The application introduced dedicated inputs for both contextual background and user roles, allowing individuals to define the scenario and their position within the organization before initiating a query. This structured framing helps the AI interpret intent more accurately, resulting in responses that are highly relevant, situation-aware, and aligned with organizational workflows rather than generic outputs.

Users can ask questions within structured threads, enabling conversations to evolve naturally over time. At any point, users can dive deeper into responses, refine queries, or explore subtopics without losing context. Sorting and filtering options further help users analyze information based on specific conditions, making research and decision-making more focused and efficient.

Knowledge sharing is a core capability of the platform, enabling users to collaborate effortlessly across teams. Entire chat threads can be shared with a single click, allowing insights, discussions, and outcomes to be reused without duplication. This feature ensures faster alignment across teams and promotes consistent knowledge dissemination throughout the organization.

The platform organizes conversations into domain-specific categories such as marketing, sales, or operations. This structure allows users to access relevant discussions, gain insights from peers working in similar areas, and contribute domain expertise. By grouping conversations by function, the platform enhances discoverability and encourages meaningful cross-team learning.

Recognizing varying business needs, the platform adopts a pay-per-usage model instead of fixed user limits. This approach allows organizations to scale usage based on demand, ensuring cost efficiency and flexibility. Teams can adopt the platform for daily operations without being constrained by rigid licensing structures, making it suitable for both growing and large enterprises.