in prevention

We go out to look for children
who are unprotected.
Our proposal is adaptable to the needs and resources of local governments.
We develop a proactive approach that allows to find 20 times more children and adolescents who suffer in silence.
Through engagement meetings we work with mothers, fathers and caregivers to identify situations of violence and work on positive parenting.

We promote positive parenting strategies with the double objective of fostering a family bond based on affection and communication, and calling attention to those violent practices naturalized in families.

We also provide children with a safe space to express themselves by means of psychological techniques, such as storytelling and projective drawing.

By predictive analytics and machine learning techniques, we developed a model that identifies households with children at risk of violence. Our preliminary results suggest that up to 40% of at-risk children can be identified, i.e. a 20-fold improvement over current detection levels.


Abrazar uses innovative statistical methodologies that make it possible to prevent and identify cases of child violence before they become serious.


By using machine learning techniques instead of waiting for referrals, local governments will be able to use these tools to find children who are at risk and prevent violence.