Cognitive Solutions

A platform designed to build GenAI assistants, by providing client specialists with innovative tools to customize content, style, interaction flow, and integrations. These tools enable the specialists to monitor and tune the assistant to deliver reliable and valuable responses for real business cases.

Empower your Business Specialists

Our platform's strength lies in the involvement of business specialists who are integral to the successful functioning of our solutions. These specialists play a vital role in tuning, monitoring, and ensuring that the AI assistants continue to respond accurately and reliably. Far from replacing the work of these experts, our technology depends on their unique insights to amplify and scale their efforts. By incorporating their knowledge, style, and form, we control AI capabilities to serve specific business needs, ensuring that it acts as an extension of the specialists' expertise rather than a substitute.

Cognitive Assistants

Cognitive Assistants are advanced AI-powered solutions built upon Large Language Models (LLMs) that provide conversational assistance tailored to specific domains, or guide users through organizational processes. They are not rigid, predefined pathways but instead offer flexible and personalized interactions. These assistants adapt to the user's individual knowledge level and needs, creating a responsive and intuitive conversational flow.

Innovative Tools

To empower business specialists, we surround them with a suite of innovative tools, specially designed to personalize and monitor their AI assistants.

• Self-improvement Module During the construction stage, the functional expert can decide to enter self-improvement mode, to dialog with the assistant, give feedback, suggest desired answers, make corrections. This process allows the assistant to automatically modify different components of the implementation until reaching the answer desired by the expert.
• Implementation Module Where assistants, techniques, tools (default and custom), configurations, prompting and information sources are defined and managed.
• Evaluation Module Component used in implementations to measure the performance of the assistant at each stage of the process. Using LLM-based metrics, embedding-based metrics, and traditional NLP metrics, we generate reports for the client with the assistant's performance at a given moment. After the implementation stage, it is periodically run as regression tests.
• Monitoring Module Where the client can see in real time (and in pre-built dashboards) all interactions with the assistant and user feedback.