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We build technology to solve real problems.

Twinny is a Spanish technology company founded in 2022 at the Science Park of Universidad Carlos III de Madrid. We build Digital Workers, hyperautomation systems and AI Operating Layers on our own platform, with a team that has worked with data and artificial intelligence since 2011.

What is Twinny?

Twinny is a Spanish technology company founded in 2022 at the Science Park of Universidad Carlos III de Madrid. It builds Digital Workers, hyperautomation systems and AI Operating Layers for mid-sized and large companies, using its own platform as the foundation of every project.

The founding team brings together more than 25 years of experience in engineering, software development and digital product creation. It has worked with Big Data architectures since 2011 and with Machine Learning and Deep Learning since 2015. In 2024 Twinny obtained official certification as a Spanish startup (empresa emergente) and closed a funding round that brought new investors into the project.

Twinny does not sell generic AI agents. It starts from a specific business problem, reuses the connectors, data systems, automation, voice and AI components of its platform, and builds systems capable of understanding, deciding and executing complete processes inside an organisation.

What is the history of Twinny?

Our history with data and artificial intelligence began long before Twinny. These are the stages that explain how we work today.

  1. 2011

    First Big Data architectures

    The team was already working with Big Data architectures and large volumes of data. That foundation explains why our vision of AI always starts with data.

  2. 2015

    Machine Learning, Deep Learning and Computer Vision

    We began developing solutions based on Machine Learning and, later, on Deep Learning, Computer Vision and image recognition. We took part in public-private collaboration projects with universities and companies, and in research initiatives and publications related to artificial intelligence.

  3. 2022

    Twinny is born at the UC3M Science Park

    Twinny is founded at the Science Park of Universidad Carlos III de Madrid with a very clear idea: use our experience in software, product and data to build our own technology capable of solving complex business problems.

  4. 2023

    Generative AI changes the landscape

    The arrival of generative artificial intelligence completely changed the landscape. That same year we evolved our technology to build systems capable of using generative AI inside real business processes. Our first product focused on sales automation, customer onboarding and intelligent agents able to interact with users across different channels.

  5. 2024

    From talking to working. And a new stage of growth

    We began combining generative AI with process automation, RPA, systems integration and enterprise technologies: the goal was no longer to create agents, but systems that understand, decide and execute complete processes. That same year Twinny obtained official certification as a Spanish startup and closed a funding round that brought in new investors, allowing us to strengthen our infrastructure and take on more complex projects.

  6. Today

    The platform as the engine

    Our platform, infrastructure and components are the foundation on which we build tailored Digital Workers, hyperautomation systems and AI Operating Layers for each client. We never start a project from scratch.

  7. 2026–27

    Turning experience into a reference

    Our ambition is to make Twinny a reference company in building enterprise artificial intelligence systems: Digital Workers, AI Operating Layers, Company Memory, MCP and multi-agent architectures, hyperautomation and Voice AI.

We quickly understood something important: the real value of AI was not only in talking. It was in working.

From SaaS product to infrastructure for working with AI.

Twinny was initially born as a SaaS platform focused on creating artificial intelligence agents. Today, basic agent creation is quickly becoming a commodity. That is why our evolution has taken a different direction.

We use our own platform, infrastructure and components as the foundation for building solutions specific to each company. We do not start every project from scratch: we reuse proven technology to develop tailored solutions faster and with greater ability to scale.

And we are working on local AI implementations: models deployed in the customer’s infrastructure, on-premise or in their private cloud. The reason is threefold: cost savings when usage volume is high, control over data security, since data never leaves the company perimeter, and control over the infrastructure itself. The same platform, pointing to your own models.

Our platform is now the engine that lets us build Digital Workers, hyperautomation systems and AI Operating Layers for our clients.

What a Digital Worker is

What we reuse in every project

  1. Connectors
  2. Data systems
  3. Automation and RPA
  4. Voice
  5. AI components
  6. Infrastructure

Data has always been at the core.

Before the current generation of AI agents existed, we were already working with large volumes of data. That is why our vision of artificial intelligence always starts with data.

We build architectures capable of connecting information from different systems and turning it into a shared company memory: the Company Memory. The different agents and digital workers operate on top of that memory.

AI can only be truly useful when it understands the context of the company.

How the Company Memory works
  • Data Lakes
  • Big Data
  • Databases
  • Corporate systems
  • Documentation
  • Conversations
  • Internal tools

Company Memory: a single context layer

Agents and Digital Workers that understand, decide and execute

We understand technology. But we start with the business.

One of Twinny’s main strengths is not a specific technology. It is our ability to understand how a company works.

We get involved in the client’s real processes, identify where there is friction, repetitive work, unnecessary cost or limits to scalability, and look for a technological solution capable of solving it. We do not just implement what we are asked for.

  1. Understand the problem

    We get inside the real process: who is involved, which tools they use and where time or money is lost.

  2. Question the process

    Before automating, we ask whether the process should exist as it is.

  3. Design a better solution

    We build the technology that solves the problem, not the one in the original brief.

How we work with clients

Engineering without technology lock-in.

Throughout our history we have worked with multiple architectures, clouds, languages and platforms. Our infrastructure operates mainly in Europe.

Environments we regularly work with

  • AWS
  • Microsoft Azure
  • Google Cloud

We also integrate enterprise solutions, RPA platforms, APIs, corporate systems and legacy software.

We do not believe there is a single correct technology. We choose the architecture that best solves the problem.

Security and compliance

Which sectors does Twinny have experience in?

Over the years our team has taken part in complex projects across multiple sectors:

  • Banking and financial services
  • Marketing and digital commerce
  • Education and corporate training
  • Human Resources
  • Healthcare
  • Hospitality and tourism
  • Business operations

That cross-sector experience lets us identify patterns that appear in very different organisations and carry solutions from one sector to another.

2026–2027: turning experience into a reference.

Our challenge for the coming years is to grow while keeping the same way of working: always start from real business problems and build technology capable of solving them.

After years working with Big Data, Machine Learning, Deep Learning, automation and generative artificial intelligence, our ambition for 2026 and 2027 is to make Twinny a reference company in building enterprise artificial intelligence systems.

We do not want to be just another company that creates AI agents.

We want to help build the infrastructure on which artificial intelligence will work inside companies over the coming years.

Especially in

Our vision.

We believe the next business transformation will not simply consist of adding chatbots or assistants. Companies will progressively build a new layer of intelligence on top of their data, systems and processes.

An infrastructure where people and digital workers collaborate. Where agents can share context. Where different systems can communicate. And where artificial intelligence can execute real work inside the organisation. Twinny wants to help build that infrastructure.

  1. We always start with a specific challenge.
  2. We understand how it works.
  3. We design a solution.
  4. We build robust, scalable technology ready to keep growing with the company.

That is what we love doing.

Origin and backing

Universidad Carlos III de Madrid

Technology-based company affiliated with the Science Park of Universidad Carlos III de Madrid since 2022.

ENISA — Certified Spanish startup

Official certification as a Spanish startup (empresa emergente) obtained in 2024.

Frequently asked questions about Twinny

When and where was Twinny founded?

Twinny was founded in 2022 at the Science Park of Universidad Carlos III de Madrid, in Spain. The legal entity operating the brand is Wason Digital, S.L.

What does Twinny do?

Twinny builds Digital Workers, hyperautomation systems and AI Operating Layers for companies: artificial intelligence systems capable of understanding, deciding and executing complete processes inside an organisation, connected to its data and its systems (CRM, ERP, databases, email, telephony, WhatsApp and legacy software).

Is Twinny a SaaS product or a consultancy?

Twinny was born as a SaaS platform for creating AI agents. Today it uses that same platform, its infrastructure and its components as the engine for building tailored solutions for each company. It does not start projects from scratch: it reuses connectors, data systems, automation, voice and AI components, which allows faster delivery and better scaling.

What experience does the Twinny team have?

The founding team brings together more than 25 years of experience in engineering, software development and digital product creation. It has worked with Big Data architectures since 2011 and with Machine Learning, Deep Learning, Computer Vision and image recognition since 2015, and has taken part in public-private collaboration projects with universities and companies and in research publications on artificial intelligence.

Where does Twinny’s infrastructure operate?

Twinny’s infrastructure operates mainly in Europe. The team regularly works with AWS, Microsoft Azure and Google Cloud, and integrates RPA platforms, APIs, corporate systems and legacy software. There is no single correct technology: the architecture that best solves each problem is chosen.

Which sectors does Twinny have experience in?

Banking and financial services, marketing and digital commerce, education and corporate training, Human Resources, healthcare, hospitality and tourism, and business operations. That cross-sector experience allows proven solutions to be carried from one sector to another.

Is Twinny a certified startup and does it have investors?

Yes. In 2024 Twinny obtained official certification as a Spanish startup (empresa emergente) and that same year closed a funding round that brought new investors into the project.

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