Funding
Funding not disclosed
Founders
Product
Problem
AI agents are typically built and used by a single engineer, causing the organization’s collective knowledge to remain siloed and limiting the agent’s usefulness across the team. This results in duplicated effort and underutilized expertise when only one person can access the agent’s capabilities.
Solution
Unfairly provides a model‑agnostic multiplayer context layer that lets teams share and augment AI agents with organization‑wide knowledge. Builders connect data sources such as Slack, GitHub, Notion, and Google Drive, which are automatically chunked, embedded, and indexed into a shared vault. Oracles—domain experts—contribute trusted information through a simple chat interface without writing code. Players query the agent and receive answers enriched by the combined knowledge of the entire team, with trust‑aware retrieval ensuring reliable results. The platform exposes a Model Context Protocol (MCP) server that integrates with any MCP‑compatible client (e.g., Claude, ChatGPT, Cursor), delivering semantic search, retrieval, and real‑time collaboration via a single endpoint.
Target Audience
Primary customers are product and engineering teams that develop AI agents and need to embed organization‑wide expertise, including builders, domain experts, and end‑users who query the agents.
Features
- Connectors for common enterprise sources (Slack, GitHub, Notion, Google Drive) with automatic chunking, embedding, and indexing
- Trust‑tiered knowledge management allowing builders to set access and reliability levels for contributed data
- Role‑based workflow (Builder, Oracle, Player) that separates engineering, domain expertise, and end‑user querying
- Model‑agnostic MCP server providing semantic search, trust‑aware retrieval, and real‑time multiplayer context for any LLM client
- Incremental sync and vectorized indexing for up‑to‑date knowledge across the organization
- Simple SDK configuration (unfairly.config.ts) and one‑command deployment for rapid production rollout