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Tulsk vs Referee.chat

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Tulsk compared with Referee.chat
DetailTulsk logo TulskReferee.chat logo Referee.chat
What it doesAutonomous AI agents that plan, execute, and deliver work without setup or babysitting An AI panel debates your goal; a referee rules on re-checkable evidence
StageStartup Not given
FoundedNot given Not given
Based inNot given Not given
Pricing modelFreemium Freemium
PricingFree: $0/month with unlimited projects and tasks plus $2 of agent work to get started, no credit card required. Starter: $39/month with $50 of agent work monthly and up to 6 AI agents. Pro: $99/month with $120 of agent work monthly and unlimited agents, marked as most popular. Enterprise: custom pri Free: $1.00 starting credit once. Credit plans from $10 top-up with no expiration. Your own key: 5% infrastructure fee after the first $5.00 of usage.
Key features
  • Create agents by describing their role in natural language; Tulsk automatically builds them with the right skills, tools, and schedules
  • Agents run continuously in the cloud on schedules, events, mentions, or connected channels without user intervention
  • Memory system that learns preferences and project context, separated between personal and team-shared knowledge
  • Reusable skills that agents follow consistently without re-explanation across the entire team
  • Approval system for writes to connected apps and new connections before agents act
  • Connect Slack, Telegram, or WhatsApp for agents to receive and respond to messages with the team's preferred communication tools
  • Real workspace files created by agents with live preview; files persist even when the workspace computer sleeps
  • Mac desktop app for quick access via keyboard shortcut to chat, inbox, and workspace in any application
  • Panel of up to six AI models from different vendors
  • Referee rules on re-checkable evidence only
  • Searches academic databases: arXiv, OpenAlex, Crossref, Europe PMC
  • Executes Python code to verify claims
  • Customizable acceptance standards
  • Matches pause and resume without losing work
  • Shared ledger prevents re-derivation
  • Spending limit per match
What makes it different
  • Agents run autonomously in the cloud without requiring setup, configuration screens, or DevOps knowledge
  • Integration with any HTTP API, MCP server, or internal company API without agents being limited to one suite
  • Reusable skills and shared knowledge layer allow teams to teach patterns once and have all agents follow them consistently
  • Free tier with unlimited projects and tasks plus $2 of agent work lets teams start and explore without credit card commitment
  • Referee decides on evidence, not argument quality
  • Panel from different vendors fails in different directions
  • Stuck is a targeted question, not model thrashing
  • Cost grows with ledger, not round count
  • Published matches become research record
Community votes00
DR (Domain Rating by Ahrefs)23 no change since last check2 no change since last check
Trust Flow (Majestic)30
Citation Flow (Majestic)3013
Referring domains (Majestic)12231

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