Teams experimenting with autonomous agents or multi-agent LLM setups lack visibility and control — agents run tasks, diverge from goals, or produce poor outputs that go unnoticed until human review. Current agent frameworks are developer-first and lack UX for non-engineers to steer, pause, or correct in-flight agent behavior.
Why now: As agentic patterns and multi-step LLM workflows proliferate, organizations need governance and UX layers to safely run agents in production.
A real-time dashboard for supervising LLM agents that shows step-by-step traces, current goals, confidence levels, resource usage, and dependency graphs. Humans can pause/inspect/override actions, inject corrective prompts, set safety/policy rules, and replay execution traces. Integrates with GitHub/Jira/Slack to surface agent decisions and offers templates for common steering strategies.
Built for: Teams building agentic workflows (product teams, AI ops, developer teams) who need operational control and auditability over autonomous LLM behavior
Business model: subscription
Agent Steering & Supervision Dashboard targets a small market ($10–100M TAM). Existing solutions are incomplete or outdated — there's clear room for a better product.
Underserved
Small
Startup (3 Months)
Medium
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Includes: 9 competitors found, 10 risks identified, full business plan, market research