We turn knowledge into practical value
in:know works with organisations that face complex problems, dispersed knowledge and transformation challenges that do not fit standard solutions.
Our work starts by understanding how knowledge, people, processes, tools and decisions interact inside each context. From there, we help organisations make sense of complexity and create practical value through process redesign, dedicated IT tools, applied AI and human-centred technology.
We do not treat technology as the starting point. Technology is one of the instruments. The starting point is always the real organisational challenge.
Process Redesign
Organisations often accumulate routines, informal workarounds and fragmented procedures that continue to function, but no longer work well.
in:know helps analyse how work is actually performed, where friction appears, where effort is duplicated, and where knowledge or responsibility becomes unclear.
We support process redesign with a practical objective: making work more coherent, more efficient and easier to sustain.
This may involve: process mapping, identification of bottlenecks, redesign of workflows, alignment between people and tools, definition of improvement indicators, and support for implementation.
Knowledge Systems
Much of an organisation’s value is hidden in dispersed knowledge: people’s experience, documents, data, past projects, operational routines and informal decisions.
in:know helps organisations gather, structure and use that knowledge more effectively.
We design systems and methods that make knowledge easier to find, interpret, share and apply. This may include knowledge repositories, recommendation mechanisms, contextual information systems, semantic structuring, decision-support content, and tools that connect organisational memory with daily work.
The goal is not simply to store information. The goal is to make knowledge usable.
Decision Support
Complex organisations make decisions under uncertainty, incomplete information and competing priorities.
in:know develops decision-support approaches that help people understand options, compare alternatives and act with better structure.
Our background in decision systems, modelling and control allows us to design tools that support human judgement rather than replace it.
This may include decision models, multi-criteria analysis, dashboards, recommendation systems, simulation-based support, scenario exploration and human-in-the-loop decision workflows.
Applied AI
AI is useful when it is connected to a real organisational need.
in:know applies AI as a practical tool for knowledge retrieval, recommendation, classification, conversational interaction, process support and automation of repetitive cognitive tasks.
We are especially interested in AI that helps organisations use their own knowledge better: making documents searchable, supporting users in complex workflows, recommending relevant information, assisting decisions, and improving the interaction between people and digital systems.
We avoid AI theatre. AI should create value, improve work, or clarify decisions.
Human-Centred Technology
Technological change fails when people do not understand it, trust it or see value in using it.
in:know designs technology with attention to acceptance, usability, social context and organisational adoption.
Our work includes human-in-the-loop systems, participatory approaches, social acceptance analysis, interface concepts, user feedback, training support and adaptation of tools to real work practices.
The objective is to create systems that people can use, understand and adopt.
R&D projects
in:know has strong experience in applied research and innovation projects.
We help transform research ideas into working concepts, prototypes and demonstrators. This includes software development, system architecture, integration of intelligent components, validation in pilot contexts and communication of project results.
Our R&D background allows us to work effectively with universities, companies, public organisations and European consortia.
We bring the capacity to move between conceptual work and implementation.
How these capabilities come together
Our work rarely fits into only one category.
A project may begin with organisational complexity, require knowledge structuring, lead to process redesign, use AI as an enabling tool, and result in a demonstrator or dedicated software system.
That is where in:know creates most value: connecting different forms of knowledge and turning them into coherent action.
We work best in contexts where the problem is real, but not yet fully structured.