What is our primary use case?
My main use case for OpenLink Virtuoso involves using the infrastructure for an application I call Mama Africa, a source-grounded cultural knowledge application. The objective is to let someone ask a question and receive information drawn from identifiable records with references they could inspect.
A quick specific example of how I use OpenLink Virtuoso in that application includes using it as a combination of RDF, SPARQL, and named graphs. It gives me a structured way to retrieve relationships rather than depend only on loosely matched text. Resource identifiers and graph references also make it possible to carry the source into the application response, which matters because the user can inspect the evidence behind the statement instead of being asked to trust the answer alone.
A practical example of how I actually made use of this is a question about Egusi. Egusi soup is a native soup here in Africa, and the application retrieves the relevant cultural record and reports what that is. It does not turn a food association into a claim about someone's personal ancestry.
How has it helped my organization?
OpenLink Virtuoso has made a positive difference for my organization, both structurally and in projects that I have worked on, by giving me a structured way to retrieve relationships rather than depend on loosely matched text. Resource identifiers and graph references also make it possible to carry the source into the application response, which matters because it allows the user to inspect the evidence behind the statements instead of being asked to trust the answer alone. This is a very important feature, and it has helped my organization in the way we deliver, both in retrieval and in projects that we are delivering. It makes clear governance in most of our AI automated workflows, being more precise for the user, so that it is not about giving someone a trust that can fail, but instead, a trust made structural here.
What is most valuable?
The best features OpenLink Virtuoso offers include data virtualization, which makes it possible for me to query directly on an ontology, from an ontology to a knowledge graph. The benefit is that published ontology data becomes usable inside an application workflow, allowing us to move from a question to retrieve records and then to a source reference response. I have not measured the percentage improvement to productivity or revenue, but the outcome I can speak to directly is a working retrieval path that makes the supporting record visible.
What stands out the most about the data virtualization feature for me is both the flexibility and the speed, along with the precision at which this actually happens. Most times, we capitalize on speed and forget that when there is speed and no precision, we have lost the main aim at which that particular capability was there in the first place. OpenLink Virtuoso actually helps make sure that alignment is possible.
Regarding OpenLink Virtuoso's AI capabilities, I find its governance and security to be very sound. Many of the AI tools currently operate under the misconception that governance is just about directing the AI to behave. What I noticed about Virtuoso is that its AI capabilities concerning governance give me the flexibility to decide how the runtime architecture itself should behave, not just the model, but its runtime gives me that flexibility to determine how the fundamental machine itself should respond before the model generates even a word.
When using OpenLink Virtuoso's AI features, I find the results to be accurate and reliable because most times they are structural, and that contributes to my efforts to extend the answers to point to a particular knowledge graph. Its responses are sound because they come back with a reference that is actually strong. It does not provide vague responses, so its AI feature, referred to as OPAL, is sound because it improves the structure of how a knowledge graph type of application functions.
What needs improvement?
From an application developer perspective, I would value more end-to-end examples, including examples covering named graph discovery, SPARQL JSON processing, and error handling. These are important steps between understanding the technology and integrating it into a user-facing workflow.
Challenges and improvements required careful handling of graph selection, query structure, and return results. We had to distinguish an empty result from an endpoint failure and avoid treating ambiguous graph selection as a successful lookup. Additionally, we needed to configure certificate trust correctly in our Node.js environment, which I would describe as an integration issue we addressed rather than assume it was a database defect.
For how long have I used the solution?
I have been using OpenLink Virtuoso for about a year now, since November 2023 until now.
What was our ROI?
Regarding specific outcomes or metrics since implementing OpenLink Virtuoso, I have not measured the percentage improvements in productivity or revenue yet. However, it has helped to ensure that we have received referrals and customers coming back to say that they liked the way we implemented the project that they gave us to handle. In terms of measuring percentages, I have not come down to measure them yet because we are waiting for each quarter to make those particular measures. It is not yet up to the quarter for us to give those metrics.
What other advice do I have?
My advice for others looking into using OpenLink Virtuoso is to begin with a clearly defined data set and retrieval questions. Verify the results and preserve that information into the application, as that is where the value becomes concrete for my work. I also recommend evaluating Virtuoso for applications that need standard-based access to linked structured knowledge and relationships.
OpenLink Virtuoso has helped my organization gain a way to actually administer structural trust, and when something provides me a way to do that, it is something that is very hard. This is something that is theorized in the ecosystem, and being able to make it structural is a very big plus for me. I rate OpenLink Virtuoso an eight out of ten because the reason I cannot give it nine or ten yet is that I have not measured the metrics to confirm confidently that I can give it a higher rating.
Which deployment model are you using for this solution?
On-premises
