AfterQuery GTM brain

AfterQuery supplies expert-generated training data, evaluations, and agent environments to frontier AI labs and enterprises.

category

AI training data and evaluations

market profile

  • text: Frontier model teams need professional reasoning and workflow data beyond raw internet outputs.
  • text: The offering spans supervised fine-tuning, reinforcement learning rubrics, agent environments and computer-use trajectories.

personas

  • title: Head of post-training at a foundation model lab
    pains:
    • Training on final answers misses expert decision processes
    • Scalable reward signals are difficult to design for complex professional tasks
  • title: Enterprise AI evaluation lead
    pains:
    • Generic benchmarks do not show if an agent can complete domain-specific workflows
    • Obtaining qualified experts and realistic source documents takes time
  • title: Agent research engineer
    pains:
    • Training and evaluating agents requires realistic tool environments and demonstrated software interactions

icp

  • text: Frontier foundation model developers investing in post-training and agent evaluation are the core target.
  • text: Enterprises building agents for specialized legal, finance or other professional work are adjacent buyers.

message pillars

  • text: Capture expertise as reasoning rather than just answers.
  • text: Translate real professional work into model training material.
  • text: Build environments for agents to practice and be evaluated on workflows.
  • text: Design datasets around the decisions experts make.

objections

  • objection: Can your data move a model on our specific benchmark?
    response: Propose a scoped evaluation with a held-out set and report baseline and post-training performance.
  • objection: Is the expert data relevant to our domain?
    response: Review sample tasks, expert qualifications and grading rubrics for the target workflow.
  • objection: Can sensitive enterprise material be used safely?
    response: Agree on data handling and privacy terms before sharing any proprietary documents.

competitors

  • name: Scale AI
    website: https://scale.com
    why: Supplies human-in-the-loop data and AI systems to model developers and enterprises.
  • name: Mercor
    website: https://mercor.com
    why: Connects expert human intelligence to AI evaluation and professional benchmarks.

keywords

  • expert AI training data
  • LLM post-training datasets
  • reinforcement learning grading rubrics
  • agent evaluation environments
  • computer use trajectories
  • legal AI benchmark
  • SFT reasoning data

voice

  • Research-led
  • Technical
  • Confident

signals

  • text: A lab is hiring post-training or reinforcement learning researchers and building an agent benchmark.
  • text: An enterprise is developing an agent for legal or financial analysis and needs domain-specific evaluation.

stack

  • MCP
  • API

hiring

  • Research Scientist - Post Training
  • Software Engineer - RL Environments
  • Head of Enterprise GTM

pricing

model: unknown

motion

sales_led

channels

  • Research content
  • LinkedIn
  • X

confidence

medium

Founders

  • name: Spencer Mateega
    title: Founder/CEO
    role: CEO
    bio: Building AfterQuery
  • name: Carlos Georgescu
    title: Founder/CTO
    role: CTO
    bio: Building AfterQuery. Previously interned at Citadel Securities (2x), Meta & Google as a software engineer. Past acquired ed-tech founder. Studied for a B.S. in Computer Science from the University of British Columbia.

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