In today’s fast-moving world of insights, not all data challenges can be solved through traditional sample collection. Whether you're tackling low-incidence populations, looking to augment datasets, or testing scenarios at scale, Correlix helps you go further — faster — with confidence.
Built by DataDiggers, Correlix delivers high-integrity synthetic data that reflects real-world behavior without ever compromising on privacy, reliability, or representativeness.
Unlike generic data simulators, Correlix is:
Rooted in domain-specific logic
Trained on real, validated research inputs
Designed with the rigor market research demands.
That means you're not just generating numbers — you're generating credible, actionable synthetic insights.
Correlix is a statistical and machine learning engine designed to generate synthetic data that mirrors real-world patterns. It helps you explore outcomes, test hypotheses, and strengthen models — especially when observed data is sparse, sensitive, or costly to obtain.
Talk to a SpecialistEven the best samples have limits.
Synthetic data can:
Correct biases by enriching underrepresented segments
Simulate new market conditions before they happen
Scale insights without incurring additional fieldwork costs
Preserve privacy when handling sensitive respondent profiles
Speed up modeling when working with incomplete datasets
With Correlix, these capabilities are built-in — not bolted on. We combine advanced regression models, pattern recognition, and statistical bootstrapping to ensure that your synthetic datasets remain valid, traceable, and interpretable.
Correlix is ideal for:
Needing robust data augmentation for concept testing, segmentation, or modeling in hard-to-reach audiences
Running simulations or stress-testing scenarios before go-to-market
Modeling potential user journeys or purchasing behavior
Forecasting the impact of changes in regulation or public behavior
Training and validating ML models without risking data privacy
Let’s say you’re running a study on high-net-worth crypto investors in Southeast Asia — a notoriously tough group to reach. Or you’re modeling future food choices under climate change scenarios. In these cases, Correlix gives you the flexibility of simulation with the credibility of empirical logic.
All synthetic datasets are:
Privacy-safe and GDPR-compliant
Built from real, validated data patterns (often from our proprietary MyVoice panel)
Customizable to your modeling goals and research needs
Auditable, so you know where the logic comes from
Our models undergo regular calibration and validation against actual fieldwork, ensuring the synthetic insights remain relevant, explainable, and decision-ready.
Correlix never re-identifies individuals or replicates actual survey answers. Instead, it builds a statistical representation of reality based on trends, relationships, and constraints observed in high-quality input data.
Correlix works alongside your existing insights. Whether you use it to enhance survey data, fill in gaps, or run predictive models, it’s here to expand your analytical toolkit — not override it.
Need to simulate multiple market scenarios before fielding a real survey?
Correlix works seamlessly with Modeliq and Syntheo, our other synthetic insight engines.
Want to bring synthetic and real data together in one place?
Feed Correlix outputs into Brainactive and unlock streamlined analysis across both sources.
In an era where speed, scale, and privacy matter more than ever, synthetic data is not a shortcut — it’s a strategic advantage.
Looking to learn more about the difference between synthetic personas and synthetic data?
Explore Syntheo to meet your AI-driven digital respondents.
