What actually remains exclusive to a creative organisation in the age of AI? Not necessarily the next image, film or campaign – but the knowledge, decisions and creative DNA from which all of these emerge. This is precisely where SIISTER.AI positions itself: as the Intelligence Layer Behind Global Brand Production.
Founded by Brivaelle Capitaine, founder and Managing Director of One Hundred Berlin, the new EU-based company is developing what it calls an “AI-native Operating System for the Creative Industry”, centred around an intriguing concept: Creative Memory. While foundation models learn from the data and content of millions, SIISTER aims to enable creative organisations to preserve, structure and activate their own creative knowledge with AI – while keeping that memory exclusive to the organisation itself.
The idea raises an interesting proposition: the future competitive advantage of agencies, production companies and creative businesses may not only lie in the assets they produce, but increasingly in how well they preserve and build upon their own creative history, decisions and institutional knowledge.
In parallel, Brivaelle is completing an MIT Executive Program in Artificial Intelligence, where she is applying advanced AI concepts to the design of AI-native organisations and next-generation AI products and services. As part of the program, she is developing SIISTER’s enterprise AI strategy and deployment roadmap. Research on cognitive architectures, embeddings, knowledge graphs, agentic workflows and human-in-the-loop governance is directly informing SIISTER’s architecture.
SIISTER is also part of the MTH Startup Accelerator, the nine-month program of MediaTech Hub Potsdam. Located in the Babelsberg media ecosystem, the program supports early-stage MediaTech companies with individual coaching, industry expertise and access to a network of founders, technology partners, investors and media companies.
SIISTER.AI is launching in 2026. GoSee spoke with Brivaelle Capitaine about Creative Memory, AI-native workflows and the question of what creative organisations can actually teach their own AI.
You describe SIISTER as an “AI-native Operating System for the Creative Industry”. What does that actually mean in the everyday life of an agency, production company or creative studio?
AI-native means that AI is built into the operating logic from the beginning, rather than added as another tool on top of an already fragmented workflow. SIISTER’s architecture is designed to understand the context of a project, retrieve relevant knowledge, support decisions and orchestrate the interactions between teams, tools and workflows.
In the same way a CRM gives companies a shared system for understanding and managing customer relationships, SIISTER is designed to become the shared intelligence and operating layer for creative production.
In practical terms, it means that everyone involved in creative production can finally really collaborate within the same environment. Today, briefs, schedules, budgets, assets, feedback and approvals are scattered across different platforms. Adding more AI applications does not solve that fragmentation. I believe getting the full value from AI requires more than learning how to prompt or generate, it requires reinventing the workflow itself.
For an agency, that means clearer briefs, connected feedback and better visibility across the project. For a production company, it means coordinating scope, budget, timing, talent and production decisions. For a creative studio, it means bringing traditional craft and AI-powered asset production into the same workflow, while automating repetitive tasks where it makes sense.
Importantly, SIISTER is not built around a rigid or standardized production process. It is designed to evolve with the technology, continuously looking outward for new tools, models and production methods and recommending the most suitable approach for a particular project.
Transparency is built into the architecture as well. If a photograph is modified with AI, I believe preserving its Creative Lineage should become standard practice, keeping the photographer source, rights and subsequent AI and human interventions traceable throughout production.
Creative Memory is at the heart of SIISTER. What exactly belongs to a company’s Creative Memory – finished work, treatments, references, decisions, conversations, rejected ideas?
Creative Memory is a central piece of SIISTER’s architecture. It differs from a traditional archive because it does not simply store past work; it captures the intelligence created through that work and makes it usable again.
Every project is a goldmine of knowledge with real commercial value: briefs, treatments, references, brand guidelines and finished assets, but also the decisions behind them, what was approved or rejected and why, client preferences, correction rounds, successful workflows, mistakes, exceptions and lessons learned throughout the project lifecycle.
AI adds another layer: which tools or models were used, which outputs were selected or rejected, where a model failed, and how a human corrected it. What worked and what failed are both part of the memory.
And it is not about saving every email or conversation forever. The goal is to extract what actually matters, connect it to the right project context, and use it to make the next project smarter.
Today, much of this knowledge remains buried in archives or in people’s heads. Creative Memory is designed to support continuous learning, so the right precedent, experience or expertise can surface when it is needed most.
Most creatives are currently being offered AI tools that promise to generate more, faster. You seem to start somewhere else: preserving what an organisation already knows. Why?
The challenge isn’t access to AI tools. We already have plenty. It’s making sure creative organizations don’t lose the knowledge they’ve built over years. As AI becomes increasingly accessible, the technology itself will become less differentiating. What remains unique is what an organization has accumulated through experience: its craft, taste, client understanding, decisions, corrections, mistakes and ways of solving problems.
During my MIT Executive Program on Artificial Intelligence, I’ve been working on how AI-native organizations and the next generation of AI products and services can be designed, from knowledge architectures and agentic workflows to human-in-the-loop governance. For SIISTER, that work led to a question that became increasingly central: what can we actually teach AI?
Together with our ML engineer, we’re developing proprietary, domain-specific AI models and experimenting with what knowledge and craft we can teach our own models. We’re keeping the details in stealth for now, but there will be more to discover in our MVP+.
For me, that is where Creative Memory becomes really powerful. It gives an organization the foundation to learn from its own experience rather than constantly starting again from zero. The competitive advantage won’t simply be having access to AI. It will increasingly be what your organization has managed to teach it.
The word “exclusive” is important in your positioning. How do you make sure a company’s Creative Memory remains its own – and isn’t ultimately used to train someone else’s model?
Our architecture is being developed around one clear governance principle: your Creative Memory should remain yours. SIISTER is meant to be an ally, loyal to its organization, helping it evolve while protecting the knowledge that makes it unique and the intelligence that develops from it over time.
The knowledge an organization builds should reinforce its own intelligence, not leak into someone else’s. SIISTER is therefore being designed with clear separation between organizations, controlled access, and traceability of how data and models are used, including when external AI services are involved.
Human-in-the-loop governance is central to this as well. Professionals remain responsible for what constitutes a good result, and validated human feedback can help the system become increasingly relevant to that organization’s own standards, preferences and creative language.
For us, exclusivity therefore goes beyond privacy. It is about protecting both the Creative Memory and the unique intelligence that grows from it over time.
And perhaps the most important question for our readers: What will SIISTER actually enable them to do when it launches that they cannot do today?
In the MVP+, teams will be able to manage projects, asset production, corrections, approvals and delivery within one shared workflow, alongside integrated AI-powered production capabilities and our first proprietary AI model.
SIISTER is designed with a dual entry point: a project can begin with traditional photography or with AI-generated content, and both can continue through the same professional production environment. For me, these should no longer be disconnected worlds.
What excites me most is that SIISTER is not designed as a fixed toolbox. It will continuously connect teams to the best technologies available across photography, AI generation and professional post-production, bringing the right capabilities into the workflow as they evolve.
At the same time, the system begins to build an intelligence layer around the production itself, so that useful knowledge, creative choices and successful approaches do not simply disappear when a project ends.
So what becomes possible is not simply doing the same work faster with AI. We are building a new intelligent operating system for the Creative Industry, one that can learn from the organization while evolving with the technology. Our MVP+ is starting to show where this can go, but there is quite a lot happening under the hood that we are deliberately keeping in stealth for now.
ABOUT BRIVAELLE CAPITAINE
Brivaelle Capitaine is Founder & CEO of SIISTER.AI, the AI-native Operating System for the Creative Industry, launching in 2026. She is also Founder & CEO of ONE HUNDRED BERLIN, the independent creative production and post-production company she founded in 2010. In 2025, she was recognized as a “Vorbild-Unternehmerin” (Role Model Entrepreneur) by the German Federal Ministry for Economic Affairs & Climate Action.
