EMPA - Data & Management Consulting

Senior Consultant

KPMG

As a specialist at KPMG, I advance AI innovations in taxation, develop MVPs through Design Thinking, and strategically lead prototype development for future-oriented solutions.

Specialist

DatafabriQ

As CTO at DatafabriQ, I led the technological direction, built the backend MVP, and coordinated an external team for rapid frontend development.

Chief Technology Officer

cognaize

As a Data Scientist at cognaize, I shaped the technology by developing advanced ML models in Python and enhanced the platform for effective extraction of information from unstructured data.

Data Scientist

ZDF Digital Medienproduktion GmbH

As a working student Data Scientist at ZDF Digital, I significantly contributed to the company's success by developing Machine Learning algorithms for recommendation systems and Computer Vision projects.

TechQuartier

As a Backend Developer, I realized an event-carpooling platform, significantly contributing to its success and third-place finish in a start-up competition by establishing a seamless backend infrastructure and integrating it via REST-API.

TechTalent

Johannes Gutenberg-University Mainz

As a Research Student Assistant in the EUFOOT project, I analyzed the impact of international football events on European identity and presented the findings through an R-Shiny app I developed.

Research Assistnat

Knatsch.com

As a Mediator at Knatsch.com, I facilitated a more harmonious collaboration between parties through effective conflict resolution and open communication.

Mediator

Unstructured data is everywhere—hiding in emails, buried in SharePoint, scattered across OneDrive. Without the right approach, it remains just that: unstructured, unoptimized, and underutilized. 

I help businesses unlock the hidden value in their unstructured data by applying proven strategies for metadata management, automation, and governance. My expertise lies in making sense of vast amounts of information — turning chaos into clarity, risk into compliance, and data into insight.

With a strong focus on OneDrive, SharePoint, and Exchange metadata, I work with organizations to:
→ Classify, tag, and structure unstructured data for better findability and compliance.
→ Enhance governance & security, ensuring sensitive information is properly managed.
→ Extract actionable insights, empowering businesses to make data-driven decisions.

If your organization is struggling with unstructured data management, let’s connect. I’d love to discuss how we can turn your data into a strategic asset.

Yannik Suhre

Founder | Helping startups hire pre-screened devs in 24 hrs.

I’ve spent the last 10+ years building and scaling tech products — including founding and growing two startups to 7-figure revenue, fully bootstrapped.

Along the way, I worked closely with early-stage founders, CTOs, and product teams on one core problem: turning ideas into real, shipped products — without burning time or money.

After helping dozens of startups with product strategy, hiring, and execution, one pattern became obvious:

Great startups aren’t held back by ideas.
They’re held back by slow execution and bad hiring.

Hiring developers the “traditional” way is broken — endless CVs, multiple interviews, long onboarding cycles… and still no certainty you hired the right person.

So I built Y Interval — a dev partner designed specifically for startups.

We combine:
• Startup-grade product thinking
• Vetted senior engineers who work like in-house
• Fast MVP builds without over-engineering
• Flexible, no-drama engagement models

The result:
Startups ship faster, hire smarter, and scale with confidence.

Since then, I’ve worked with 100+ startups and product teams, from early MVP stage to scale-ups, helping them:
• Build and launch MVPs
• Extend or replace in-house dev teams
• Execute AI, web, and full-stack products properly

Credibility highlights:
→ Built and exited two tech startups
→ Generated 7-figure revenue across services businesses
→ Helped 100+ startups build and scale remote dev teams
→ Worked with teams connected to Microsoft, Meta, and other large orgs
→ Built a media + newsletter brand read by 50K+ founders

If you’re a founder or CTO:
• Building an MVP
• Struggling with dev execution
• Or tired of unreliable agencies

Happy to connect and share how we usually help. Just connect via DMs here or check out our website: yinterval.com

Samee Hassan

One thing we’ve learned building products across startups:
Speed without feedback is dangerous.

You can ship fast.
Push updates weekly.
Close tickets quickly.

But if real users aren’t responding, you’re just accelerating in the wrong direction.

The best teams don’t just move quickly.
They close loops quickly.
Ship.
Measure.
Learn.
Adjust.

Small loops beat big launches.

We’ve seen startups spend 4 months building something “big” that could’ve been validated in 2 weeks with a smaller version.

Momentum doesn’t come from volume.
It comes from tight feedback cycles.

If progress feels heavy right now, it’s worth asking:
Are we building… or are we learning?

Curious how other teams here structure their feedback loops.

Helping startups build better products. Deep in AI and data.

There’s a shift happening in how products get built.

Not just faster - but different.

In the past, building an app meant:
architects and specs,
wiring up frontend and backend,
deploying infrastructure,
and weeks of setup before anything worked.

Now, with tools like Zoer AI, that whole journey feels reimagined.

Instead of separate tools and pile of tickets, you describe your idea in plain language - what you want your product to do - and Zoer generates the whole thing:
A real frontend.
A real backend.
Database structures.
Authentication.
Business logic.
Everything.

It’s not just a “page builder.”
It’s a full-stack app builder powered by AI - capable of producing deployable applications without you having to wire together five different services.

What’s fascinating here isn’t the speed - it’s the shift in who can ship.
Founders and small teams with ideas can now build complete apps without pulling in a full engineering crew first.

We’ve been watching this space closely because it changes how we think about MVPs, prototypes, and early validation.

Instead of weeks of planning and hiring, you can go from idea → prototype → live in hours.

NOT replacing engineers - empowering teams to focus on problem solving, not boilerplate.

Curious how others here are thinking about AI tools and app builders - are you building with them yet, experimenting, or still on the sidelines?

CHECK IT OUT: https://tryit.cc/Z5HSip

In 2012, two students had a wild idea:

What if design worked like Google Docs?

Adobe laughed.

They had 22,000 employees.

Figma had 20.

But by 2022, Adobe offered them $20B to buy their silence.

Too late.

Here’s how Figma humbled a giant with 1/100th the team - and what founders can learn from it:

🔹 Figma didn’t out-feature Adobe. They out-architected them.
 While Adobe stacked features on 20-year-old code, Figma rebuilt from scratch. Their multiplayer engine used constraint solvers and custom WASM rendering.

🔹 They built infra before they built UI.
 Figma spent 4 years pre-launch.
 Why? Multiplayer design isn’t a UI trick — it’s an architecture problem.
 They solved it with CRDTs, OT, and sub-50ms sync before showing a landing page.

🔹 They targeted teams, not just designers.
 – PMs loved comments
 – Devs loved inspect mode
 – Growth teams loved version history
 Figma stuck because it worked across the stack.

🔹 They gave devs a playground.
 Plugins. APIs. Widgets.
 Instead of locking devs out, they opened the gates — and the community built everything.

🔹 They didn’t chase distribution — they earned it.
 By 2021:
 – $400M+ ARR
 – 80% of YC startups by default
 – Adobe panicked


If you're building against giants:

-Don’t out-feature them.
-Out-architect them.
-Out-culture them.
-Outflow them.

----
👇 👇👇

P.S 
If you're a founder/CTO who's looking to hire devs, let's connect.

we help ramp up dev capacity, speed up product and MVP development, automate processes, and cut costs.

Most GTM teams still use AI like an intern they have to babysit.

Prompt.
Wait.
Prompt again.

Hope something useful happens.

That’s fine for experiments.

It’s terrible for pipeline.

The real unlock is when AI stops acting like a chatbot and starts acting like a colleague.

That’s what makes this interesting:

FlashClaw is built as a 24/7 proactive agent for B2B teams. 

It runs on a heartbeat, checks for signals EVERY 30 minutes, and executes GTM playbooks without waiting around for someone to poke it first. 

The shift here is simple: from reactive chat to proactive execution.

A few GTM use cases where this gets very real, very fast:
- Spot buying signals and trigger the next step before the rep even notices
- Run account research and enrichment on autopilot
- Push reminders, updates, and actions into the tools your team already uses
- Keep repetitive workflows moving even when nobody is online

What I like about the angle is this:
If you want flexibility, you can explore OpenClaw and build around the proactive GTM workflow concept yourself.

If you want the more practical version for an ACTUAL team, FlashClaw is the secure, hosted route. Same big idea, less duct tape, less babysitting, less “who’s maintaining this thing?” energy.

That’s where a lot of AI products are heading next.

Not better chat.

Better teammates.

CHECK OUT: https://tryit.cc/m60iaup

taplio

The Battle

Yannik Suhre

Samee Hassan

Followers

Posts

Engagements

Likes

Performance ScoreSamee Hassan's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Yannik Suhre

Samee Hassan

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Samee Hassan's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreSamee Hassan's LinkedIn Performance