Not every pitch comes with a green light for fieldwork. Not every brief comes with time to wait. And not every client is ready to rerun an entire survey just to ask three more questions.

If you’ve ever faced that tension, tight timeline, limited data, high expectations, you’re not alone.

Agencies from Berlin to Bratislava are exploring how to scale research, simulate insights, and reuse existing datawithout losing trust or control. Synthetic panels (aka AI respondents) offer a simple promise:

You stay in charge. We power what’s behind.

The Real Bottleneck Isn’t Technology. It’s Time.

Most agencies already have the tools. What’s missing is capacity.
You don’t need another flashy dashboard or a new way to chart Likert scales. You need:

• Faster access to relevant opinions

• Smarter ways to reuse what you already know

• Flexible capacity to test more without overloading your team

Agencies aren’t suffering from a lack of insight, they’re suffering from overhead bloat and rework. The same fieldwork is repeated to answer adjacent questions. Teams are stretched chasing feedback that could have been simulated, modeled, or explored with what already exists.

Here’s a hard truth: Most agencies are sitting on years of underused data.

• Segmentations no longer activated

• Trackers archived without synthesis

• Open-ended interviews whose insights die in transcripts

What if agencies treated their knowledge base as a living asset?
What if that old campaign pretest could inform the next pitch, or that unused persona work could model reactions to a new concept without recontacting a single respondent?

In short, what if we stopped thinking of research as a one-off event and started treating it like a scalable system?

Built for Agencies, Not to Replace Them

Let’s be real. Plenty of vendors talk about “AI in research.” But most of them throw ChatGPT on a deck and call it innovation.

At Lakmoos, we’ve spent the last three years building agency-grade AI panels:

• Powered by hybrid neuro-symbolic models (not black box LLMs)

• Trained privately on your data — you stay in control

• Designed to fit your methods, from KANO to MaxDiff, Conjoint to open coding

• Tested in 15+ large-scale validation pilots

• With proven 95%+ accuracy and full auditability

Whether you’re a quant-heavy research agency, a creative studio under pitch pressure, or a media team needing real-time sentiment, we adapt to your workflows, not the other way around.

Turn Single-Use Surveys into Lasting Intelligence

Most agencies are sitting on gold:

• Old trackers

• Past segmentation studies

• Interview transcripts

• Lost briefs with half-run surveys

Lakmoos helps you upcycle that knowledge into a custom AI panel. That means:

• No new fieldwork just to run one more cross-tab

• No delays waiting for next month’s tracker wave

• No asking “can we afford to ask this?” ever again

💡 Use it when…

• A client wants Gen Alpha insights but you’ve only got Gen Z data

• You want to test two more concepts by Friday

• You’re sitting on a decade of data no one’s touched since 2017

Our models don’t just give you responses. They learn, adapt, and evolve with your needs.

Your agency panel can:

• Suggest next questions based on early results

• Run comparative simulations for new ideas

• Recommend segments most likely to switch

• Automatically generate charts and reporting summaries

We call this Agentic AI, because it doesn’t stop at answers. It plans, runs, and refines workflows alongside you.

Synthetic Doesn’t Mean Fake, It Means Repeatable

In other industries, synthetic means control. Scale. Simulation.

• Finance uses synthetic instruments to model risk.

• Pharma uses synthetic trials to augment testing.

• Product teams use synthetic personas to run usability tests overnight.

But in market research, we’re still clinging to fieldwork as the only source of truth.

It’s time to expand the definition. Synthetic samples — when done right — don’t replace human understanding. They expand what’s possible with it. They allow you to ask new questions without starting from scratch. They help teams test more ideas before anyone spends a euro on production or placement. And, crucially: they’re not here to replace researchers. They’re here to multiply their judgment.

AI in research isn’t a wave to be “caught.” It’s a tide that’s already reshaping the beach. Agencies that act now will shape the norms of tomorrow.