TNQ transforms content for global leaders in STM publishing. The company has 18 years of experience in delivering to exacting SLAs and consistently high customer ratings.
TNQ puts machine learning behind its editorial teams worldwide. As demands rise, human intelligence is empowered to focus on the semantic and deliver great quality.
Machine-learning is the new Mark-up Language. The building blocks of journal production at TNQ are its auto structuring and auto conversion tools. The Auto Structuring tool creates mark up from input mark down. Our auto conversion tool, MLiFlow, renders the generic ML to standard ML and DTDs and Schema.
Can we automate the aesthetic of Page Composition? Can we eliminate DTP? Can we create a new Reader? Can we make the page faster, better - with or without DTP? Can we make the page fixed or fluid, print or electronic, computer or device? Can we deliver thousands in a day? Yes.
See samples. The interesting part is visual creation - Illustration, Interactive, Simulation and Animation for Science.
We transform the technologies and processes that transform content. We bet on the world's most open content standards - HTML and Unicode. We anticipate a future where a file becomes a URL. Instead of versions, we see Single URL Publishing.
Our technology products are author facing. Well, what does an author face today? Tedious submission systems. Long peer review cycles. Clumsy proofing. And uncertainties about how the content will eventually appear, if and when. Our SaaS platforms transform these, one process at a time.
TNQ has a 200+ people software services delivery organisation. The entire engineering team is domain aware. The development methodology is a unique hybrid of Agile and Waterfall. The practice is appraised for CMMI Level 3.