Hello everyone, I'm Christian van Gils, Co-founder of PulseBoard.
For my entire career, I've been a dedicated entrepreneur. I successfully built and ran a media agency for 12.5 years, followed by a software company that I recently and successfully exited after 22 years.
Now, I'm redirecting all of that experience, knowledge, and entrepreneurial drive toward a single mission: making 2026 a healthier year by focusing on people.
I ve been talking to a bunch of creators lately and noticed a pattern. Most spend a surprising amount of time searching through Google Trends, YouTube trending, X, Reddit, etc just to find one or two solid content ideas.
Some said they lose 1 to 2 hours a day. Others feel like they keep spotting trends only after they re already saturated.
Meku just crossed 10,000 registered users, it's a big milestone for us and hits different
The AI coding and dev tool space is loud and very competitive, but seeing so many people try Meku and actually stay shows we re building something that genuinely helps devs and teams ship faster and build better web apps
Massive love to the Meku team for grinding and polishing every day, and heartfelt thanks to our early users for trusting what we re creating
The year is almost done, and I have started to be curious about what could be stopping companies from adopting AI for their customer support services?? From my experience, I can tell - fear, fear of losing control. Support leaders worry that AI will say the wrong thing, sound off-brand, frustrate customers, or create more cleanup work for the team. Until they see that an AI agent can learn from their own knowledge base, follow rules, escalate when needed, and stay accurate, they hesitate. Once they realize it can actually reduce workload without breaking trust, adoption becomes much easier. What do you think? Do you agree with me?
Tejas here, 19 years old, founder of @Dimension, a powerful AI co-worker that gets work done for you before you need to think about it. We raised $2M+ from founders of @GitHub, @Pitch, @Netlify, @Framer , @Postman , @WorkOS , Frame, and more, and we're launching to the world today! AMA.
Introducing The Unfiltered Data Club - a Slack community for data folks who want to vent, rant, laugh, cry, share memes, ask for help, or confess their most chaotic pipeline moments without judgment.
If you ve ever stared at a failing SQL query for an hour, fought with messy CSVs, or questioned your life choices because a dashboard refused to load, this is your new home.
The last 14 days have been mental. Here s why Pretty Prompt has grown faster in two weeks than our previous product did in 14 months . Crazy. Highlights: - 36 new reviews. More than the last 3 months combined. - 1,000+ new paying users signed up. Still can t believe I m typing that. - We gave a talk at Stripe about our story and using LLMs in production. - And on our side, we have been shipping like crazy. This week is Launch Week. Major updates. New integrations. Small but powerful tweaks. Super excited What people are saying: - My productivity has skyrocketed. It just makes sense the second you use it." - Honestly, it's one of those tools that instantly becomes part of your everyday stack. - No friction, no learning curve. Just genuinely better outputs..." - "The time savings compound quickly." - "The output I'm getting from Pretty Prompt is a million billion times better than what I was getting before. Biggest focus: - Refine v2 better refinement, multiple options, context. - Team Plans shared libraries, multi-user support. - Lovable Integration site-specific prompts for Vibe coding Obsessed with making every day better than the last.
And it all started right here in Product Hunt. The best place to launch new products.
At least it was for us.
Your feedback drives what we're building. Try Pretty Prompt and let me know your thoughts!
We've built Querri with the mission of making data work accessible to everyone. Over the last months, we have trained it to be more business-oriented. One of the most significant pain points we have heard is scattered data, so we have built in more connectors to help unify the data view. What are your biggest data challenges? Which connectors would you love to see in an AI Data analytics tool, so you can see all your data, build dashboards, and track your business KPIs in one platform?
I realised how important videos are in search results.
This and the previous week, we reached out to many creators for custom videos on various topics that include the client's product. (I gained some overview about prices for such a video and need to say that if things go well, it can be a good investment in the long term).
Our What s your biggest data frustration? thread got way more love than I expected.
Reading through it, it hit me: everyone needs a place to rant about their data chaos - dirty spreadsheets, broken dashboards, wild analytics expectations.
So what if we created The Venting Room? A community where data people can share rants, memes, and maybe even fixes together.
Many brands have their long-standing mascots (McDonald's, Mr Clean, Michelin), etc. But with the development of AI, physical forms are moving online, and AI avatars look promising in this.
On one hand, it feels less human (authentic), on the other hand, AI influencers are a "cheaper" solution.
We ve always aimed to make data ridiculously easy to use. This release takes a massive step toward that goal. We ve built an entire data workflow that lets you connect your data, clean it, analyze it, and share it, all through a simple conversational interface. For me, that s the most exciting part. This is a true data platform workflow, built for everyone.
Let s break down what s new and why it matters so much.
The idea for Querri, an AI-powered data analytics platform, came to life in early 2023. By the end of that year, we had a very basic version live, and in the spring of 2024, we launched our first MVP. It was powerful but far from user-friendly. Users had to know exactly what questions to ask, and there were no integrations or dashboards to make the experience seamless. We quickly realized that if we wanted to make data analytics truly accessible, we needed to rethink everything.
By the spring of 2025, we launched a completely revamped Querri. This version made data analysis feel more like a conversation than a guessing game. Querri could evaluate datasets, provide quick overviews, and offer tailored suggestions for analysis. We also trained it to be business-focused, offering insights that aligned with real-world business needs. But even then, we knew we weren t done. There were still no dashboards, and integration options were limited.
Fast forward to today, and Querri has evolved into a true end-to-end data analytics solution. With robust integrations like Google Drive, PostgreSQL, and MySQL, users can now pull data directly from the source. Creating charts, graphs, and shareable dashboards is as simple as a few clicks. Querri doesn t just stop there...it offers follow-up suggestions at every step, helping non-data scientists uncover deeper insights or explore new directions with ease.
Every time we thought we had made data analytics easier, we discovered new challenges to tackle. Building Querri has been a journey of constant learning and iteration. Our mission is to make data analytics accessible to everyone, but we know there s always room to improve.
Given all the AI tools out there today, what is one challenge with data that still remains unsolved? why do you think it hasn't/can't be solved easily.
When @daveaingram came up with the idea for Querri in the spring of 2023, the term "AI Data Analyst" wasn t even a thing. AI itself was far from mainstream. Even when we launched our first MVP in the spring of 2024, many larger companies still saw AI as "fringe." Fast forward to the fall of 2025, and not only is every tech business racing to incorporate AI, but entirely new product categories like "AI Data Analytics Tools" have emerged. So, we re proudly leaning into that term.
This is our second Product Hunt launch, but it s the first time Querri can truly help users through the entire data analytics cycle from start to finish.
