Iliya Valchanov

CEO @ Team-GPT | 1,300,000+ AI students on Udemy

Putting AI agents inside marketing agencies.

3x founder, 1.5M AI students on Udemy, ex-math competitor, finance graduate, 3x $0-$1M, boostrapped to $30M revenue.

Creator of content, software, and agents.

Co-founder & CEO

Learn, collaborate, and master ChatGPT in one shared workspace.

We are planning our biggest launch ever.

I'm in full founder mode, currently running 3 agents at a time (2 coding, 1 GTM), not counting the background ones. 

I don't have cognitive space for more even if I wanted to.

I feel like 10x-ing myself (again?). How many times can this happen within 1 year?

Will keep you posted.

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Personal website

Juma is a team-first AI workspace for marketing teams. 

We help teams and agencies co-create with AI, stay aligned on every project, and deliver better results together. Because the best ideas don't come from AI alone. They come from teams working together.

Juma is trusted by teams at Costa Coffee, Procore, Maersk, and Salesforce. Backed by True Ventures and Pact.


75K+ users, $1M+ ARR, AI for marketing teams

Co-Founder & CEO

1.5M+ students in the field of statistics, data science, machine learning, and deep learning.

AI Course Creator

3veta is an appointment scheduling platform with 10K+ active users.

Co-Founder

Co-founded and led 365 Data Science to 4M students and $1M ARR.

CEO @ Juma | 1,500,000+ AI students on Udemy

CEO @ Juma → AI that runs your marketing | 1.5M+ AI students in a past life

Juma was boostrapping and profitable.

But our competition wasn't. 
They had raised $3-5-10M+ and were growing by burning tons of capital.

The only way for us to exist today was to become venture-backed. 

Your market and competition are often the main drivers of VC-backed vs bootstrapped.

Trump banned Anthropic's Claude from working with US government.

It's because CEO of Anthropic refused these 2 use cases:
- Mass surveillance of US citizens
- Fully autonomous weapons

Mass surveillance of US citizens is clearly bad.

But here's why autonomous weapons are so terrifying:

Imagine 10 million drones controlled by a single person, with no chain of command and no accountability - just an algorithm deciding who dies.

That's not defense but the most powerful offense.
It's a dangerous concentration of power.


Trump called Dario selfish and arrogant. 
But Dario Amodei is the only major AI CEO publicly saying this out loud. I've read his 15,000-word essay 'The Adolescence of Technology'. Twice and highly recommend it.

Actually, Dario's company (Anthropic) has the most powerful technology in history of humanity. But he wants it to be used for good. 


The whole problem and rhetoric about this is about who actually gets to decide.

Who should decide how AI gets used in war?

AI, the Pentagon or the CEO of a tech company?

We're in the middle of a pricing overhaul at Juma and wanted to share what we're thinking. 

The problem:
We sell an AI agent for marketing tasks. Until now we've been seat-based ($25-40/seat/month). But as the agent gets more capable, the business model breaks in two ways:

1. Our costs are usage-based, our revenue isn't. 
Some customers pay $40/month and burn $800 in compute. Others pay $250/month and barely use it. The misalignment is getting worse as agents do more. We are not aligned with power users but with sleepers, which is ridiculous as a concept.

2. Seats shrink, not grow. 
One person with a good agent does what 3-4 people did before. Our customers are literally reducing seats because fewer people need to touch the work. We're selling units of something that's deflating (seats).

What we are thinking:
Low workspace fee + unlimited users + credits. 

Heavily inspired by Lovable's model (they hit $200M ARR in 13 months after removing per-seat pricing). 

The idea:
- Free tier with enough credits to complete a few full agent runs (the 'aha' moment)
- One paid plan - flat workspace fee, unlimited seats, credits included, top-ups when you need more
- Enterprise for SSO/compliance/volume

Image shows what we are thinking (far from final).

We are showing what credits can do, because it is the main objections right now. 

We are excited about virality of this because if adding a teammate costs $0, every person invited is a potential power user who drives credit consumption.

What we're still debating:
1. Base price. $29? $49? $99? 
Lower = more viral, higher = better signal + filters out tire-kickers. We don't have a sales team so PLG has to do the work.

2. Credit anxiety..
Everyone on the team has experienced it — you're mid-workflow and suddenly worried about burning credits. UX has to solve this (never break a run mid-execution, show cost before action, auto-recharge).

3. Migration
What do we do with existing clients?

Curious about any thoughts you have whatsoever. 
We need to decide ASAP and get it live by 23 March.

Yavor Belakov was about to give an awesome lecture on agents but something came up. Whoever is coming will get the 2nd best option- me.

If you enjoy my lecture on agents, I'll stop accepting the fundraising talk invitations and will pivot to deep tech lectures.

17 March during AI in Practice Masterclass by Kapital.

↗️ 𝗬𝗼𝘂𝗿 𝗻𝗲𝘅𝘁 𝗔𝗜 𝗶𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁 𝗰𝗼𝘂𝗹𝗱 𝗯𝗲 𝗮 𝗴𝗲𝗻𝘂𝗶𝗻𝗲 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲 𝗼𝗿 𝗮𝗻 𝗲𝘅𝗽𝗲𝗻𝘀𝗶𝘃𝗲 𝗰𝗵𝗮𝘁𝗯𝗼𝘁 𝘄𝗶𝘁𝗵 𝗮 𝗯𝗲𝘁𝘁𝗲𝗿 𝗹𝗮𝗯𝗲𝗹.

Everyone calls their product an "AI agent" now - from simple automation tools to systems that can actually think, plan, and deliver results on their own. When everything sounds the same, how do you tell what's real from what's just marketing?

Iliya Valchanov teaches 1.5M+ students on the topics of AI, data science, and machine learning. He is co-founder and CEO of  Juma (ex Team-GPT), a marketing superagent that executes complete workflows autonomously - analyzing data, generating content, and delivering ready-to-use assets.

At 𝗔𝗜 𝗶𝗻 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀 on March 17, Iliya will explain:
➤ How the most capable AI agents actually work
➤ What makes an AI agent "real" today and how to spot the difference between a genuine agent and dressed-up automation
➤ How the best agents plan, do the work, and check their own results 

A 𝗰𝗹𝗲𝗮𝗿 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 for understanding what's under the hood  so you can make confident decisions whether you're building or buying.

Iliya’s keynote is for leaders who want to invest wisely in AI agents without getting lost in the hype.

📅 March 17 | Grand Hotel Millennium Sofia
🎫 Secure your seat → capital.bg/en/event/336


#AIinPracticeMasterclass #AIinPractice #AIAgents #MarketingAI #AgenticAI

Next week Juma will have a low-key launch of something we've worked on for the past 3 months. 

You'll hear a lot more about it soon but this will be special because it's an AI Engineer Foundation meeting in our offices!

I love that this coincides with a long-time member giving an exciting lecture.

Georgi Alexandrov built an autonomous agent that monitors his home server - crash detection, log analysis, auto-recovery. He'll walk through how agentic frameworks work: the tool loop, system prompts, lifecycle hooks, and safety gates. Built with Pi-mono (the engine behind OpenClaw) and a self-hosted 35B model from his wardrobe.

Come and let's talk about agents: 
https://lnkd.in/eV3dtixX

Tech Lead at Sourcelab

What makes a great marketer? Think: Steve Jobs, Elon Musk, Kim Kardashian, most recently even Timothee Chalamet..

I think it's: 
- strategic thinking
- 6th sense for what works
- curiosity and willingness to experiment
- understanding of marketing mix and multi-touch interactions (even on a subconcious level is enough)
- taste!!!

What most great marketers can't do:
- Run ads
- Edit videos
- Set-up Google Analytics
- Write SEO-optimized articles
- Know where to find stuff in HubSpot lol


Keep in mind:
-> The first list will remain human
-> The second list is being automated as we speak

Juma is a superagent that can do any marketing task.

We have rolled out the full capabilities to only 5 workspaces (~100 people). 

If you want early access to try it out, send me a DM.

Or comment 'superagent' below.

Our product can do the same as Lovable, Manus, etc... just 6 months later.

The best companies are best at... speed. 

Speed is the only thing that matters in AI right now.

Memory for agents!

Round led by an OpenAI co-founder, amazing Vasilije Markovic!!!

Founder @ Cognee inc | Semantic memory for AI apps and Agents

We raised $7.5M to scale our knowledge engine that gives AI systems memory.

LLMs are powerful, but they’re stateless — once a session ends, context is gone. Companies have their own context, rules and practices. There are no solutions out there that can bring this knowledge reliably to the LLMs.

At cognee, we’re building a knowledge engine that allows AI systems to retain context, understand relationships, and dynamically update the knowledge over time. 

We raised $7.5M in seed funding led by pebblebed — founded by Pamela Vagata (ex-founding engineer, OpenAI) and Keith Adams (founder, Facebook AI Research Lab) and the amazing Tammie Siew — with participation from 42CAP and Vermilion Cliffs Ventures and angels like Jan Oberhauser from n8n, Charles Dolan, Alexander Dean, Matthaus Krzykowski and Combination VC, and Roman Stanek, Jan Ebbinghaus, Tony S. Kim, Mehdi Ghissassi, Steffen Kirchhoff, Daniel Kirch, Ilya Kozlov, Bojana Miloradovic Parman, Dr. Pascal Wichmann, Jens Lapinski, Bob van Luijt to scale up engineering, accelerate research, and increase number of cognee deployments to clients like Bayer from 70+ to 700+.

I want to thank the team, the open source community, and to our investors for the trust.

If you are struggling with memory, our devs can get cognee running with your data in 7 days. Don’t hesitate to reach out to us.

5 years ago we dropped this ad.

It didn't convert well.

But boy did we enjoy making it!

Може би в топ 3 на клиентите, които са помагали за развитието на Juma → Simeon Penev и VertoDigital

Лекцията ще си струва!

n8n Ambassador | Data & Analytics Consultant at VertoDigital

🤖 AI инструментите вече не са "nice to have".

Миналата година VertoDigital мина от разпръснато ChatGPT използване до 90%+ AI adoption в екипа. Ключов елемент? Juma (ex Team-GPT)

На 26 март от 19:00 ще покажа на живо как използвам juma.ai в ежедневната си работа. Без теория - само практика.

За всеки пример ще видите "преди и сега":
➡️ Колко време отнемаше?
➡️ Какво се промени с AI?
➡️ Какъв е реалният резултат?

Семинарът е безплатен и подходящ за всеки в дигиталния маркетинг.

👇 Линк към семинара в първия коментар

'Am I in the market for better janitorial services?'

I'm still trying to figure out if they want to mop my floors or prep us for an IPO through a leveraged buyout.

Growing MRR of B2B SaaS companies via affiliate marketing | Growth Manager @ Reditus | T500 | Reforge '24 🤘

Hi there, welcome to my profile!

Currently building Signalbase, a real-time signal provider helping GTM and RevOps teams be the first to reach out when a signal occurs.

Because let’s face it, creating firmographic-first lists and hoping for intent later simply doesn’t work anymore. Prospecting isn’t a filtering exercise as 95% of your market is not ready to buy, but signals can help you see who is about to be.

We help teams spot real intent signals before anyone else does and plug those signals straight into your existing GTM stack, so your workflows trigger when the market’s ready, not when it’s too late.

You will want to use Signalbase if: 

1. You want a healthy pipeline with active companies
2. You seek verified signals to feed your GTM workflows
3. You don't have time to learn Clay or the money to hire someone to do it for you

Ready to discover some accounts with real-time intent? 

Give Signalbase a try, no card needed!

Talking about signal-first GTM and data which you will use to feed your workflows with

Georgi Furnadzhiev

Clay just increased their pricing 🤷‍♂️ 

The most important thing that you need to know? 

👉 HTTP API costs jumped 0→ $0.03 each (imagine that table run)
👉 You need to pay extra if you want to use their signals 

For a detailed breakdown you can check their pricing, but now we need to address something BIGGER that's happening! 

When a platform taxes data access & nudges users toward their "actions", which is their new feature...the implicit message reads that data matters less & what you do with it matters more.

I disagree + contact data gets cheap, not signals 😉 (Thanks for the question Wesley & Spencer for pushing me to share my thoughts.)

To put it simply, garbage in = garbage out 

History simply shows that your data is only valuable when it's contextualized and verified, as there is simply so much noise out there. 

In fact, that's the reason why to every raw signal source inside Signalbase we run additional enrichments to meet at least 80% accuracy threshold.

So big updates or not, don't lose control over your data quality 

P.S to address another question which destroyed my DMs - If you are looking for an alternative check (in no particular order) 👉 Databar.ai, Baseloop, Freckle.io, Floqer, Cargo 🧱, Sendr, Starnus, nRev, Extruct AI, BitScale

API for real-time signals at scale | CEO @Signalbase

Building Signalbase in public to $1M ARR

👇 Here are a few lessons from this week 👇 

1. Founders should not automate everything, at least not so early in their journey! 

Yes, I said it as perhaps too many of us think about designing shiny GTM systems rather than doing what's needed for you to survive today

While everyone talks about automation, I’m still sending ~200 messages manually and doing support 24/7 as I need to feel the friction to get better with every single day 

I need to see where people hesitate, what objections repeat and what wording makes someone reply on a Sunday afternoon and jump on a call to evaluate us.

Honestly, why even worry about scaling something which may not even exist down the line???? 

By far the hardest part is also to remember that your journey is not "theirs" :) So focus on your own resources and timeline

2. Don't underestimate the importance of resource allocation

If you wait for something to address the bottlenecks within your business, you are a dead man walking

I learned to challenge what's currently in place, as only then can you experiment and move the needle with learnings.

Guess what? We set an experiment exactly 22 days ago, and that thing starts to slowly pay off, shaping the slightly different direction of the company.

Many VCs claim that speed is key, but perhaps we need to talk more about the speed of gaining new learnings and iterating upon them.

Radical choices always seem to be the hardest right now, but they can save you in the long run.

3. Learn from others ahead of you 

A few weeks back, I spoke to another founder of a data product and what he simply said saved me 4 years of struggling. 

Because finding PMF and that repeatable use case is not an easy job, but we are getting closer with every passing day.

Right now, we are still in a state where we get destroyed by feedback and at times, it actually feels shameful to be in the call.

Yet that exact same feeling means that people care about what you are building and the direction that you are heading to!

Shall we take a realistic look at the situation? 

The roadmap is clear, the vision is clear, the pipeline for high ACV deals looks good...

We just need to keep on hustling and showing up just like the live pre-verified data in our dashboard 😉 

That's it for today, looking forward to crushing the new week!

Time to ditch the old databases with stale data and find the real movement so you can be the first to reach out.

👉 try Signalbase

Wrapping up month 4 of building Signalbase in public to 1M MRR

Trust me, this one got the best of me...

Believe it or not, everything that we did in the past suddenly stopped working and we got stuck BIG TIME.

It felt like it just didn't click, no matter how hard we tried. (the nightmare of every founder)

Luckily, we remained hungry for learnings and the market showed us a new direction, which made us finally discover that sweet repeatable use case.

I remember talking to Iron Brands and Adriaan van Rossum about it at the beginning of the month: 

"I am dedicating the entire month to exploring that ICP" and it worked as I had a record of 6 high ACV calls in one day. Pipeline is growing nicely at the moment too! 

We also managed to bring life back to our biggest deal that we lost back in December (The very optimistic me thought we could close it in 2 weeks of building 🤣) 

All while still getting a few customers a day via the PLG motion, which we were also improving in the meantime, on top of training our own LLM models, as signal verification ain't a joke! 

2 few things that I am extremely proud of 🧡

👉 Shipping the biggest quality update within our 3-step verification process
👉 Making our first full-time hire 

March will be huge, let's survive!

Month 5 of building Signalbase in public to $1M MRR 

Weekly product update 👉  We shipped A LOT of code over the past 4 days 

🧡 Core scraping and validation process upgrades
🧡 Taking the first step towards signal stacking 
🧡 Shipped the beta for the hiring signal
🧡 Introduced new filters for the job changes
🧡 Rebuild completely the M&A signal
🧡 Introduced a self-sustaining investor and company databases

Now that's what I call building a sick product! 

Extremely proud of the boys Tadas Gedgaudas & Adriaan van Rossum for pushing the limits and keep on questioning what's possible 👏 

If you are tired of feeding your systems with stale accounts, this is your sign to refresh them with signals sourced within a minute

STOP killing your SDRs right now.

If you're an in-house GTM exec betting on “AI replacing humans,” you might be slowing your own pipeline.

To prove you wrong, I had the absolute pleasure to take a deeper look inside Clay’s actual GTM engine with Everett Berry 🐐 

While everyone keeps shouting about “AI SDRs are replacing humans", the winning companies are surrounding their top performers with the most advanced automated systems

Here’s what’s cooking inside the episode👇

 🟧 How you should think about building your in-house GTME team
 🟧 Clay's 4 main signals that helped them to scale before being integrated within the platform
 🟧 The biggest mistake they made while scaling their signal engine
 🟧 Why data quality quietly kills most outbound teams

and of course a ton of nerdy battle-tested tips for the hands-on practitioners out there! 

If you're building a signal-based GTM engine, rethinking your SDR team, or wondering how automation should actually fit into your stack…this one’s for you

Don’t kill your SDRs yet, let’s get practical!

Finding recently hired execs across the world has never been easier 🤯 

We just shipped the new company country and city filters, which enable you to find the right people at the right time within the right location 

All of this is also available via API 👇  

Let's build your first signal-based list Signalbase

The friday shenanigans are here to stay, and so are your evergreen signals 🕺

Believe it or not, you do need them as every piece of context helps you narrow down your list, which also increases your probability of success

Let's take the fundraising signal as an example. Once an org secures their round, you can expect them to: 

👉 Invest in new features or optimise current ones (great if you are selling data) 

👉 Expand to market or simply add another location within the same country (great SEO & office management solutions)  

👉 Hire a new key exec or face more job changes (great starting signal for all vendors) 

and the list of hypotheses continues further, which helps you to layer an additional custom signal on top of your. 

Isn't it obvious that we all need to help the SDRs to talk only with people who have a budget right now? 

No need to spend 20K in complex enrichment chains, just build your first signal-based list under 2 minutes with pre-verified funding, M&A and job changes data at scale 

Happy Friday! Signalbase

Month 5 of Building Signalbase in public to $1M ARR

This time we will talk about GTM & the overall founder journey👇 

As a founder, you probably felt at least once that odd feeling in your chest that keeps you from breathing? 

Yep, that was me a few weeks ago while panicking about running out of cash. First thing we did? Put ALL of the money for product development meaning savings mode is activated.

Feeling lost about what to do next and how to take the company to the next level....I went back to all of the calls from November to identify patterns and something just clicked. 

If you go to our website, you will see that Signalbase slowly adopts a new look as a proper live data provider that acts like a refreshment layer on top of your datasets or agentic workflows

Over the past 2 weeks, we spoke with nearly every LinkedIn automation tool, AI SDR agent, AI GTM engineer, Clay alternative, and big GTM data provider.

The harsh truth about building a company?

We all read these great stories about going from 0 to 10M MRR in less than a year, but honestly none of that would happen if the market does not assist you (so yes there is luck involved) 

Right product, right time, right founder, right message

Another harsh truth? 

The moment your development stops, you are dead! 

You simply can't imagine how many alternatives and smaller competitors pop up on the market and most of them are born from one of the 500 WhatsApp groups out there!

We saw the saturation of tooling also this week as LinkedIn turned into a complete blood bath.

Here is the quote that made my week👇 

"Dude this is great!!! You don't know how much trouble Signalbase will save us with the signal sourcing. We need to get started as soon as possible" - a vendor who wants to feed our data into their product

Great, we hit the sweet spot! All we need to do is keep on showing up, keep on taking the feedback and the rest will follow. 

My role should also be to remember the bigger picture and know exactly our next 3 steps ahead.

Btw we have also reached a new revenue milestone and despite being small, I find it meaningful. 🧡 Because your team needs hope, a clear direction and an incredible amount of resilience along the way. 

There are a ton of other things, I won't be able to cover fully such as:

- Designing a repeatable sales process (I've seen it already 10 times so it's slowly becoming more repeatable)
- PLG experimentation (7-day free trials vs freemium) 
- Product updates such as server boosts and more AI magic to help you find the right leads
- Listing smaller chunks of our API here and there
- Answering Jack's question about how we use Signalbase (video is coming)
- Hyping further Francesco's sick agentic workflow (link below)
- Preparing myself for a few new speaking gigs while also working on the tweaks around our content strategy

That's all for now folks! ☕ 

Chat next week,
G

"The company has not made any official announcement regarding the funding."

I'm not kidding, this is the third time this month we've caught such news! And the best is that we can also showcase the source.

Now that's the whole point of using Signalbase 👇 

While the majority of GTM tooling goes on a monthly shopping spree to refresh their stale datasets, we will only display companies with real change!

- Funding rounds
- Job changes 
- M&A activity
- Hiring news

All captured, additionally enriched internally to find more data points and displayed in less than a minute when it’s publicly shared. 

Or in this case, even before that! 

Try Signalbase, you can be surprised 😉

You know that you are building a great product when one of the biggest GTM agencies hypes you up 🤝 Understory

Huge shoutout to Naufal Nugroho 🌲 and the rest of his team for supporting us since the second month of our journey! Deeply appreciating you folks, the product won't be the same without your feedback.

These guys really know the new rules of the GTM game, so if you are building your signal-based engine from scratch, make sure to hit them up.

Signalbase is the biggest cheat code for 2026 when trying to be the first one to reach out to PE investors while hunting for M&A deals at scale. 😎 

Let's build your first signal-based list under 2 minutes 👇

Just because someone is wearing red underwear..doesn’t mean you should mention it.🤷‍♂️  

Yet that’s exactly how most teams use intent signals 

They see one trigger, maybe two, and immediately start reaching out like it’s a green light. The result? “Intent signals don’t work.”

But that's so far away from the truth as you simply don't know how to build your signal-based system  😉 

Come join me for the latest episode of My First Signal, where I had the absolute pleasure to sit with Bill (SalesCaptain) to understand what it actually takes to build a repeatable signal-based GTM engine

*I think this is a better intro than a Greek and a Bulgarian sitting in a room 🤣 *

Here’s what we actually broke down in the episode:
🟧 Why testing 1–2 signals is a guaranteed failure
🟧 A harsh reality check for all GTM executives 
🟧 Sales Captain's way of introducing a 3-layer signal funnel
🟧 The importance of the “language-market fit” concept most teams ignore

And of course, a little lesson for vendors to not be so explicit with their signals! 

If you're looking to build a signal-based GTM engine in 2026, this one might save you months of hitting your head against the wall

Let’s get practical!

What if most of your “intent signals”… are just an illusion?

Call me crazy, but indicating that a lead smiled at you should not be part of your CRM 🥴 (yes, history knows these examples) 

While building Signalbase, I kept seeing the same mistakes being repeated over and over again.

👉 Not using evergreen signals to craft the first versions of your lists
👉 Treating all market shifts with equal weight
👉 Jumping on every like or comment 

The result?  Burning out your SDRs while reaching out to the wrong people

Come join me on the 11th to discover even more mistakes and so many more hard learned lessons when sharing the stage with Zeynep (CompanyEnrich) 

We are about to go crazy with this one, make sure to register below!

CEO: Is this a real lead or not? 🤷‍♂️ 

Now that's a dangerous game to play and if you feel overwhelmed by all of the noise out there, this one is for you 👇 

Till this day, it's incredibly funny to see how the landscape pushes social engagement as the ultimate source of intent while completely missing out on the whole context per account 

The number of times history knows SDRs sitting in a room talking to someone who is eventually going to waste their time is honestly ridiculous. 

👉 That's why you are burning out your GTM team
👉 That's why you see such low response rates 

and that's why competitors are closing the right deals in front of your eyes!

Come get a grip on your signal-based GTM strategy at 5 PM CET today with our friends at CompanyEnrich (Zeynep Serra Avan)

Workflows, battle-tested insights and most importantly fun! As we are all done with the boring webinars out there 

Chat later!

Catching leaked news one time is miracle, but catching it twice is a system 🫡  

Once again before the press and any kind of official announcement. 

Signalbase is just getting scary good after the new verification & sourcing updates in place! 

While majority of GTM agencies and in-house teams swim in stale data, Signalbase only displays companies when real change is happening 👇

- Funding rounds
– Job changes 
– M&A activity
- Hiring (yes, we finally shipped it!)

+ we now have a fully self-sustaining or simply put growing investor database driven by the fundraising signal itself

All of this captured in less than a minute ago when it’s publicly shared (or according to this case way before that! 👀)

It's time to act first, not watch competitors close deals in front of you.

👉 Try the new Signalbase

Too many GTM teams undervalue how complex scraping signals really is.

They think: “Just scrape it.” or “Just pull it via API.” or “Just add another data source.”

When building Signalbase, I came to realise that scraping is maybe 20% of the problem. The other 80% is what breaks quietly in the background while your product keeps serving bad data to your users.

To actually make signals usable inside your GTM workflows, you need:

1️⃣ Continuous source monitoring across hundreds of sources 
2️⃣ Multi-layer verification so you're not passing recycled data downstream to your users 
3️⃣ Deduplication logic that doesn't collapse at scale 
4️⃣ Schema drift handling when sources change structure without warning 
5️⃣ Backfills and uptime guarantees your product can actually depend on 
6️⃣ An 80%+ accuracy threshold before a single signal reaches your platform

Without these verification and refreshment layers, you’re just automating scraped assumptions.

With proper verification, signals become reliable enough to drive outbound, enrichment, and routing.

Your GTM stack doesn’t need “more data.”
It needs a signal infrastructure beyond simple post engagement

Signalbase

Everyone is talking about signals, but not everyone understands how to leverage them to the fullest 👇 

I've been hammering on this recently, but social engagement signals can take you only so far as SDRs simply miss on the bigger picture 

To put it simply, does this company have any budget ?????

Because GTM is so much more complex than a simple like or comment which btw most of your buyers probably won't execute on as they know that they will be pitch slapped in seconds

Start feeding your platforms, custom Claude environments or workflows with evergreen signals to get the full company context 

👉 Signalbase

Most GTM teams destroy the mailboxes of their ICP right after a single signal lands in their workflow

Job changes. Website visits. G2 reviews. Then they wonder why nobody replies. 🤷‍♂️

The uncomfortable truth?

To make your message really stand out you need to find YOUR custom signal and use it as the ultimate competitive advantage. 

We are talking about that one signal that no competitor is tracking. The one tied directly to the pain only you can solve on top of a list full of already available context

That's exactly what we unpacked in Ep #8 of My First Signal with Kevin White  (Scrunch), representing one of the many seasoned marketing-led GTM leaders building signal-based engines out there!

Here's what we got into 👇

🟧 Why ABM ≠ signal-based GTM (and where teams keep getting this wrong) 🟧 How to find your bespoke signal through jobs-to-be-done research 
🟧 The intent spectrum framework — where to start so you're not overwhelmed 
🟧 Why personalization without relevance is just noise 
🟧 What "right person, right message, right time" actually looks like in practice

If you are a GTM exec lost in the journey of discovering their money-making signal sitting on top of their evergreen ones, then this one is for you 👇 

Let's get practical!

What if you could stop fighting all of the signals coming your way and build a predictable growth engine?

That's exactly what I'll be exploring live this Wednesday at 18:00 CET hosted by Ruadhán himself inside the Clay Club Europe.

Here are a few things we'll go deep on 👇 

→ What a predictable growth engine actually looks like 
→ How to layer real-time intent signals within every part of the sales process while killing it with your marketing efforts
→ A case study where this approach doubled the revenue of a multi-million dollar company 
→ Drilling down the agentic workflows of Francesco & Tanay

and sooo much more to experience when you join us!

Link in the comments 👇

Want to know how all of the AI SDR agents or ChatGPTs for sales teams work? 

Here is what I learned after talking to 40 CEOs of different sales intelligence tooling in Q1👇 

They don’t actually track what’s happening in real time as their data refreshment process looks more like a monthly or weekly shopping spree.

The result for the end user like GTM teams? Making them blast massive campaigns and pray to catch intent by one way or another.

It reminds me a lot of a childhood game called "Broken Phone," as if only 1 person messes up or in that case data point, everything goes wrong.

So in short... AI SDRs buy static datasets with their contact data without any context from other niche API vendors with even more static data. 

What do these datasets tell you?

 👉 Who exists on the market (or at least on paper)
 👉 Where they are
 👉 What do they historically do

But the missing piece to all of these "recommendation" engines? 

 🔶 Who just got promoted or switched their role 
 🔶 Which teams got acquired
 🔶 Who just raised funding

Static data = risk of reaching out to the wrong person
Real movement = getting conversations that actually convert.

Because nobody should waste the time of their SDRs on accounts with no budget or movement behind them. 

Try Signalbase's API

Before purchasing your next API, think of this…

If the vendor claims that their data refreshes every 30 days that's not real-time. That's nothing more than a scheduled download.

And plugging it into your vendor, Clay workflow, or Claude code environment doesn’t make it smarter. In fact, it just makes stale data move faster.

Because a pipeline doesn’t move when a company exists, but when something around that ICP-like org changes.

🔶 A funding round was announced 15 minutes ago
🔶 A VP who switched roles this morning
🔶 An acquisition that just reshuffled priorities

In short, timing + context = opportunity.

Want to know what makes one real signal infrastructure look different?

• Continuously sourcing, not buying chunks of contacts 
• Multi-layer verified as scraping alone can't give you the best results. You also need a verification layer 

More APIs on stale data ≠ better GTM.

It just means you’ll be wrong… at scale.

taplio

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