CoArena GTM brain

CoArena offers a live computer-use model arena and leaderboard for users comparing agents and AI labs seeking real-task evaluation data.

category

Computer-use agent evaluation

market profile

  • text: Computer-use model evaluation benefits from real user tasks and blind preference comparisons, beyond static benchmark scores.
  • text: The product has a two-sided audience: people submit tasks and judge results, while AI labs can use evaluation and training data.

personas

  • title: AI evaluation or model research lead
    pains:
    • Static benchmarks may not reflect real user workflows
    • Collecting independent comparisons across competing agents is expensive
  • title: AI product or agent engineering lead
    pains:
    • Selecting a model for computer and phone tasks without comparable real-world evidence
    • Testing model capabilities across diverse tasks and failure modes
  • title: AI-curious end user
    pains:
    • Comparing model performance without building separate integrations
    • Finding out whether an agent can complete an actual task

icp

  • text: Frontier model labs and agent builders evaluating or training computer-use systems, with a need for human preference data.
  • text: Developers and product teams choosing between AI models for browser, desktop or phone workflows.

message pillars

  • text: Test frontier models on tasks that matter to users.
  • text: Agents operate on actual device interfaces.
  • text: Make multiple models accessible through one API.

objections

  • objection: Are rankings independent if the operator also builds an agent?
    response: Review governance, blind comparison methodology and model-level sample sizes before relying on rankings.
  • objection: Does a leaderboard score predict our use case?
    response: Compare relevant task categories and validate on your own workflows, since aggregate preferences may not match local needs.
  • objection: What happens to task data or credentials?
    response: Review the current privacy, security and saved credential terms before submitting sensitive tasks.

competitors

  • name: Arena
    website: https://arena.ai/leaderboard/agent
    why: Publishes real-world agent rankings based on user sessions and task performance.
  • name: Steel
    website: https://leaderboard.steel.dev/
    why: Publishes open leaderboards for browser and computer-use agents.

keywords

  • computer use AI benchmark
  • computer use agent leaderboard
  • AI agent evaluation dataset
  • browser agent benchmark
  • human preference AI evaluation
  • compare computer use models

voice

  • Direct and experimental
  • Developer-friendly
  • Benchmark-focused

signals

  • text: An AI lab is training a new computer-use model and needs real tasks and human comparisons.
  • text: A product team is evaluating several models for an agentic desktop or phone workflow.

stack

  • Model API

pricing

model: free
starting price: $5 of model usage a day free

motion

community_led

channels

  • community
  • leaderboard
  • SEO
  • LinkedIn
  • YC launch

confidence

medium

Founders

  • name: Prateek Jannu
    title: Founder/CEO
    role: CEO
    bio: Prateek Jannu, Co-founder & CEO - Stanford (MS. EE) and Purdue (BE. CE). Invented Solo-Synth-GAN, which generates labeled training data from a single example. Built Coasty to #1 on the OSWorld benchmark (82%), beating Agent S3, UiPath, Kimi K2.5, and Claude Sonnet 4.5. Now building CoArena.
  • name: Nitish Kovuru
    title: Founder
    role: Founder
    bio: Co-founder and CTO/COO of Coarena, launched Coasty prev, SOTA CUA framework on OSWorld at 83% accuracy. Did CS at Columbia (Vision track) and hold a BS in Computer Engineering from Purdue, where I TA'd a graduate-level AI course as an undergrad and later went on to build enterprise sales automation agentic systems for my previous company.

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