Ontotext Expands To Help More Enterprises Turn Their Data into Competitive Advantage

Join us for a review of our accomplishments and plans for the next few years

December 30, 2022 8 mins. read Atanas KiryakovDeron RyanDeron RyanDoug KimballDoug Kimball


Christmas is a wonderful time to look back, appreciate and discuss plans for the coming year. In this post, we want to share with you, our customers, partners and fans, a high level view of our accomplishments and plans for the next few years. Those are bold plans, because in 2022 we received recognition for what we’ve achieved through investment to help us expand, accelerate growth and engage the market with the technology we’ve been developing for 20 years. This makes 2023 both a very challenging and exciting year!

Have a cup of tea or a glass of wine and enjoy the story!

The first 18 years: Develop vision and products and deliver to innovation leaders

Ontotext started in 2000 as an R&D lab, led by now CEO Atanas Kiryakov, becoming one of the pioneers of the Semantic Web. 9 years of research, prototyping and experimentation went into developing enterprise ready Semantic Technology products. In 2008, we received a small round of funding and focused on bringing this technology to the market.

We have exciting success stories, including the first and popular mission critical implementation of knowledge graphs – BBC’s website for the FIFA world cup in 2010. We have delivered technology and solutions to global leaders across several sectors: publishing (FT, Elsevier), financial services (S&P), pharma (AstraZeneca), government (UK Parliament) and others.

The last 3 years: Turn a boutique shop into scalable technology business

In 2019 the market for graph databases and knowledge graphs started heating up – appearing on Gartner’s hype curves in 2018. Over the next 3 years Ontotext transformed itself into a product focused company with over 30% revenue growth.

A major game changer was developing a rich partner ecosystem, including the best semantic technology providers, specialized consultants and global system integrators. We developed OEM partnerships, where our GraphDB engine powers industry specific solutions. Such an example is supporting Johnson Controls’ leading building management system, which operates tens of thousands of buildings around the world.

The next 3 years: World domination!

In September 2022 we received a €11million investment from a consortium of three investors: Integral Venture Partners, PortfoLion Capital Partners and Carpathian Partners. This recognition for the development and strength of Ontotext gives us the resources to properly compete in the graph technology market where other knowledge graph players already had substantial investments.

Supported by new capital, Ontotext is accelerating international expansion and go-to-market operations, adding direct sales and marketing in North America and growing our partner network. We will invest further in extending our product stack, adding solution accelerators for specific industries as well as cross-industry demonstrators. Our focus is on making it easier for our customers and partners to develop knowledge graph-based solutions.

In 2022 we already made two great steps in this direction, releasing:

  • Target Discovery – a solution for accelerates drug development and
  • Metadata Studio – our new product for streamlining the development and operation of solutions involving text analysis.

GraphDB: Faster and more versatile

2022 was very exciting on the core technical side as well. In June, GraphDB 10 was released, with improvements to make our advanced data management technology more robust and easy to operate. GraphDB 10 brings smarter and simpler cluster architecture enabling, among other benefits, best in class resilience and reduced infrastructure costs. With our customers top of mind, especially those new to knowledge graphs, we provided interactive user guides to speed understanding and implementation.

Significant engine optimizations made GraphDB more powerful and more efficient across a wider set of workloads. As a result, query performance improved by 30% to 50%, and delivered lower memory usage, most beneficial in larger datasets. Typical memory usage is now 15% to 20% less.

GraphDB 10 passed the LDBC Semantic Network Benchmark (SNB), making it the only RDF database that does so. SNB is the most comprehensive benchmark for graph analytics and was previously targeted at labeled property graph (LPG) engines. We are in the process of auditing SNB results as well as the improved results of GraphDB on the knowledge graph-centric Semantic Publishing Benchmark (SPB).

Our product roadmap: Make knowledge graphs easier to start and quicker to deliver value

Ten years ago there was a single commercial Knowledge Graph used by Google to gain competitive advantage against the other web-to-customer) giants. Since then there have been many successful projects across industry verticals. However, knowledge graphs were generally only affordable for larger enterprises with the most mature IT teams and knowledge management capabilities. Ontotext’s mission is to lower barriers to entry and bring this technology into the mainstream.

Of course, there is still heavy lifting needed to lower the cost, risk and time-to-value of such an advanced knowledge management technology. Getting there boils down to making multiple aspects of development of a knowledge graph-based solution easier such as:

Domain knowledge models – those are the main ingredients, the “special sauce” of knowledge graphs, which allows them to offer better data interpretation. However, developing these models from scratch for each and every solution can be slow, expensive and risky. Ontotext develops re-usable domain models as pre-packaged knowledge graphs. Such examples are our Linked Life Data Inventory and Company Graph for entity intelligence. The new investment will accelerate these efforts, creating more and improving existing ones, to allow implementing solutions in a matter of months, instead of years.
Data sourcing – knowledge graphs enable deeper insights to be gained from distributed data. Domain knowledge must be linked to that data, requiring substantial ETL and data integration work. Ontotext will integrate our engine with enterprise data management platforms, such as Databricks, Dremio and Snowflake, in order to increase the efficiency of data unification. We will also develop connectors for popular enterprise software systems such as CRM, ERP or CMS.
IT operations and cloud – Supporting the increase in cloud migrations, we are making knowledge graph based solutions easier to operate in complex IT enterprise ecosystems. Additionally, we have a growing number of customers using managed services, where we are in charge to guarantee availability, response times and updates. The next step in our roadmap is to make GraphDB available through Amazon and other cloud providers via a pay-per-use model.
Analytics, AI, ML – our products already offer numerous capabilities for information extraction, data linking, search and ranking based on graph analytics, word- and graph-embedding, neural networks and other ML techniques. Still, there is a lot more that we plan to do to make it easier for data scientists and subject matter experts to experiment with different models, fine-tune and retrain when necessary. Our plans foresee integration of the most popular ML libraries and environments as well as operational improvements of the built-in algorithms.

Global Sales planning

Ontotext developed its portfolio of reference clients and global success stories with limited sales and marketing resources. In recent years, more than 50% of our revenues came from North America, without any sales people based in that region. We grew the business from our European headquarters mostly by handling inbound inquiries. But while it’s possible to grow based on the popularity of the solutions and word of mouth, to accelerate this growth, we had to take a more proactive approach.

Since joining Ontotext in July, Chief Commercial Officer Deron Ryan’s primary focus has been to establish the U.S. direct sales operation. His secondary objective was to ensure the U.S. expansion aligned with the team of experienced sales professionals within Ontotext. With these changes, Ontotext is better positioned to execute and benefit our clients globally, with a stronger focus on industries, better OEM partner management and experienced solution architects.

We have a tremendous opportunity ahead to establish Ontotext as the market leader in the knowledge graph space – said Deron. – I am excited about the plan designed to bring better value to our customers and have great confidence that our talented global sales team will deliver the results our investors expect.

Taking Marketing to the next level

Also joining Ontotext is Doug Kimball, coming on board early November as Chief Marketing Officer. Supporting both North American and global marketing expansion, Doug is excited about the opportunity to support a growing marketing team to best tell the story of knowledge graphs.

I see so much value across multiple industries for the power of what knowledge graphs enable, bringing deeper insights from the data that enterprises have. With the continuing struggles of finding and sharing information from all this data out there, Ontotext is positioned well to help organizations maximize IT resources, support customer focus and get more value from their digital assets.

Wrap up

As we enter 2023, we are looking forward to doing more to deliver value for our customers and future clients. Our solutions continue to evolve and improve, keeping business needs in mind, and we are focused on shortening time to delivery and value. With our new leadership in Sales and Marketing, solid investment due to our continued success, and even clearer focus and support for our clients in supporting data modernization with knowledge graphs, the future that will be delivered by Ontotext is bright!

Article's content

CEO at Ontotext

Atanas is a leading expert in semantic databases, author of multiple signature industry publications, including chapters from the widely acclaimed Handbook of Semantic Web Technologies.

Deron Ryan

Deron Ryan

CCO at Ontotext

With more than 20 years of sales leadership experience across diverse industries, Deron has a strong track record of building and leading high-performance sales teams that catalyze exponential growth.

Doug Kimball

Doug Kimball

CMO at Ontotext

Doug is a business and technology evangelist focusing on advancements that can be applied to e-commerce, customer centricity and insights development in the data management space.

Prioritizing Data: Why a Solid Data Management Strategy Will Be Critical in 2024

Ontotext’s CEO Atanas Kiryakov talks to TDWI about data and knowledge management trends he expects to emerge in 2024

You Cannot Get to the Moon on a Bike!

Read about the impacts of complexity on the growth and efficiency of big enterprises and the way knowledge graphs help organisations get richer insights from data in less time

Benchmark Results Position GraphDB As the Most Versatile Graph Database Engine

GraphDB is the first engine to pass both LDBC Social Network and Semantic Publishing benchmarks, proving its unique capability to handle graph analytics and metadata management workloads simultaneously.

Ontotext Expands To Help More Enterprises Turn Their Data into Competitive Advantage

Join us for a review of our accomplishments and plans for the next few years. Have a cup of tea or a glass of wine and enjoy the story!

Reasoning with Big Knowledge Graphs: Choices, Pitfalls and Proven Recipes

Read about how to use reasoning to enrich big knowledge graphs with new facts and relationships, avoiding the typical pitfalls and reaping all the benefits

At Center Stage IV: Ontotext Webinars About How GraphDB Levels the Field Between RDF and Property Graphs

Read about how GraphDB eliminates the main limitations of RDF vs LPG by enabling edge properties with RDF-star and key graph analytics within SPARQL queries with the Graph Path Search plug-in.

The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

Read about how the Semantic Web vision reincarnated in thousands of Linked Open Data datasets and millions of Schema.org tagged webpages. And how it enables knowledge graphs to smarten up enterprises data.

Ontotext Comes of Age: Increased Efficiency, New Technology, Big Partners and Big AI Plans

Read about the important and exciting developments in Ontotext as we are closing up 2018.

Linked Leaks: A Smart Dive into Analyzing the Panama Papers

Learn about how, to help data enthusiasts and investigative journalists effectively search and explore the Panama Papers data, Ontotext created Linked Leaks.

Practical Big Data Analytics For Financials

Learn more about the benefits of big data – from keeping up with compliance standards & increasing customer satisfaction to revenue increase.

Triplestores are Proven as Operational Graph Databases

Dive into the theory of how RDF triplestores work and how they can support graph-traversal efficiently.

Industry Relevance of the Semantic Publishing Benchmark

Learn how the Semantic Publishing model for using Semantic Technology in media and how the Semantic Publishing Benchmark is utilized by organizations to tag information.