The value of making sense of structures.
Untangle knowledge with Discovery Maps.
Maps for knowledge landscapes
Nifty.works are knowledge discovery platforms to find paths between entities, like paths between places in a geographic map.
Discovery helps to find paths in between of entities and reach out to novel areas, starting from your own background.arrow_downwardLearn More
Imagine the full-potential of enabling access to innovation, for anyone
Nifty.works support discovery activities for self-empowerment, education, research and open innovation.
Maps of knowledge landscapes help individuals, organizations and learners to find what they cannot name yet, reaching out to the its sorrounding context and overview which topics are key to understand it.
Make sense of the context of a subject at a glance, and decide where to invest time for deeper understanding.
You guide technology. Under the hood, techology scoutes for hidden connections, sort their relevance and lay them out to uncover how knowledge and industrial domains are shaped. You can navigate maps as tools to orient yourself, according to your expertise and point of view.
While recommender systems filter results they think you will skip, maps for knowledge landscapes harness AI, topological and data-driven landscapes to let you navigate out of the filter bubble.
Rolled out a discovery engine of 100M factual knowledge connections to the public, enabling dissemination of maps to democratise learning paths.
Engaged in sustainable food habits, implementing food discovery of 25K recipes paired with food sustainability index.
Supported digital transformation in advance research, crafting MVP for genomics discovery of genes interactions and genes association to diseases.
Nifty.works support thinking in systems and encourage lateral thinking: explore how systems are organised and uncover interconnections between multidisciplinary areas.
The discovery platforms are made by two independent components you can choose to apply to your business and research area: done network science component, to quantitatively organise knowledge networks, analyse how they evolve, deploy data-driven and NLP-driven services; done experience component, to navigate and make sense of complex systems - with ease.
Plug-and-Play Discovery Networks
Organisations, businesses and individual projects can flexibly pick up the component that best empower their infrastructure.
Nifty.works support teams and labs, offering an holistic approach addressing knowledge discovery: business design, passion for sci-tech, prototyping and human centered design skillset.
Knowledge networks and AI organise structures and analyse how they evolve.
Maps allow to navigate, overview and summarise context for awareness and decision making.
Suited for technical and domain experts, as well laypeople with entry level expertise.
Model discovery engine solutions atop of your infrastructures and datasets, to extract the best out of big-data as well as relatively small data-sets typically in use at SMEs.
Topology and Software architecture. Use your own backend infrastructure or set up MVP quickly.You are free to model knowledge graphs upon graph db solutions such as Neo4j, OrientDb, Titan, or hybrid solutions designed upon noSQL, scientific python, ElasticSearch, Redis, to deploy functional solutions on budget. The knowledge graph for General factual knowledge is actually deployed on hybrid architecture, allowing reducing costs by 10x VS same model deployed on graph db infrastructure.
Plug the visualisation component to your own system and uncover what you have under the hood, with extreme ease.
UX for knowledge discovery. Visualisation component is independent from the backend infrastructure and is designed to consume simple web API REST. No need to install an SDK, special connectors and middle-wares. No need of maintanance on your behalf. Simply provide compliant JSON objects, and you are done: go for your a-ha moments and start to navigate knowledge graphs.
Embed knowledge discovery with specific industrial technologies.
Digital transformation. AI and visualisation components of Knowledge discovery can be paired with data and technological opportunities specific to your industry, such as blockchain to track, monitor, evaluate supply chains, and vertical search engines.
Suited for general public
The vision of Maps for knowledge landscapes is to help people make the right questions when they come to study and learn about new things. We want to encourage evaluation of newly produced information, by making its context known and accessible.
In terms of system thinking, maps for knowledge landscapes are designed by considering information as an asset - an in-kind Capital - and by considering the imporance to balance Stocks and Flows in Capital-to-Information processes. Facilitating comprehension of the context of things, it means enabling access to Capital to process novel ideas. Like githubs for innovation processes, showing how different "knowledge" routes merge and branch.
Taking decisions is easier when the context of things is clearer. It is also easier to validate things, reach out and connect with diverse expertise for cooperation and fact-based discussions. We hope that the ability to overview the context of factual knowledge can encourage self-empowerment, awareness and participation in trasversal areas characterising a society evolving as fast as never before.