Use cases
Inventory
Find every tool, owner, seat, and cost.
Savings
Catch waste, overlap, and renewals early.
Access
Onboard and offboard across your stack.
Context
Map how people, tools, spend, and agents connect.
For
Founders
Protect runway by seeing every tool and cost.
Engineering
Control AI usage, access, and provider spend.
Finance
Reconcile software spend and find waste.
Operations
Keep inventory, access, and renewals current.
Resources & company
Resources
Guides and practical software insights.
Manifesto
Why software operations need a new model.
Press
Company news and media resources.
Partners
Build and grow with ELI.
IntegrationsStacksTools
Talk to a humanDiscover my stack
IntegrationsStacksTools
Discover my stackTalk to a human

Company

  • Home
  • Manifesto
  • Talk to us
  • Partners

Help

  • Terms of service
  • Privacy policy
  • Docs

Product

  • Inventory
  • Savings
  • Access
  • Context

For teams

  • Founders
  • Engineering
  • Finance
  • Operations

Explore

  • Integrations
  • Tools
  • Stacks
  • Startup credits
  • Articles

Socials

  • LinkedIn
  • Instagram
  • TikTok
  • YouTube
Enterprise Layer Intelligence
Categories/AI Orchestration & MLOps/AfterQuery
AfterQuery

AfterQuery

Founded 2024

Generate expert reasoning datasets and evaluation environments for foundation AI models

Pricing model

Demo

Rating

★ Mixed Reviews

Time to value

Requires Expertise

You can use AfterQuery to build high-quality training datasets that teach artificial intelligence models how human experts think and solve complex problems. It captures expert chain-of-thought reasoning traces, decision tradeoffs, and workflows across various technical domains. The service provides supervised fine-tuning data, reinforcement learning reward rubrics, custom API and Model Context Protocol agent environments, and computer use interaction trajectories. Teams can use these specialized datasets to train autonomous agents, improve code generation, and benchmark model capabilities against realistic professional tasks.

What AfterQuery does

Generate chain-of-thought training data from human expertsBuild custom tool-calling environments using APIs and MCPRecord desktop and browser user interaction trajectoriesCreate rubric-based evaluation frameworks for model outputsBenchmark foundation models against domain-specific test setsFine-tune language models for complex multi-step reasoningSupervised Fine-Tuning datasets with chain-of-thought reasoning tracesReinforcement learning rubrics converting subjective evaluations into reward signalsCustom API and Model Context Protocol agent testing environmentsComputer use trajectory recording across browser and desktop appsExpert-designed prompts tailored for code generation and complex workflowsDomain-specific failure mode analysis for frontier models

Pricing breakdown

Pricing model: Book a demo

Tutorials & Demos

Frequently asked

Custom API Endpoints, Python SDK, JSON/CSV Export, Cloud Storage (S3/GCS), Unverified, Model Context Protocol (MCP), S3/GCS Cloud Storage, Terminal-Bench Environments, Amazon S3, Google Cloud Storage

Want a tailored answer?

See whether AfterQuery fits your stack.

Techbible weighs AfterQuery against what you already pay for, your team shape, and the work that's actually happening. Free to start.

Side by side

Compare AfterQuery

Search the catalog or pick a similar tool to compare pricing, features, and fit.

Or pick from similar tools

More in AI Orchestration & MLOps

All tools →
CrewAI

CrewAI

Build and run autonomous multi-agent workflows using visual canvases or Python code

Arize AI

Arize AI

Monitor, trace, and evaluate large language model applications

PySpur

PySpur

Build, test, and deploy AI agent workflows using code or visual drag-and-drop interfaces

AgentOps

AgentOps

Track, debug, and monitor AI agents and large language model interactions

Composio

Composio

Connect AI models and agents to external apps and developer tools

Buster

Buster

Build internal agents and automate complex company workflows

LaunchLemonade

LaunchLemonade

Build and run custom AI assistants grounded in your business documents without code

LlamaIndex

LlamaIndex

Parse complex documents and tables into clean data for language models

AfterQuery, AI training data, expert data, reinforcement learning, supervised fine-tuning, SFT, RLHF, model evaluation, agent environments, computer use trajectories, chain of thought, frontier models, Model Context Protocol, rubrics, reasoning datasets