A data scientist for everyone
Team experience
Where our people have delivered
What we solve
Sound familiar? The Data Advisor solves it.
Today
We see what happened. We don’t know why, or what comes next.
Data AdvisorThe Advisor shows the cause and what comes next, with the risk.
The benefit of a data scientist
A dashboard shows what happened.
What a data scientist gives you:
Root cause
You see why the number moved
What-if
You know what happens if you act
Risk
You know the risk before you decide
What it was worth in published studies
+19%
profit from data-driven pricing¹
+25%
employee tenure from data-driven hiring²
$2.6M
saved per year with a demand forecast³
Studies: ¹ Dubé & Misra 2023 · ² Hoffman, Kahn & Li 2018 · ³ Pinson et al. 2025
Who gets a data scientist
Most decisions never get a Data Scientist. Now they can.
Why most companies have none
Expensive€57,200 average salary¹, before employer costs
¹ Salary: Stepstone 2026, Germany
Why explai closes the gap
A fraction of the costPriced per seat, cancel any month.
Small and mid-sized companies
Enterprises
Already have data scientists?They stay in charge: they configure, evaluate and control the agents, and their work reaches every team.
What the research shows
Where companies stand today
What data science delivers
How we deliver
What you get, and what you keep
Two ways in
The same advisor. Two doors, depending on who you are.
Business uses the Advisor. Data teams configure, evaluate and control it. Pick the page that matches how you work.
Data Advisor
A reliable, tailored AI advisor for your decisions
Would you take the last AI answer without re-checking it? The Advisor knows your data and your company logic: root causes, forecasts, and recommendations you can trust.
For business decision-makers →WorkbenchManufacture a reliable advisor. Multiply your reach.
Forward-deployed data science plus a Workbench to configure, evaluate, release and control agents, so the business gets a personal analyst and you keep quality.
For data & analytics teams →Who it’s for
A data scientist on calls that used to wait, or never got one.
Mid-market · no data scientist on the call
The lean operator
“We don’t have a data science bench. The next pricing call still has to be right.”
Sounds like you?
CFO / CEO · direct, founder-speed
Stuck with today
Excel, a dashboard, and other AIs. Big calls get postponed.
Why no data scientist yet
One hire costs a full salary, takes months to find, and still needs data engineering.
What you get
A data scientist on the decisions that move the business: yours to keep
Enterprise · data science for a privileged few
The blocked department
“Only a handful of decisions get a data scientist. The rest wait, or someone guesses.”
Sounds like you?
Business-unit VP · with IT & data science
Stuck with today
BI plus a backlog only specialists can clear. Risky calls wait.
Why no data scientist yet
The central data team is booked for the biggest projects.
What you get
Data science on everyday decisions, taught and proved by your data team
Product feedback
What adopters say
For every team that decides with data, from marketing, sales and finance to product, operations and research. Here’s what adopters say in their own words.
Testimonials
- MarketingNW
Noah WatlingCo-founder, NOSA Partner GbRCustomer analytics “What really won me over about explai is how concrete the analyses get. It tackles exactly the questions we wrestle with at NOSA Partner: Which customer segments are especially valuable? Where is more budget worth spending? And which customers could we deliberately win back? We already have the data for this ourselves. But we could hardly produce analyses at this depth in our day-to-day work. Being able to ask these questions in plain language and actually understand the relationships behind the answers is something I find genuinely powerful. It turns a gut feeling into a clear, well-founded basis for decisions, with concrete starting points for who to target, what to test, and where the opportunities for better results lie.”
- ResearchHM
Hannes MuellerTenured Researcher, IAE-CSIC · Program Director, M.Sc. Data Science for Decision Making, BSE · Principal Investigator, Conflict Forecast & EconAIAcademic research “I used explai on a genuinely hard problem, the link between IMF policies and violence, and watching the agents work was astounding. They even caught that we had forward-filled some variables. I'm really excited to be working with this.”
- Product leadershipTW
Thomas WittlingerChief Product Officer, OWNLY FinTech GmbHData autonomy “As a product manager, I often depended on others for data. explai's focus on autonomy and personal empowerment flips the script.”
- Executive leadershipHG
Heinz-Georg GeisslerCEO, WeLikeU GmbHOnboarding “Using explai was very intuitive and simple — I needed no help on first use. It then proactively flagged specific data-quality issues, so I could quickly and precisely fix them or adjust my analysis settings.”
- FounderGH
Gerald HeydenreichFounder EtherMail & Barcelona Blockchain NetworkUser experience “explai’s user experience is surprisingly easy and different from any analytics tool I have seen.”
explai.com/demo