AgentGate – Group chat speak-or-not guard

Decide when an AI agent in a group chat should stay silent, not reply to everything

Problem

Teams adding coding agents to Slack/GitHub find agents don't know when to speak. Every message triggers a full LLM call to decide if a reply is needed, adding noticeable latency, and the model often returns explanations instead of a clean boolean, forcing string parsing hacks. Eventually the channel gets noisy and the agent is removed.

Solution

A lightweight 'should-reply' middleware that uses a typed, probabilistic decision model instead of full LLM calls to quickly decide if a message needs agent attention. Supports rule config, confidence thresholds, and quiet periods to cut latency and cost.

Users

Developers and teams integrating AI agents into Slack, Discord, or other team chat tools

MVP

Self-hostable decision service or SDK; declarative rules (keywords, context, rate limits); returns probabilistic boolean instead of text; simple config panel and examples; drop-in integration with existing agent flows

Revenue

Open-core with paid cloud hosting; usage-based API pricing; enterprise tier for custom models and private deployment

Why now

Agent-in-chat adoption is rising, yet the 'should I reply?' decision still relies on costly full LLM calls; indie devs can ship a fast classifier-based alternative