AI-native Slack alternative for big teams and communities
New age desktop app for big teams and online communities. Less interruptions, more curious questions and discussion. Every day, millions of people use apps like Slack and Discord to access the specific knowledge of their peers, so you can get work done or pursue your hobbies and self-actualize. I've redesigned this experience to redefine how people self-actualize.
Integral used RAG (Retrieval-Augmented Generation) over community history to compose answers grounded in what the community had actually said, retrieving semantically relevant context from a knowledge graph rather than relying on model hallucination.
Integral's knowledge-graph layer linked people to topics, threads to artifacts, and questions to previous answers, allowing context to travel across conversations and making the community's collective knowledge discoverable and retrievable over time.
Integral embedded each message into a custom vector space using Google Vertex AI, collapsing paraphrases, languages, and jargon into the same semantic neighborhood for more intelligent context retrieval and linking.
Integral treated community output as durable artifacts by embedding every message, linking threads in a knowledge graph, and enabling semantic search across the community's entire history—solving the problem of important answers decaying into unsearchable history in platforms like Slack and Discord.