CogniMatch

CogniMatch AI

Inspiration

For some, the thought of starting a conversation with "Let's start with an icebreaker" or "So, what do you do?" can feel dull or even anxiety-inducing. These boring openers often don't capture who we truly are or what we even care about.

We wondered: why not personalize our conversations based on deeper AI-driven insights-real personality, interests, speaking styles, and more?

Product Summary

By building agents that reflect our unique personality, attributes, and hobbies and then letting these agents interact in a controlled virtual environment, we can watch and tailor potential conversations even before they happen in the real world.

This approach has the potential to uplift matchmaking, social conversations, and even dating. Instead of relying on surface-level algorithms or arbitrary elo systems, we can create interactions that respects real personalities and create more authentic data-driven experiences. It's no longer simply a "swipe-left-or-right" interaction, but now a deeper exploration on compatibility based on how we may actually conversate with each other. By simulating these interactions, we can see firsthand where conversations flow naturally-and where they might get bumpy-giving us deep insights into who we actually connect with and why.

Agents

We utilized four specialized agents—Conversation, Safety, Evaluator, and Sentiment—each calling a different Gemini model variant.

Our agents were created by using chatGPT-o1 and other preprocessing techniques to create a profile of the user based on the results of the survey they've filled out at the beginning.

Conversation Agent

Uses Gemini 2.0 Flash for generating context-rich, dialog-style responses. This endpoint supports multimodal (text+image) prompts, so the agent can send and receive images from each other. This model was our model of choice as the huge one million context window allowed it to keep track of its user's generated profile, conversation history, previously sent images, and worked well for the task.

Safety Agent

Uses Gemini 1.5 Pro for deeper, policy-driven reasoning. Before or during chat, it checks if messages are safe to continue or if they violate safety guidelines.

Evaluator Agent

Also uses Gemini 1.5 Pro to analyze conversation logs to produce compatibility scores between speakers and in-depth analysis of the conversation.

Sentiment Agent

Uses Gemini 1.5 Flash (8B) (lightweight but powerful) to classify user utterance in real time-determining if the agent is engaged, bored, or excited based on the given user profile data too.