Cogniflare works closely with Business and Technology stakeholders to translate their vision to reality. We use lean methodology to iteratively deliver features based on Minimum Viable Product.
Key principle/ ethos:
Building a model that could solve a particular problem/ use case within an organization is very common. However the common challenge is to operationalise the model and scale to the demands of the business, which includes integrating the model outcome to one or more downstream systems, continuous validation and training at enterprise level.
Our approach towards introducing and integrating actionable outcomes on key operational systems by complementing their existing process has been key for the success of our customers
With the explosion of IT systems and data collection efforts, organizations are now faced with an overwhelming amount of data. Having the ability to successfully navigate these data is becoming increasingly critical to remaining competitive in today’s business environment. Consequently the more data an organization has, the more resources are required to organize it, in order for it to be useful. This cost is prohibitive to the point of large amounts of data remaining ‘dark’. Illustrative examples of impacts of ‘dark data’ not feeding into decision making processes are numerous.
We help organisations to unlock the potential of their dark data with our innovative and disruptive solutions that will enable organisations to make the right decisions.
It’s key for enterprises to tap in sensitive operational data in real-time (RT) or near-to-realtime (NRT) that would influence key decision making both from a customer perspective and from an organisational perspective. However sourcing data from these operational systems having their unique challenges such as streaming data from a mobile network systems or production lines on manufacturing or mobile transport systems. The growing adoption of IOT further provides additional challenges. Our bespoke patterns enable organisations not only to stream data in RT but also empower in processing the data in RT and support in making the right decisions at the right time.