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With over 25 years of experience, we offer our clients a broad set of strategic and technical guidance in the adoption of advanced technology. From Solutions Design to Technical Architecture implementation, from usability of search solutions and semantic technologies to generative topic modeling and information supply chain architecture, we have helped companies large and small to evolve, produce, and compete at levels and in ways they had previously not thought possible. And while we are proud of our clients, we take even greater pride in what we have been able to help them achieve.
Designed and developed an enhanced search experience, offering greater awareness of end-user intent, click-through rate, and valuation of content - both published and social media. Moved end-user search experience from transactional, to "search as a conversation" boosting organic web traffic and retention. Developed an automated visually oriented taxonomical view of diverse content, from proprietary research to chat-room.
Search & Big Data
Conceived and developed a visually-oriented API Testing Framework for big data to facilitate the on-going evolution of a complex set of search and storage APIs providing client with an immediate ROI and dramatically reducing future development and maintenance costs.
Designed and developed an advanced interactive search solution for large internet search provider. Developed search experience strategy to contend with wide diversity of content and end-users. Designed a "Search as Way Finding" User Interface leveraging dynamic faceting of content to automatically generate an intuitive information topology.
Enabled client to realized a $13.5 million ROI within 6 months. Developed a gracefully degrading entity extraction API to ensure high precision without a loss in volume while robustly contending with a myriad of bad data phenomenon (encoding and diacritic transliteration failures to transposed and missing values).
Conceived and developed advanced content enrichment technique (Chained Context Discovery) to generate an empirical taxonomy of mixed content (both text and HTML). Implemented generative Topic Modeling using stochastic mathematical methods ranging from classic Latent Dirichlet Allocation (LDA) to Hierarchical Pachinko Allocation Model (PAM). Designed and implemented an interactive visual anlaytic environment for exploring and critiquing generative topic models
Conceived and developed an enhanced content search and modeling solution with compound search algorithms and visual analytics to enable new research in finance and economics.