Maternal Health AI Startup Matresa Raises £315,000 to Tackle the UK Maternal Health Crisis

Maternal health AI company Matresa has raised £315,000 in pre-seed funding to accelerate the development and rollout of its personalised, preventative maternal health platform. The investment comes at a critical time for maternal health in the UK, with maternal mortality rates now at their highest level in more than two decades and growing evidence of gaps in support for mothers before and after childbirth.

Set to launch this summer, the Matresa platform provides continuous, personalised support for women throughout the maternal journey, from preconception through pregnancy and into postpartum recovery.

Addressing the UK Maternal Health Crisis

One in five women in the UK experiences maternal mental health conditions or serious complications following childbirth. Many of these outcomes are preventable with earlier intervention and better continuity of care, yet maternal services remain fragmented and reactive. Preventable maternal health problems are estimated to cost the UK economy between £13 and £15 billion annually through healthcare spending, lost productivity and long-term social impact.

Matresa was founded to address these systemic gaps by shifting maternal care from crisis response to proactive prevention.

From Nurse to Founder: The Origin of Matresa

Matresa was founded by former nurse Mari-Carmen Sanchez-Morris after witnessing the lack of structured support available to mothers both clinically and socially. Her experience working in paediatric intensive care, combined with her own journey through motherhood, revealed how maternal health needs often go unseen once a baby is born.

She created Matresa to provide mothers with personalised, continuous care during matrescence — the complex transition into motherhood that spans physical, psychological and social change.

AI-Driven, Preventative Maternal Health Support

Matresa combines clinical expertise, behavioural science and AI-driven insights to deliver personalised maternal health support across pregnancy and early parenthood.

The platform focuses on three high-risk periods:

  • maternity leave

  • the return-to-work transition

  • early workforce re-entry

By supporting mothers during these phases, Matresa helps reduce health risks, workforce drop-out and long-term complications.

Supporting Employers and Maternal Workforce Retention

Maternal health challenges directly affect workforce participation. Currently, one in three mothers leaves the workforce within a year of childbirth, creating significant economic and organisational impact.

Replacing a skilled female employee post-maternity can cost employers between £30,000 and £150,000, highlighting the need for preventative maternal support in workplaces.

In a pilot with a global professional services firm, Matresa demonstrated measurable outcomes:

  • wellbeing scores increased from 5.2 to 7.8

  • productivity rose by 20%

  • energy and mood improved by 50%

These results show how early maternal support can improve both health outcomes and workforce retention.

Female Founder Funding Gap

The funding also highlights persistent inequality in venture investment. All-female founder teams received just 2.8% of funding in 2024–2025, making Matresa’s raise a notable milestone in women-led health innovation.

A Preventative Future for Maternal Health

Mari-Carmen Sanchez-Morris, founder of Matresa, said:

“Poor maternal healthcare doesn’t exist in isolation. It affects women’s health, careers, families and the wider economy. Tailored maternal care isn’t a privilege — it’s a necessity. Mothers deserve to feel safe and supported, and we must do more to tackle this crisis.”

Looking Ahead

Launching in 2026, Matresa aims to transform maternal health support across healthcare, workplaces and communities by delivering personalised, continuous and preventative care at scale. By connecting physical, psychological and socioeconomic factors in one platform, Matresa is helping build a future where better maternal outcomes are expected, not exceptional.

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