Semantic Arts teams with reputable companies dedicated to applying semantic technology in systems, creating simpler information systems for clients.

Alion Science and Technology delivers advanced engineering, IT and operational solutions to strengthen national security and drive business results. We worked with Alion to deliver ontology support for the JPOD, which is a joint project between NASA, the Air Force and the FAA to coordinate information about the shared airspace.

Be Informed is an internationally operating, independent software vendor. The Be Informed business process platform transforms administrative processes. We worked with Be Informed on the P&G project to redefine how they tracked and obtained approval for materials used in their many projects worldwide.

Coherent Knowledge offers the tools the increasingly knowledge-based economy needs. We teamed with Coherent Knowledge on the Schneider –Electric project to create a semantic rule based approach to electric product configuration.

Global IDs allows organizations to follow a systematic approach to taking cost out the data ecosystem. We have just penned our MSA with Global IDs and plan to begin a joint project soon.

Mphasis is a leading IT solutions provider, offering Applications, Business Process Outsourcing (BPO) and Infrastructure services globally through a combination of technology knowhow, domain and process expertise. We worked with Mphasis on the Schneider-Electric project to define the ontology and help with their building of semantic based architecture and User Interface.

Sagence understands the linkage between data management and analytics to accelerate data ROI and drive competitive advantage. We have worked with Sagence on all three of our projects at Goldman Sachs, brining semantic technology to bear on Activity Based Costing, Risk Classification and Resolution Planning.

We worked with Soal on creating an enterprise architecture and a long range plan for the Texas Teachers Retirement System.

We have worked with Xypress on the Broadridge Financial projects to create ontological representations of their legacy systems.

We have taught our DBBO course at least six times using TopBraid and Maestro from TopQuadrant. We also used TopBraid on our ontology building projects with P&G, Sallie Mae and LexisNexis.

We teamed with 3 round stones on a project at Sentara to build a personalized medicine mashup. The proof of concept combined anonymized discharge records from asthmatic hospital admissions, and very detailed air quality information from the EPA. The air data included 5 air components (Ozone, Nitrous Oxide, Carbon Monoxide, Sulfur Dioxide and Small Particulates) by day for the zip code of the patients residence. The mash up allowed patients to see the specific components of the air on the days they were admitted and had the same information for the current date.

We worked with ROI consultants on a workshop for JP Morgan in Bournemouth, England.

We worked with a Progress team at Sallie Mae to convert our ontology into a canonical message model in the Progress tool DXSI, and then subsequently built out the SOA messages to support the integration of a new line of business with Sallie Mae’s existing applications and architecture. We are currently evaluating the Corticon suite for compatibility with the architectures we are deploying.

Capsenta sell the UltraWrap product which is a delivery platform for attaching to Relational databases and extracting RDF triples. The product supports the R2RML standard and the same maps can be used either in an ETL style architecture for populating triple stores, or in the NoETL mode, where it acts as a federator allowing a single SPARQL query to be resolved over potentially many relational databases. We have used the Capsenta UltraWrap product on our engagement with Schneider-Electric to populate their next generation semantic product data system. We have also worked with Capsenta on several proof of concept projects.

Lymba sell a suite of products including the K-Extractor. The K-Extractor can extract RDF triples from unstructured documents. In the default configuration it extracts a small set of known predicates. They have a rule writing capability that allows both the recognition as well as the mapping to a specific (Enterprise) ontology. Two of our consultants have been trained to write these custom rules, and we are about to build a proof of concept using K-Extractor to extract information from documents to adjust their retention classification.

We have just inked a deal with Price Waterhouse Coopers that sets us up to work in either of three modes:

They can subcontract us as experts on their projects that involve semantic technology; we can subcontract them either in areas of their vast domain expertise, or to help scale out (sometimes projects need more resources); we can jointly bid on projects that combine our skills.

We have been working with them on a very informal level with one of our investment bank clients for over a year.  Now that we have a formal relationship we are looking forward to extending this relationship and extending it to other clients.