Knowledge Valorisation
Koralae expands the capacity of universities, research institutes, technology centres and innovation agencies to identify, assess and develop opportunities for knowledge valorisation.
The case for change
Research results rarely arrive as ready-made opportunities. Their potential may extend beyond the questions and disciplines that produced them, while the evidence needed to assess it is often scattered across people, documents and systems. For valorisation teams managing diverse portfolios, the challenge lies both in the complexity of each case and in the number of possibilities demanding attention.
Approach
An answer may reveal a possibility. Developing a valorisation opportunity requires more: testing assumptions, examining evidence and assessing alternative routes as new information emerges. Koralae brings these activities into a connected process of enquiry and professional judgement, helping teams develop stronger propositions and decide how to advance them.
Evidence should shape the opportunity, not merely validate the starting assumption.
Product
Koralae provides a platform for exploring where research results and capabilities could create value, shaping and assessing opportunities, and coordinating the work needed to advance them. It helps clarify what the evidence supports, what remains uncertain and which routes merit further work as circumstances change.
Research findings, technological capabilities and unmet needs can each provide a starting point. Explore possible uses across disciplines and sectors, including responses to societal, economic and environmental challenges. Draw on relevant expertise to determine which possibilities merit further investigation.
Explore possible uses through knowledge, needs and relevant expertise.
Findings, technologies, methods and know-how
Practical needs, societal and economic challenges, and possible uses
Researchers, practitioners and potential users
Possible uses and why they merit further exploration.
Turn an opportunity into a clear proposition: what could create value, for whom and under what conditions. Compare possible routes for creating value using the available evidence, make assumptions explicit and identify what each route would require. Build a sound basis for deciding what warrants further work.
Make the proposition explicit enough to assess its evidence and test its assumptions.
Evidence of relevance, intended benefits and alternatives
Capabilities, ownership, access rights, partners and resources
Evidence gaps and assumptions to examine
Compare routes with their evidence, requirements and uncertainties in view.
Turn an agreed direction into coordinated work. Plan validation activities, involve relevant experts and partners, and clarify the rights, resources and funding required. Keep actions, responsibilities and milestones aligned with the route, and make clear what each activity needs to establish.
Coordinate actions, people and resources, including work that can proceed in parallel.
Activities, dependencies and deliverables
Expertise, responsibilities and means to proceed
Results, milestones and remaining requirements
An opportunity may advance through collaboration, licensing, venture creation or direct adoption—sometimes in combination.
Compare new findings and results with the assumptions behind earlier decisions. Understand what has changed in readiness, risk and expected value, then use that learning to refine the proposition, revise the route or reconsider portfolio priorities. Keep the reasoning behind each decision traceable as the opportunity evolves.
Revisit the case for the route while retaining the reasoning behind earlier decisions.
Results, feedback and changes in context
Readiness, risk and expected value
Continue, adapt, pause, redirect or conclude
Revisit the proposition, the route or portfolio priorities.
Technology
Knowledge valorisation asks more of intelligent systems than finding relevant information. They must preserve meaning across sources, distinguish evidence from inference, support decisions under uncertainty and respect institutional boundaries. Koralae brings these requirements into a specialised architecture designed to make the basis of assessments examinable, AI-supported operations traceable and control over knowledge explicit.
Relate different kinds of knowledge while retaining the distinctions and provenance essential to interpretation.
Examine propositions against available evidence, explicit constraints and uncertainty.
Coordinate specialised AI operations through defined permissions, traceable actions and professional oversight.
Work with authorised knowledge across organisational boundaries without assuming unrestricted sharing.
Research findings, technological capabilities, intellectual assets and possible uses appear in different vocabularies, formats and systems. Semantic models, knowledge graphs and entity resolution help identify the same entities across sources and represent their relationships, while retaining the provenance and distinctions on which sound interpretation depends.
Assessments must distinguish what evidence establishes, what can reasonably be inferred and what remains an assumption. Structured knowledge, source-linked evidence and explicit constraints help examine propositions, identify contradictions and make uncertainty visible. The aim is to keep the grounds for assessment open to challenge, rather than treating a plausible answer as an established conclusion.
Complex assessments can involve different AI models, tools and specialised operations. Governed orchestration coordinates these activities through defined permissions, task dependencies, traceable execution and appropriate points for professional review. It extends the scope of intelligent work while keeping the limits of automation and responsibility for consequential decisions explicit.
Knowledge relevant to valorisation may be distributed across organisations, each with different access rights, confidentiality obligations and conditions of use. Policy-aware access, authorised retrieval and privacy-preserving approaches provide ways to work with relevant information while respecting these boundaries. Collaboration need not depend on unrestricted sharing or centralised ownership of knowledge.
From intelligence to action
Greater capacity changes not only what can be explored, but what can be pursued. Koralae helps examine possibilities, compare courses of action and coordinate the work they require, even when time and specialist resources are limited. That gives people more room to form teams, build partnerships, negotiate conditions and move promising initiatives forward.
Company
Koralae brings together a founding team with extensive experience in artificial intelligence research, European R&D, innovation, entrepreneurship and product strategy. Its founders have led research and innovation projects, developed products and new ventures, and built partnerships across research organisations and industry. That combination shapes Koralae’s approach to knowledge valorisation: scientific rigour applied to complex technologies, alongside the practical judgement needed to develop propositions, partnerships and new initiatives. Founded in Bilbao, Koralae is a startup supported by the University of Deusto.
Contact
Whether you're seeking new ways to create value from research, developing an innovation initiative or bringing partners together around a challenge, we'd welcome a conversation about what you're working towards and how Koralae could contribute.
Let's talk
