ARCHITECTING ENTERPRISE INTELLIGENCE

We understand that digital transformation is a journey that requires adoption by the entire organization. It’s more than just data-driven business solutioning; it’s a culture change. This is why in our Enterprise Intelligence Hub, we have designed an Analytics Center of Excellence (ACE) with Data Science capabilities that enable our clients to “learn to learn faster.” Our analytics and AI/ML solutions facilitate both Culture and Business transformation, leveraging domain knowledge with cognitive computing to produce unbiased learning accelerators for different parts of our client’s business.

Leaps beyond the typical RPA, our smart automation consulting service considers the full spectrum of productization, taking into account the importance of adoption in our clients’ organizations and their customers. Leveraging our proprietary graph and ontology-driven computer vision and ML techniques, we build self-patching and evolving document readers and writers, scene diagnostic engines, robotic assistants, matching engines, and behavioral shaping interfaces.

Discover new signals through AI/ML engines that can sift through multiple dimensions of data, using evolutionary knowledge graphs powered by self-learning ontologies. With the multi-dimensionality of our learning engines, we help companies build resilient models that adjust to contemporary events. We detect early indicators of fraud and financial stress, disease outbreaks, net promoter changes, claims and chargeback uptrends, and more.

We build predictive and prescriptive algorithms with our clients, incorporating domain expertise from the business, and future-ready algorithmic designs that leverage ontology-based networks. It enables our clients to predict and decide on insights generated in real-time as their data.

During our initial assessment of client’s data and business objectives we often discover that the metrics being used are due for redesign, for they no longer capture what is important to the business or do not confirm to contemporary business goals. Our Metrics design service does an inventory of current metrics and data assets. It further explores alternatives and designs new ones that fit-for-purpose to our client’s business objectives based on the assessment.

From insightful data visualizations to designing and implementing smart, dynamic reports, we help our clients derive layered insights from their data assets, enabling analysts and business leaders to sift the right information for their business objectives quickly.

Design, construct, and maintain a secure and scalable environment where the enterprise’s entire corpus of data is always available and accessible.

Enterprise Data Bus (EDB) is a modern data hub that creates visibility to all the data, centralizes the control, and provides a toolset to create diverse views for multiple businesses and IT purposes. It is a modernized architecture, a framework, and an orchestration of software tools, workflows, and infrastructure that allows a data-driven enterprise to capture, store, analyze, and act on the corpus of enterprise data.

We help clients prioritize their enterprise data sources and provide valuable context to data to drive insights on the business processes. This AI-driven toolset allows for the ingestion of diverse data sets into the data process flow, reducing the time and resources required to gather and input source data.

We help enterprises identify, acquire, store, manage, and transform data to fuel impactful business insights. In the process, we deliver higher and regulatory-compliant business value. We employ leading data-management technologies to help our clients and remain engaged with them to minimize the lifetime costs of their technology choices.

We work with our clients through a collaborative approach to curate, govern, and master data throughout its life cycle. This approach helps drive impactful insights and fuels business processes to function at peak efficiencies. We employ leading data management technologies to help our clients minimize the lifetime costs of their technology choices.