DeepTech Talks BCN: From Data Autonomy to Adaptive AI

From Data Autonomy to Adaptive AI: Building Systems That Change How Decisions Get Made

DOORS OPEN: 18:30
TALKS START: 19:00
NETWORKING: 20:00 - 21:30

Our Speakers

Marta Expósito Ventura, PhD, Head of Data, Stark Future
Africa Perianez, Co-founder & CEO, Causal Foundry

Marta Esposito - From ticket queues to data autonomy - engineering the shift

Marta Esposito is Head of Data at Stark Future, an electric motorcycle company building high-performance, connected vehicles at the intersection of hardware, software, manufacturing and data.
In her talk, Marta will explore what it takes to move a data function away from reactive ticket queues and towards a more autonomous operating model. As connected products generate increasingly rich streams of operational, product and user data, the role of data teams changes: from responding to requests, to enabling better decisions across the organisation.
Her session will look at the engineering, organisational and cultural shift behind data autonomy: how teams structure data work, prioritise internal demand, build trust in data products and move closer to the real systems they support.

Africa Perianez - Designing AI for imperfect conditions

Africa Perianez is Co-founder and CEO of Causal Foundry, where she leads a team of engineers and AI scientists building reinforcement learning and personalisation technologies for real-world operational decision-making.
Her work focuses on adaptive AI infrastructure that supports decisions across healthcare, logistics, behavioural nudging, demand forecasting, stockout prevention and resource allocation. Causal Foundry works with global partners including the Gates Foundation, Google.org, GAVI, Lilly and Johnson & Johnson, applying AI in environments where decisions are complex, resources are constrained and impact matters.
In this talk, Africa will explore how AI systems move beyond prediction and dashboards into adaptive decision support. What does it take to build systems that can operate across changing contexts, local constraints and human behaviour? And how do you design AI that supports better decisions without pretending the real world is cleaner than it is?

What’s In It For You?

Some of the most interesting work in AI today is not just about building more powerful models. It is about turning data, machine learning and decision intelligence into systems that people and organisations can actually use.
In this DeepTech Talks edition, Marta and Africa will explore two complementary sides of applied AI: how data teams become more autonomous inside complex organisations, and how adaptive AI systems support operational decisions in the real world.
You’ll hear about:

• How data teams move from reactive service models to autonomous data products
• What it takes to build AI systems that support operational decision-making
• How reinforcement learning and personalisation can be applied beyond consumer tech
• The gap between dashboards, predictions and decisions that actually change outcomes
• How technical teams work with messy real-world systems, constraints and stakeholders

Expect a grounded conversation about AI that becomes s part of how organisations sense, decide and act.

Who Should Come?

• Data scientists, ML engineers and AI engineers
• Data leaders, analytics leaders and engineering managers
• Product leaders working with data-heavy or AI-enabled systems
• Deep tech founders and technical operators
• People working across healthtech, mobility, logistics, manufacturing or decision intelligence
• Anyone curious about how applied AI becomes operational infrastructure

Extras

We’ll have food and drinks. 🍷🍕
Come ready to meet engineers, founders, esearchers, data leaders and technology builders working on the next generation of applied AI systems.
Spaces are limited, so grab your spot on Meetup while you can.
Brought to you by DeepTech Recruitment & Cloudworks.

The organisers and venue reserve the right to refuse admission or entry and shall not be held liable for any incidents, losses or damages occurring during the event.