Blockbrain – unlocks your enterprise
knowledge
and makes it usable with AI.
Blockbrain combines Knowledge Bots, digital Knowledge Twins, workflows, and AI agents into a central Enterprise AI platform. Le Bihan designs the knowledge architecture, prioritized use cases, governance, and integration. This activates existing knowledge exactly where it is needed.
Unlock knowledge. Trace sources. Scale AI in a controlled manner.
Blockbrain places a central AI layer over existing knowledge sources and systems. Information is semantically unlocked, structured, and made available in the respective context of use via bots, Knowledge Twins, agents, and workflows.
Networking Corporate Knowledge
Semantically unlock documents, knowledge bases, and connected systems – across system boundaries and in line with existing permissions.
Building Knowledge Bots and Knowledge Twins
Answer technical questions with sources and structure experiential knowledge so that the decision-making logic of experienced specialists becomes traceably usable.
Connecting Workflows and AI Agents
Not just outputting knowledge, but transferring it into recurring work steps, document processing, and defined actions.
Operating Enterprise AI in a Controlled Manner
Design roles, access, model selection, data residency, and governance so that AI scales securely within the existing system landscape.
Enterprise AI needs more than just a good model.
Le Bihan combines knowledge management, use-case design, process integration, and governance with Blockbrain's technical platform. The starting point is not as much AI as possible, but a clearly defined knowledge or process question with reliable sources and responsibilities.
Structuring Sources, Domains, and Responsibility
Defining Access, Quality, and Control Points
Embedding AI into Systems and Work Processes
Software is only one part of the solution.
To turn a powerful tool into a functioning overall solution, more than just configuration is required. We consider the interplay of people, organization, methods, processes, data & AI, and software.
Powerful software and standard functionality.
Product expertise and best practices for the platform.
Roadmap, standard functionality and ongoing technological development.
Clarity on objectives, priorities and the intended management contribution.
Roles, responsibilities and decision paths.
A suitable management logic and end-to-end processes.
Sources, data quality and interfaces within the overall model.
Enablement, adoption, operations and controlled evolution.
Securing experiential knowledge before it is lost.
A large part of the most valuable corporate knowledge is not found in documents, but in experience: in the considerations, exceptions, and decision-making paths of long-term specialists. Digital Knowledge Twins make this knowledge accessible and traceable in a structured way.
Interviews and structured knowledge recording make typical questions, exceptions, and proven procedures of experienced specialists explicit.
Experiential knowledge is translated into traceable decision-making paths and checked and refined together with those responsible for the subject matter.
Documented sources, access rights, and technical responsibility create the basis for ensuring that answers remain verifiable and controllable.
Knowledge Bots and Knowledge Twins bring secured knowledge to where questions arise – without losing the original context and the underlying sources.
Enterprise AI needs control – not just good answers.
Knowledge management with AI touches on sensitive content, permissions, and decision-making bases. Architecture, data residency, model selection, and traceability must therefore be part of the operating model from the very beginning.
Data Residency
Operation on European infrastructure and data sovereignty within the corporate context.
Data Privacy
Designing roles, access, and data processing in accordance with European requirements.
Information Security
Information security and service continuity on a certified basis.
Traceability
Securing answers and knowledge use with source references and clear control mechanisms.
Making knowledge usable where work happens.
Blockbrain can integrate existing knowledge sources, collaboration platforms, and specialist systems into a central AI layer via connectors and APIs. The existing systems remain part of the system landscape; the AI layer unlocks knowledge across their boundaries.
Le Bihan designs the functional and organizational interplay: Which source is leading? Which permissions apply? How are answers checked and improved? And at what point should a bot, Knowledge Twin, or agent provide knowledge or trigger an action?
No new knowledge repository for its own sake: The goal is a controlled AI layer over relevant sources, roles, and processes.
How we support our clients
Simon Klaedtke
Business Development Lead
„With Enterprise AI, the real work begins before the prompt: with sources, responsibility, governance, and a use case that works measurably better in everyday life.“





