What is AfterQuery?
AfterQuery isn’t just another data company—it’s a research lab rethinking how AI learns. While most models are trained on vast amounts of generic internet text, AfterQuery focuses on something far more valuable: how experts actually think. Real-world work isn’t about giving answers—it’s about making decisions, weighing tradeoffs, and understanding context. That kind of knowledge rarely shows up in public datasets. AfterQuery partners with professionals across industries to capture their reasoning step-by-step and turn it into high-quality training data that helps foundation models truly understand complex tasks.
Backed by top AI angels and operating at a $100M+ revenue run rate, AfterQuery is already powering frontier AI labs and enterprises. Their approach moves beyond simple prompt-response pairs to include reasoning traces, human-demonstrated workflows, and expert-designed evaluation rubrics—so models don’t just sound smart, they act smart in real professional settings.
What are the features of AfterQuery?
- Supervised Fine-Tuning (SFT) Data: High-quality prompt–response pairs paired with chain-of-thought reasoning to teach models how experts break down complex problems.
- Reinforcement Learning + Rubrics: Expert-built prompts with clear grading frameworks that convert subjective judgment into scalable reward signals for code and reasoning tasks.
- Agent Environments (API / MCP): Custom sandboxed environments using real APIs, tools, and services so AI agents can be trained and tested in realistic workflows.
- Computer Use Trajectories: Recordings of actual human interactions across browsers and desktop apps, showing models how to navigate and operate software end-to-end like a pro.
What are the use cases of AfterQuery?
- Training legal AI assistants that weigh case law nuances and client risk—not just cite statutes.
- Building finance agents that understand market tradeoffs and regulatory constraints when generating investment memos.
- Developing engineering co-pilots that debug code by replicating how senior developers diagnose issues step by step.
- Creating medical reasoning models that reflect clinician decision trees, not just textbook answers.
- Powering enterprise support bots that handle tier-3 troubleshooting by mimicking veteran engineers’ workflows.
How to use AfterQuery?
- Start by identifying a high-value domain where expert judgment matters (e.g., compliance, R&D, or customer escalation).
- Partner with AfterQuery to observe and record how your top performers solve real tasks—from initial analysis to final decision.
- Use their structured datasets for SFT or reinforcement learning to fine-tune your foundation model.
- Test agent performance in AfterQuery’s custom environments before deploying to production.
- Continuously refine using expert feedback loops built into their rubric system.
