Supercharge your data's value

Supercharge your data's value

Supercharge your data's value

We profit-share with social impact organizations through licensing privacy-preserving synthetic social impact data retaining the statistical properties of original data while adjusting for small data sizes.

We profit-share with social impact organizations through licensing privacy-preserving synthetic social impact data retaining the statistical properties of original data while adjusting for small data sizes.

What is Synthetic Data?

What is Synthetic Data?

Synthetic Data is artificially generated information mirroring the statistical patterns and relationships found in real, ‘original’ data without containing any actual records from the original data. Unlike statistically enriched data which preserves original data, for instance inputting a missing individual income value based on their education level, synthetic data generates completely new artificial records with prior information on the statistical properties of the original data.

These fundamental differences make synthetic data particularly valuable for sharing with partners, collaborators, grantees, funders, etc.; overcoming data scarcity scenarios; or testing new analytical methods while protecting individual privacy, since no real person’s information is included in the data.

Our Approach

Our Approach

Technical and domain expertise you need

Our deep expertise in quantitative ESG investing and impact measurement enables us to create sustainable funding streams through innovative data licensing models. We’re tailoring the investment data business model to the unique needs of organizations like yours in the social impact sector.

Strategic partnership tailored to your organization

We engage with our values of co-creation and accountability, combining bespoke data strategy with responsive, multidisciplinary social impact analysis for sustainable revenue growth and impact amplification alike. We empower organizations to build self-sustaining data capabilities, with a goal for most partners to realize substantive progress within a year.

FREQUENTLY ASKED

FREQUENTLY ASKED

FREQUENTLY ASKED

Questions?
We have the answers

Questions? We have the answers

What are Chromatic’s approaches to privacy when generating synthetic data?

What are Chromatic’s approaches to privacy when generating synthetic data?

What are Chromatic’s approaches to privacy when generating synthetic data?

How does Chromatic protect its data?

How does Chromatic protect its data?

How does Chromatic protect its data?

What types of data can be synthesized?

What types of data can be synthesized?

What types of data can be synthesized?

How can Chromatic enforce our requirements on data quality?

How can Chromatic enforce our requirements on data quality?

How can Chromatic enforce our requirements on data quality?

Is it possible to account for types of bias inherent to the ‘original’ data the synthetic data is generated from?

Is it possible to account for types of bias inherent to the ‘original’ data the synthetic data is generated from?

Is it possible to account for types of bias inherent to the ‘original’ data the synthetic data is generated from?