Getting relevant, accurate data from a reliable source requires man-hours; Clients do not want to pay extra for this, meaning extra hours will impact project economics
Data quality, accuracy and security are paramount – incorrect analysis and unreliable sources are detrimental to clients
Client-facing team members are often unwilling to dive deep into the data, or do not have the skillset to do so effectively
Without the right data and analysis, it is impossible to progress a project
Collecting inputs via an easy-to-use interface
Integrating with different types of data sources using automated tools
Once collected, cleaning and analyzing data from our data lakes using AI tools and human verification
Analyzed data is then turned into client-ready outputs