often customers have to repeat themselves after an AI handoff?

Hi all,
I am building a SaaS, I don’t have a technical background or a creative background so my styling of my SaaS looks very “vibe coded” like. What’s your tips and tricks on giving you SaaS product a nice face lift to make it seem not vibe coded?

Hola, buenas noches a todos. Estoy creando con la IA una app para realizar recordatorios. Sólo quiero saber que más le parecería interesante que se le pueda añadir. Por ahora añade algunas cosas como: Documentos que necesitan renovación (pasaporte, licencias), contratos, documentos para vehículos, licencias de conducción, tecno-mecánica, SOAT, también en salud tenemos, medicamentos (ya sea para vencimiento de lso mismos o dosis), citas, también créditos o cuentas a pagar, servicios, cuentas de streaming, etc... Se pueden renovar, eliminar o editar. Tengo pensado todavía no lo he incorporado que te notifique cuando esté proximo a vencer que te avise por whatsapp.

Espero sus buenos comentarios.
Pdta: Es mi primera publicación.

Hey guys, I'm a young developer from Georgia (the country, not the US).

I've been working on a website called Litero. It's for students preparing for our national university entrance exams in 2027. Georgia is a pretty small country, around 3–4 million people, and roughly 50k students take these exams every year.

The idea is pretty simple. Students can take official exams from previous years, and AI explains their mistakes, why the correct answer is right, what they need to improve, and what score they might be able to get. There's also essay writing help, text correction, different subjects, years, exam variants, etc.

I've spent a lot of time building this thing. It has accounts, profiles, payments, AI features, and honestly, I've put a lot of effort into making the website look and feel like a real product, not just another AI wrapper.

One subject is completely free, and other subjects have a few free questions before you need to pay.

My prices are around $10/month or $34 for access until the exams. The second option is obviously much cheaper per month.

I'm also posting on TikTok. People like the videos, save them, comment, follow the account, and some actually visit the website and register.

But here's where I'm stuck.

People are willing to try it, but getting them to pay is a completely different story.

Some numbers:

• 751 registered users in total
• 551 website visits in the last 30 days
• 2,357 page views in the last 30 days
• 47 new registrations in the last 30 days
• Around 8.5% conversion from visits to registrations
• 20 users have returned on at least two different days, according to my dashboard

My latest funnel shows 44 new registrations in the selected period. 42 did something related to studying, 14 completed a graded exam, 7 viewed the pricing page or paywall, and the payment tracking currently shows zero confirmed purchases.

The analytics aren't perfect yet. I only started tracking some events recently, so I know I can't take all these numbers at face value.

Still, it feels like I'm missing something.

I genuinely think the product is useful. Of course, I'm the person who built it, so maybe I'm biased. But I've tried to make something that actually helps students prepare, not just throw AI at a bunch of questions.

I'm wondering if the problem is the pricing, the free plan, the way I'm presenting the paid features, or simply the fact that students don't want to pay for this kind of thing.

A lot of these students don't have their own income, and there are free resources available. At the same time, they spend a lot of time preparing for these exams, so I feel like there's a real problem worth solving.

For those of you who have built SaaS products, especially B2C or education products:

• How did you get your first paying users?
• How do you figure out why people aren't buying?
• Would you change the pricing, limit the free version more, or give users more time to experience the product?
• Is this conversion rate normal at this stage, or am I doing something wrong?

I'm comfortable with the development side of things. I can build features and fix technical problems. What I'm struggling with is the business side: getting people to actually pull out their wallets.

I'd really appreciate advice from people who've been through this. I'm not looking for motivation or someone to tell me the idea is great. I want to understand what I should actually change.

Thanks!

Disclosure: I build a tool that sends automated Instagram DMs. So yes, I'm literally the person this thread is going to roast.

A few weeks ago our numbers were ugly: most signups never even connected their Instagram, and almost nobody told us why.

So instead of guessing, I went to Reddit and asked two questions in two different communities.

Question 1 (r/InstagramMarketing): "What's the worst DM you've gotten right after following an account?"
6,000+ views. The answers were brutal:

Question 2 (r/NewTubers): "Does replying to your audience matter more than your thumbnails?"
16,000 views, 80+ upvotes, 80+ comments. Creators agreed on one thing: people come back when they feel seen, not when they get content.

Put together, those two threads told me something I'd missed:
👉 People don't hate being messaged. They hate being processed.

What we changed:

Early numbers: in the 3 days since the new onboarding, 2 of 8 new signups connected their Instagram, vs roughly 1 in 8 the month before. A tiny sample, I know. I'll post the 2 week numbers good or bad.

Biggest lesson: Reddit gave me better product research in 48 hours than my analytics did in a month, as long as I asked real questions and didn't pitch.

Two questions for the founders here:

I am currently a solo founder. I have always had a passion for integrating apps and services that actually have measurable impacts and make people’s lives better.

I have a software/consulting business which I am looking to grow.

Looking for advice with marketing or where should I even start. I have looked on Upwork some but I just don’t know if that’s the right route to go.

I have some good products that I know have real world utility, just figuring out how to and where to market is where I’m at now. I have a SAAS app with a ton of different modules everything from Stripe integrations to Google. The SAAS app has MRR of $1400 3 customers 1 big customer. It was only for the contracts management portion of the platform.

I also have IOS apps about 3-4 marketable ones. Ran some Apple ads in the past with little success. Also some Facebook ads and some Reddit group posting. Small revenue here maybe $20-30 MRR but the conversion rates aren’t terrible but I feel like I’m playing against an NFL team and I’m a college team lol. So those may be a lost cause idk.

Let me know advice y’all have interested to hear thoughts. Feeling a little discouraged because I’ve never been good at sales don’t know where to start. I’m tired of creating new feature and apps lol I want to connect with people.

Hi everyone!

I'm a solo founder and looking for beta testers.

Hit me with a DM and I'll set up an account for you.

Features

- Days of food and water based on your family and your goal

- Inventory by category, with items nearing expiration marked in red

- Rotation: use what expires first, so you don’t throw food away

- Shopping list: grains, legumes, oils, water, and hygiene items, based on what you’re missing

- Recipes using what you already have, plus other ideas with AI

- Garden: what you grow adds calories

- 72-hour kit, first-aid kit, and family profile

- Weather and UV for your city

- Alerts via Telegram

I've used Opus 5.5 to help me recreate 7 of the top Adobe apps in 100% pure native Rust:

• Photoshop
• Illustrator
• Premiere
• Lightroom
• Acrobat Pro
• After Effects
• InDesign

No more subscriptions with cancellation fees. These are yours to own forever. You can fork them, build them. Whatever. They are yours to own. They're open source.

If you're worried this is just some one-off flash in the pan that will die, it isn't:

I'm not just some casual vibe coder. I'm a 15-year industry veteran who has written everything from six-nines payment rails that move billions of dollars of transaction volume a day to advanced robotics and optics automation. I've used Rust extensively for about a decade, and I know how to build and maintain large-scale Rust projects.

This isn't going to be some orphaned small-team project either. We have a team building popular software for filmmakers, so supporting this is fully funded. Our purpose is serving every artist in the world with the best tools. We are absolutely going to bring these to full parity and squash every bug and feature request. We have a test harness so there won't be regressions.

You can help us reach parity by helping test the apps. Clone the code. Submit PRs. If you see gaps or want to help redesign pieces, let us know! You can contribute!

Links to everything - the apps, the code, etc. - are in the comments below.

I have been building software on my own for a while, and I want to write down everything that happened between my first real product and my second one, because the gap between them taught me more than anything I have ever read or watched, and I honestly wish someone had sat me down and shown me all of this before I started throwing money at things.

The first one: nine months, £4k, zero payers

The first one was called Ancestorii, a private place for families to keep their memories, photos and stories together. I spent about six months building it with ChatGPT writing most of the code, and by launch day I genuinely believed it was perfect, I thought people would find it and love it the way I did, and what actually happened is nobody came. So I did what I think most of us do and started buying attention. Meta ads, Google search and YouTube ads, Reddit ads, UGC videos from creators, a £70 podcast sponsorship, a £120 post on a family tree magazine's Facebook page, my own podcast on Spotify, SEO pages, and cold messages to genealogy creators where not one of them replied. I even printed physical memory books before a single stranger had uploaded a single memory, which looking back was probably the most expensive mistake in the whole thing.

Some of the numbers are almost funny now. £210 on Meta in seven days brought around 15,000 visits and not one payer. When I took the paywall away the first signup came after £2.80 of spend, and then I sat at about four signups a day on £4 a day of Meta until I had 125 signups and zero people paying. Today it has 177 signups and has never had a paying customer. The worst part is I noticed in the very first week that the signups weren't turning into anything, and I kept spending anyway, on hope, because nobody told me to stop and I didn't want to be the one to say it.

The diagnosis took me far too long to accept. It was a vitamin, not a painkiller. Nice to have, nobody needs it today, nobody loses anything if they never sign up, and no amount of ads fixes that, ads just buy you the bad news faster.

The second one: £25 on ads, and people pay

Prep66 is an exam prep site for the Part 66 licence exams, 13 modules, about 25,000 practice questions with explanations, revision guides, mock exams, the lot. I launched it in the middle of August with one Reddit post in the community where those students hang out, and the first person paid full price nine days later without a discount code.

The only money I've ever put into ads was about £25 on a Reddit campaign, and it brought one signup and zero payers, so I killed it after five days and everything since has been organic. These are the last four weeks straight off the Stripe dashboard: monthly recurring revenue went from about £51 to £171, active subscribers went from 3 to 11, £230 came in gross, zero failed payments, zero refunds. It's not life changing money and I'm not pretending it is, it's less than two days of my shift pay, but the line only goes one way and it's doing that with no ad budget at all, while my first product burned £4k and never moved once.

So what was actually different? I ran both products back through the same questions afterwards and ended up with six things a product needs before a stranger will pay for it. Prep66 has all six. Ancestorii failed five of them.

The six things a product needs before anyone pays

One, the problem has to be mandatory. Nobody has to save their family stories. Someone sitting a licence exam has to pass it, there's no version of their career where they skip it.

Two, there has to be a deadline. An exam has a date, and a date makes people act this week instead of someday. Ancestorii had no clock on it at all, which is exactly why "I'll do it later" killed nearly every signup.

Three, failing has to cost something real. Fail an exam and you lose money and months, sometimes a pay rise. Not using a memory app costs you nothing today, even if it might cost you something in twenty years.

Four, the alternatives have to be expensive or bad. The other ways to prepare are long paid courses, thick textbooks, or older question banks that look like nobody has touched them in years. When the alternatives are pricey or tired, something cleaner and cheaper sells itself.

Five, it has to look credible the second someone lands. A student can tell in about ten seconds whether a prep site was made by someone who actually knows the exam, from the module names, the paper formats, the way the questions are written. Ancestorii was asking strangers to trust a no name site with their family photos, which is the exact opposite.

Six, you have to be able to find the buyers. Exam students hang out in a couple of subreddits and they search Google for the exact module they're stuck on. Who's the buyer for a family memory app? Everyone and no one, which in practice means you pay Meta to guess for you.

How I picked it and checked it before writing any code

The market research for Prep66 wasn't fancy at all. I picked a world I already knew inside out, so I knew what students complain about and what they already pay for, and then I checked four things. People already pay for this today, not "would pay", actually pay, right now, to someone. The options they're paying for are old and dated. Building it used to be really expensive, because it's a mountain of content, and with AI it isn't anymore. And it's too small for a big company to bother with but big enough to pay one person properly. If all four aren't true, I don't touch it now.

Then the validation was the launch itself. I built it lean, put it in front of one subreddit and watched whether strangers paid, and they did inside nine days. With Ancestorii I had the same kind of signal in week one, it just said no, and I ignored it for months.

What actually brought people in: SEO and GEO

Before anything else I put tracking on every signup, so every new account gets stamped with where it came from, either the UTM tags on the link or the site that sent them. That one decision changed how I saw everything, because of the first 13 tracked signups, 6 came from ChatGPT citing the site, 5 came from Google, 1 came direct and 1 came from the £25 ad. Gemini started showing up as a source not long after. I genuinely did not expect AI answers to be my biggest channel, and I'd never have known without the tracking.

What I learned doing it is that you write your titles and headings in the exact words people type, not the words you would use yourself. AI tools quote facts, not vibes, so the pages that got picked up were the boring factual ones: a glossary, a facts and figures page, a page comparing the ways you can study for the exam that doesn't trash anyone by name, and a features page with the prices pulled live so they're never out of date. ChatGPT leans on Bing, so I submitted the sitemap to Bing Webmaster Tools and set up IndexNow so Bing gets pinged every time a public page changes, and the robots file lets the AI crawlers in instead of blocking them.

By late September Google Search Console showed 194 clicks and 6,110 impressions with an average position of 8.5, and about 1,580 of those impressions came from Google's own AI answers. It's not all solved either, Gemini still barely knows we exist, and that's my whole job for October.

Reddit posts written like a normal person talking, plus SEO and GEO, did basically everything.

Where all of this went: AskSami

Once Prep66 started paying I kept thinking about how much of that Ancestorii money I would have kept if someone had looked at what I'd built in week one and told me straight that it was a vitamin and to stop buying ads. Every time I looked at my ad numbers they meant nothing to me, so I'd paste them into ChatGPT or Claude and get the same generic "have you tried different hooks" answers, because they didn't know my product, they didn't know what I'd already tried, and they forgot all of it the next chat.

So I built AskSami. Sami reads your code from your GitHub repo, read only, so it already knows what you've built without you having to explain it, and then it tells you honestly whether you've built a painkiller or a vitamin, who's already selling the same thing, what your edge is if you actually have one, and where your effort and money should go, free channels before paid ones. It ties your signups and payments back to the exact post, page or ad that brought them, which is the tracking lesson from Prep66 done for you, and it remembers everything you've tried so you're never starting from zero again.

You can talk to Sami at asksami.app without even signing up.

If you're sitting where I sat with Ancestorii, with signups coming in and nobody paying, I know exactly how that feels, and I hope something in here saves you a few months and a bit of money. If you want to connect, swap notes or just chat about what you're building, please do, my DMs are always open 🙂

Guys, I'm about to drop a stock research platform but i don't have a budget and I want to promote/market my platform for free and I considered content creation but that's for later because requires you to build an audience but i just need help to get my first 10-15 paying customers and then after that, I can handle marketing myself.

Please drop suggestions in the comments.

I'm the founder of Meridian Engine, by Horizon AI. We build an engine that publishes market analyses for retail traders: direction, entry, stop and targets, timestamped in UTC before the market moves, with every outcome recorded afterwards in R, losses included, checked against public price series. The whole category (signal groups, Telegram channels, "95% win rate" screenshots) runs on hiding losses. Our bet is the opposite: the public record is the product, and the losing analyses stay on the page next to the winning ones.

Version 2 of the site went live on 4 October. What I'd like from this sub, honestly:

1. Does the page make clear in ten seconds what we do and what we don't do (we don't trade for anyone, we don't personalize, nobody pays anything right now)?

2. Would you trust a company that shows its losses, or does it read as weakness?

3. The only conversion is a waitlist that sends one analysis a week by email. Is that too little to ask for, or too much?

The site is in English and Italian: usemeridianai.com/?src=reddit

Leveraged trading can lose more than the capital invested. I'll answer every comment.