Ontology’s goal is to supply pervasive, low-cost search access to all enterprise application data; in a manner comparable to that of a search engine, users can apply their own domain knowledge as they search and surf their way to the information they need. Over time, through a series of short, inexpensive projects, organizations can then elect to incrementally capture more and more domain knowledge, business entities and dependencies within the semantic model, all while improving the accuracy and automation of the results that are returned.

“We want to change the economics of data integration,” Enweani explained, “and provide a low-cost way to gain access to all of the information currently fragmented across enterprise applications” as well as “a way to improve the search experience to deliver more and more value to [a] business over time.”

This approach considerably shrinks the cost of offering search access to combined data. “We’re lowering the cost per datum,” he says. “We are doing away with the need to manually link unstructured data such as text documents and integrate structured data in management systems.”

Ontology's 4.0 release, or "Project Rothko" delivers solutions like Service Impact Analysis quickly, and combines data for migrations or MDM correlation because it is built upon five principles:

• no schemas
• no integration
• no “big bang”
• no search restrictions
• no upfront risk

Because Ontology eliminates the time needed to create and integrate a schema, it consistently deploys in scenarios of 8-18 weeks, whereas traditional approaches would take 8-18 months. And because deriving structural information from raw data is less expensive than hiring analysts to integrate said schema, Ontology is able to deploy with as little as one tenth of the expected cost of professional services.

Once it developed its “Search, don’t integrate” philosophy, Ontology had to convince other companies that there was a clear advantage to be gained in using its technology rather than heavy integration. “This year CIOs and directors of operations are willing to stand up and say, ‘Yes, this works!’” says Enweani. “And it works in about one quarter of the duration of a typical project.”

There are two product versions currently being used in both the telco and financial services industries . The first, Ontology Intelligent 360, is capable of providing real-time search and impact analysis along with dependency mapping and a 360-degree view of business entities; the second, Ontology Integrity Manager, specializes in data alignment, migration, reporting, and other data analysis-based applications. Both are available via a hosted software-as-a-service (SaaS) solution or perpetual license.

“Ontology has already proved [to be] a valuable tool for Neotel, and we are pleased to extend our use of Ontology to help improve our service management,” says Phinda Ncala, chief information officer for the South African CSP. “The SaaS deployment option provides Neotel with a low monthly cost, and we are looking forward to this solution helping us to recognize even more benefits for our business and customers.”

A 360-degree view: the big picture

Other CSPs, such as Tata Communications, the majority shareholder of Neotel, and Level 3 Communications, make use of Ontology’s ability to join billing, service and equipment silos that were never intended to be integrated in the first place. Instead of relying on database identifiers, the data is associated by semantically inferred links using patterns or rules, thus enabling dashboards, for instance, centered on dispute resolutions in the areas of customer service, audit and billing. Financial enterprises can use this same capability to classify, group and order the many types of communications that involve the same parties or trades, e.g., for applications like Dodd-Frank trade reconstruction, and to generate a single view of a customer or trade.

Business dependency mapping

Telenor Group, Vodafone SA and Internet Solutions have all used Ontology Intelligent 360 for SIA to find entities and relationships that are shared across systems, and they create alarms when customers or services are impacted, whether by unforeseen network faults or planned changes. The same real-time SIA engine is used by financial enterprises to track the margin impact caused by market events. Investment banks are also exploring Ontology's solution as a prospective platform for risk data aggregation (RDA).