OPIX and OpenAIRE are combining AI-driven analysis with the world's richest collection of open science scholarly works — and a uniquely broad set of data sources — to deliver the evidence-based intelligence that STI policymakers, R&D leaders, and innovation strategists urgently need.
Science, technology, and innovation policy has never been more demanding. As the pace of technological change accelerates and the volume of scholarly output doubles roughly every nine years, the ability to read and interpret the research landscape at scale has become a prerequisite for effective policymaking — not a luxury. The same urgency applies to R&D strategy: companies and research institutions that cannot systematically monitor where knowledge is moving, who is generating it, and how it connects to market opportunity are navigating blind.
This is the problem at the heart of the collaboration between OPIX — Athens-based AI-driven policy and strategy consultancy — and OpenAIRE, Europe's open scholarly communication infrastructure. By fusing the OpenAIRE Graph with a rich plurality of additional data sources, and applying state-of-the-art AI throughout, the two organisations are building something the STI and R&D community has long needed: a system that turns the full spectrum of innovation signals into strategic foresight.
A plurality of data sources: the OPIX intelligence foundation
One of OPIX's defining characteristics is the breadth of data it ingests. Where most analytics tools draw on a single source — publications, or patents, or company data — OPIX integrates six distinct categories of evidence into a single, unified intelligence picture. The OpenAIRE Graph, now a cornerstone of this integration through the OPIX–OpenAIRE collaboration, adds the open science scholarly layer that completes the picture.
This multi-source approach is not simply a matter of completeness — it is a matter of interpretive power. A patent signal means something different depending on whether it is accompanied by strong publication activity, backed by public funding, and supported by a growing startup ecosystem. Only by fusing these six data streams does the OPIX platform develop what it calls sector-specific contextual intelligence: insights that reflect not just what data says, but what it means for a particular industry, region, or policy challenge.
OpenAIRE Graph: the Open Science layer
Once all data sources — with the OpenAIRE Graph at the scholarly core — are ingested, OPIX applies a five-stage AI pipeline that transforms heterogeneous raw inputs into structured, decision-ready intelligence.
1. Data collection, cleaning, and integration
The platform seamlessly integrates scientific publications, patents, company data, funding reports, regulatory information, and research datasets. Advanced cleaning, normalisation, and disambiguation techniques ensure that entities — organisations, technologies, key actors — are correctly identified and linked across all source types. Entity resolution eliminates redundancies and resolves inconsistencies, producing a data foundation that is robust, up-to-date, and ready for deep analysis.
2. Extracting information and knowledge with LLMs
Using Large Language Models, the platform automatically identifies emerging technologies, maps their relevance across industries, and pinpoints key players shaping the competitive landscape. The approach is sector-specific — each industry has distinct technological trajectories and regulatory dynamics — reducing the risk of AI-driven misclassification and enhancing the trustworthiness of the intelligence produced.
3. Innovation smart indicators
Through NLP, Machine Learning, and Knowledge Graphs, the platform computes composite "signals" in the innovation ecosystem — uncovering meaningful relationships between technologies, companies, and key actors. These indicators go beyond simple analytics: they identify emerging trends, assess competitive positioning, and dynamically link technologies with their applications, market relevance, and industry impact.
4. Visualising the competitive landscape
Interactive dashboards and advanced visualisations provide intuitive representations of the technology and industry landscape — enabling users to understand technology positioning within global markets, benchmark companies and research institutions against competitors, and explore sectoral trends, collaborations, and funding flows.
5. Sector-specific configurability
The platform is fully configurable per sector — agrifood, water management, energy, automotive, and more — integrating targeted company profiles, industry regulations, and specialised indicators with a human-in-the-loop validation process. Extensible data pipelines allow rapid fine-tuning of AI models and alignment with sector-specific challenges at minimal additional effort.
Six decision types AI-driven intelligence transforms
💡 Where to invest in research
By mapping publication momentum, patent activity, and funding flows across sectors, OPIX helps R&D leaders identify which technology areas are gaining real scientific traction — before investment decisions are made. Patent and publication co-analysis reveals where academic breakthroughs are approaching commercial readiness.
Technology Scouting
🔭 What technologies to track
LLM-powered extraction from the OpenAIRE Graph and patent databases identifies emerging technologies 12–24 months before they surface in industry reports — giving corporate R&D and government foresight teams the lead time to respond strategically rather than reactively.
Competitive Intelligence
📍 Who the key players are
Knowledge graph analysis maps the complete ecosystem of companies, research institutions, startups, and key researchers in any technology domain — revealing collaboration networks, competitive positioning, and the relative strengths of different national and regional innovation systems.
Programme Evaluation
📈 Whether R&I investment is working
By linking EU and national funding data to actual research outputs via OpenAIRE, OPIX enables systematic evaluation of whether funded programmes are generating the publications, datasets, patents, and commercial outcomes they were designed to produce — automatically and in near-real time.
Portfolio Alignment
🔄 How to align R&D with policy
Regulatory and policy data, fused with the scholarly and patent record, lets organisations align their R&D portfolios with evolving European frameworks — from the Green Deal to the AI Act — identifying where their activities are at risk of regulatory misalignment and where new funding opportunities are emerging.
Regional Benchmarking
🗺 How regions compare globally
Sector-specific indicators benchmark regional innovation ecosystems — universities, companies, research centres — against global peers using open scholarly data as the common evidential base. Essential for smart specialisation strategies and Horizon Europe programme design.
A new standard for evidence-based STI and R&D decisions
The OPIX–OpenAIRE collaboration points toward a new model: STI policy and R&D strategy grounded in open science, processed by sector-aware AI, and delivered through dashboards designed for decision-makers — not data scientists. Six data source categories. One unified intelligence layer. Continuously updated as the scholarly and commercial record evolves. This is what evidence-based innovation looks like at scale.
For European institutions navigating the EOSC Federation, for national agencies implementing Responsible Research Assessment, for R&D directors deciding where to place their next bets, and for innovation strategists tracking a rapidly shifting technological landscape — this combination of open science, multi-source data, and applied AI offers something genuinely new: intelligence that is open, verifiable, sector-specific, and built to evolve in step with the knowledge economy itself.
