Over the years, we have developed deep inhouse expertise with Microsoft Academic Graph and more recently OpenAlex(OA). OA is a game changer for free metadata relating to a researcher’s outputs and often embeds knowledge from other sources.
Our consulting business is a specialized service designed to help organizations harness the full potential of open-source knowledge bases - including OpenAlex, arXiv, bioRxiv, Crossref, DBLP, and global patent databases such as USPTO, EPO, and WIPO. These datasets represent an unprecedented opportunity for research analytics, talent mapping, and innovation tracking - but they are also large, heterogeneous, and operationally complex.
While individual platforms like OpenAlex or arXiv offer structured access to metadata on publications, institutions, and authors, using them at scale requires significant data engineering, schema interpretation, entity disambiguation, and domain expertise. Scientometrics.ai brings years of experience working with these public datasets to help clients extract value without the overhead of building in-house infrastructure or teams.
For instance, answering questions like “How many generative AI papers did Anthropic and OpenAI publish on arXiv in the past 6 months?” or “What are the top-10 patent assignees in autonomous vehicles in the last 5 years?” is technically feasible - but requires connecting disjointed sources, building scalable querying systems, and maintaining entity mappings. Scientometrics.ai solves this by providing consulting, pipelines, and tailored dashboards that turn fragmented open data into actionable intelligence.
Clients include universities seeking publication trend dashboards, government agencies tracking national research output, and corporates conducting patent landscape analyses. For example, a UK research agency may want a monthly chart of publishing activity across Russell Group universities, while a deep tech VC may want to track AI patents filed by their portfolio companies globally.
Scientometrics.ai’s consulting stack includes:
ETL pipelines for ingesting and transforming massive open datasets
Entity disambiguation algorithms for authors, affiliations, and assignees
Topic classification models for grouping documents into meaningful research areas
Dashboarding and visualization layers built on scalable analytics platforms
Custom APIs or exports for integration into internal tools
By consolidating open knowledge streams into a single analytical layer, scientometrics.ai provides strategic insight for policy, hiring, funding, research direction, and IP evaluation. As open data ecosystems continue to expand, this consulting service enables organizations to stay ahead - without needing to become data infrastructure experts themselves.
Our consulting division is the bridge between open data and decision-making, empowering clients to fully leverage the wealth of global scientific and technical information now freely available.