Our Vision in Action: How We're Building the Future of AI, Today

At Sherpa.ai, we believe the future of artificial intelligence won't be defined by who owns the most data, but by who can connect intelligence in the most secure and meaningful way.

For years, the AI revolution has been fueled by a simple, but broken, model: gather vast amounts of sensitive data into one place and hope it stays secure. This created a paradox—a constant battle between innovation and privacy.

We knew there had to be a better way.

From our headquarters in Bilbao, Spain, we have pioneered a new path forward. Our solution is a sophisticated privacy-preserving AI platform built on the transformative power of federated learning. We didn't just create another AI tool; we built a new framework for trust, enabling organizations to collaborate and solve humanity's biggest challenges without ever compromising their most valuable asset: their data.

This isn't just a vision for the future; it's happening right now. This is our guide to the real-world applications of our technology.

We want to take you beyond the buzzwords and show you exactly how we're helping our partners in finance, healthcare, manufacturing, and beyond build a smarter, safer, and more private world.

Part 1: The Sherpa.ai Engine: Our Approach to Federated Learning

To understand the impact of our work, you first need to understand our core technology. The principle is elegant: instead of forcing data to travel to the model, our platform brings the AI model securely to the data.

But behind this simplicity lies a sophisticated orchestration of cryptography, distributed computing, and machine learning that we have perfected. Here’s a look inside the Sherpa.ai engine:

1. Model Initialization: Our journey begins when we, or our clients, design a base AI model for a specific task—like identifying early signs of a rare disease from medical scans.

2. Secure Distribution: We securely deploy this model to each participating organization, or "node," in the federation. These nodes—be they hospitals, banks, or factories—are the sovereign owners of their data.

3. Private, Local Training: The AI model trains exclusively within the secure, firewalled environment of each node. It learns the unique patterns and insights from that local dataset, while the raw data never moves an inch.

4. Encrypted Learnings: Here is where our privacy promise is forged. Each node sends back only an encrypted summary of what the model learned. These "updates" are abstract mathematical representations, not the data itself.

5. Secure Aggregation: This is our secret sauce. Our platform uses state-of-the-art cryptographic techniques like Secure Multi-Party Computation (SMPC). This allows our orchestrator to intelligently combine all the encrypted learnings to forge a vastly superior global model, but without ever decrypting or "seeing" any individual update. It's the digital equivalent of building a masterpiece while blindfolded, ensuring no single participant's contribution can be reverse-engineered.

6. Continuous Improvement: We send the newly strengthened global model back to all the nodes, and the cycle repeats. With each iteration, the collective model becomes exponentially more intelligent, learning from the diverse experiences of every participant.

To make our platform ironclad, we integrate Differential Privacy, a sophisticated method that adds a tiny amount of statistical noise. This makes it mathematically impossible to trace any learning in the final model back to a single individual's data point, providing the ultimate layer of anonymization.

Our platform is a living embodiment of the "Privacy-by-Design" philosophy, a principle that is not just good ethics but is also the foundation of modern data regulations like Europe's GDPR and the landmark EU AI Act.

Part 2: Transforming Finance: How We’re Building a More Secure Financial World

The financial industry is built on trust. We partner with these institutions to fortify that trust with next-generation AI, helping them combat crime and serve their customers better.

Application 1: Our United Front Against Financial Crime

The Challenge: Financial criminals operate in sophisticated, global networks, exploiting the information silos between banks. A money laundering operation can span multiple institutions and countries, with each bank only seeing a tiny, seemingly innocent piece of the puzzle. This global problem, costing the economy trillions annually according to the United Nations, requires a networked defense.

The Sherpa.ai Solution: We enable a consortium of financial institutions to fight back as one.

• Our Goal: To train a shared, market-leading Anti-Money Laundering (AML) model that can see across the entire system.

• How We Do It:

  • We deploy our AML model to each participating bank.

  • The model trains privately on their confidential transaction data, learning the unique behavioral patterns of their customers.

  • Encrypted learnings about suspicious activity patterns are returned to our secure aggregator.

  • The global model is updated, now armed with a panoramic view of how illicit funds flow between institutions.

• The Impact We Deliver:

  • Unmasking Criminal Networks: Our federated model can flag a series of small deposits across five different banks as a single, coordinated structuring scheme—a feat impossible for any single institution.

  • Slashing False Positives: We help banks cut through the noise. Legacy systems produce a flood of false alerts, costing millions in manual review hours. Our smarter, context-aware model has been shown to reduce these false positives by over 30%, freeing up investigators to focus on real threats.

  • Proactive Defense: When a new fraud technique emerges at one bank, our platform allows that defensive intelligence to be instantly and anonymously shared with all members of the federation.

Application 2: Engineering Fair and Personalized Insurance

The Challenge: The core of insurance is pricing risk, but traditional models often rely on broad, and sometimes biased, demographic data. The data from IoT devices and vehicle telematics can create fairer, Usage-Based Insurance (UBI), but customers are rightfully hesitant to stream their every move to a corporate server.

The Sherpa.ai Solution: We're creating ecosystems of trust between car manufacturers, insurers, and drivers.

• Our Goal: To help build the industry's most accurate and private auto insurance risk model.

• How We Do It:

  • Our model can run directly on a driver's smartphone or within their car's onboard computer (at the edge).

  • It learns locally from telematics data—like braking habits and speed—which never leaves the user's personal device.

  • In parallel, insurance partners in the federation train the model on their anonymized claims data, teaching it the real-world outcomes of certain driving behaviors.

• The Impact We Deliver:

  • Truly Fair Pricing: We empower insurers to offer premiums based on how someone actually drives, not who they are. Safe drivers are rewarded, and risk is priced more equitably.

  • Privacy as a Feature: Customers get the financial benefits of personalization without the privacy trade-off.

  • Fueling Innovation: Our platform gives insurers the trusted foundation they need to build the next generation of products, from "pay-as-you-drive" models to safe-driving incentive programs.

Explore how we're building trust in the financial sector on our blog: Introdution to AI in finance

Part 3: Advancing Healthcare: Our Mission to Accelerate Medical Breakthroughs

In healthcare, data holds the key to saving lives, but it is also our most personal and sensitive information. We see it as our responsibility to provide the technology that can unlock this life-saving potential while offering absolute protection.

Application 1: Powering Global Collaboration to Diagnose Rare Diseases

The Challenge: A rare disease isn't rare to the 300 million people who live with one. For doctors, the greatest obstacle is a lack of data. A single hospital might only see a few cases, not nearly enough to train an AI that can recognize the disease's subtle signs.

The Sherpa.ai Solution: This is one of our proudest contributions. We have provided our platform for vital collaborations, including one between the U.S. National Institutes of Health (NIH) and University College London (UCL).

• Our Goal: To enable the world's leading researchers to train a diagnostic AI model that can spot a rare disease years earlier than was previously possible.

• How We Do It:

  • We help form a research federation that connects top pediatric hospitals and research centers across continents.

  • Our diagnostic AI model is deployed to each institution, where it trains on their private patient scans (MRIs, CTs) and health records.

  • The model learns from an incredibly diverse patient population, and the aggregated learnings create a global model with a level of expertise that surpasses any single institution.

• The Impact We Deliver:

  • Saving Precious Time: Patients with rare diseases often endure a "diagnostic odyssey" that lasts 5-7 years. The federated AI models we enable can slash this time, allowing for life-altering interventions to begin sooner.

  • Democratizing Expertise: We help bottle the collective knowledge of the world's best specialists into an AI tool. This tool can then be used by doctors in smaller, regional hospitals, giving them access to world-class diagnostic support and raising the standard of care for everyone. For more on this global challenge, see the World Health Organization's initiatives.

Application 2: Reinventing the Pharmaceutical Clinical Trial

The Challenge: The journey of a new drug from lab to patient is incredibly long and expensive, largely due to the complexity of multi-site clinical trials. Gathering and analyzing data from dozens of global sites is a logistical and privacy nightmare.

The Sherpa.ai Solution: We partner with pharmaceutical innovators to make clinical trials faster, safer, and more efficient.

• Our Goal: To provide a real-time, privacy-preserving view of a drug trial's efficacy and safety across all participating sites.

• How We Do It:

  • Our predictive model is deployed to each of the hospitals participating in the trial.

  • It trains locally on patient data as it's collected, learning to spot early indicators of adverse reactions or, conversely, exceptional patient responses.

• The Impact We Deliver:

  • Prioritizing Patient Safety: Our system can flag correlated adverse events across multiple sites almost instantly, enabling researchers to intervene much faster than with traditional methods.

  • Smarter, Faster Trials: By understanding which patient profiles are responding best in real-time, researchers can adapt trial protocols on the fly, focusing their efforts where they will be most effective.

  • Accelerating Hope: By streamlining data analysis while ensuring impeccable privacy, we help our partners reduce the time it takes to get life-saving drugs to the patients who need them.

Discover more on our vision for health on our blog: Transforming the healthcare industry with federated learning

Part 4: Engineering the Smart Industries of Tomorrow

The physical world—from factory floors to city streets—is now a data-rich environment. Our platform helps harness this data to build more efficient, sustainable, and intelligent systems.

Application 1: Building Self-Aware Factories with Predictive Maintenance

The Challenge: In manufacturing, unplanned downtime is a multi-billion-dollar problem. Predictive maintenance AI can prevent this, but the best models need to learn from a wide variety of equipment failures—more than any single company typically experiences.

The Sherpa.ai Solution: We create collaborative ecosystems between equipment manufacturers and their customers.

• Our Goal: To build the world's most accurate predictive model for critical industrial machinery, like wind turbine gearboxes or robotic arms.

• How We Do It:

  • We establish a federation between a manufacturer and the companies that use its equipment.

  • Our AI model is deployed to the edge computers on each machine, where it trains on real-time sensor data (vibration, temperature) and maintenance logs.

• The Impact We Deliver:

  • Achieving Near-Zero Downtime: Our federated models can predict a potential failure weeks in advance, turning costly emergency repairs into routine, scheduled maintenance.

  • Creating Smarter Supply Chains: We give manufacturers an unprecedented, real-time health overview of their entire deployed fleet, allowing them to manage spare parts and logistics with incredible precision.

  • Driving Better Engineering: The insights from our models provide a direct feedback loop to engineers, showing them exactly which components fail under which conditions, leading to more robust products in the future. This is the promise of Industry 4.0 realized.

Application 2: Orchestrating the Smart Cities of the Future

The Challenge: A truly smart city needs to optimize traffic flow, public transport, and energy grids as a single, cohesive system. But the data required is fragmented across dozens of public and private entities—the city transport authority, ride-sharing companies, delivery services—who cannot simply pool their sensitive operational data.

The Sherpa.ai Solution: We provide the neutral, trusted platform for public-private collaboration.

• Our Goal: To create a real-time "digital twin" of a city's mobility network to reduce congestion, cut emissions, and improve quality of life.

• How We Do It:

  • The city municipality can act as the orchestrator of a federation including the bus network, ride-sharing companies, and logistics firms.

  • Our traffic prediction model trains across all their siloed datasets, learning the complex interplay between all modes of transport.

• The Impact We Deliver:

  • Dynamic, Responsive Cities: The aggregated model can predict traffic jams before they form, allowing the city to dynamically adjust traffic light timings or suggest alternate routes through navigation apps.

  • More Efficient Public Services: We help cities understand true mobility demand, allowing them to plan more efficient and responsive bus routes.

  • Smart, Not Surveillance: Most importantly, we enable all of this without creating a centralized database tracking every citizen's movements.

Part 5: Our Vision for the Horizon: Generative AI, Edge Computing, and European Leadership

At Sherpa.ai, we are constantly pushing the boundaries of what's possible.

Private, Powerful Generative AI: The generative AI revolution is here, but it comes with a critical privacy question. How can an enterprise fine-tune a Large Language Model (LLM) on its proprietary data without sending that data to a third-party API? We have the answer. Our platform enables organizations to build powerful, specialized, and completely private generative AI models, ensuring their most valuable intellectual property remains secure.

The Power of the Edge: Our federated learning technology is a natural fit for Edge AI. By performing model training on devices like smartphones, cars, and industrial sensors, we reduce latency, save bandwidth, and enable AI to function even without a constant internet connection.

Championing European Trustworthy AI: We are proud to be a European AI leader. Our privacy-first philosophy is in our DNA, aligning perfectly with the EU's global leadership in crafting a human-centric and trustworthy AI framework. We don't just comply with regulations like the AI Act; we see them as a validation of the ethical approach we've taken from day one. We are not just participating in this future; we are helping to build it.

Join Us in the Era of Collaborative Intelligence

The applications we've shared are more than just use cases; they are proof of a new paradigm. The future of progress no longer belongs to those who hoard data, but to those who can build bridges of trust to share intelligence.

Our mission at Sherpa.ai is to build those bridges. We provide the technology that allows the world's brightest minds and most innovative organizations to solve their greatest challenges together.

The era of collaborative intelligence has begun. We invite you to build it with us.