AfterQuery

Applied research lab curating data solutions to accelerate foundation model development.

[AfterQuery @AfterQuery]

We're thrilled to announce our $30M Series A at a $300M valuation led by @altosvc, and that we’ve since surpassed $100M in annual revenue run rate.

[Spencer Mateega @spencermateega]

For most of history, expertise was scarce, constrained by time and reach: one person, one career, one lifetime.

Now, for the first time, we can encode, evaluate, and scale it.

We believe the wisdom that once took a lifetime to build shouldn’t take a lifetime to find.

Today, we’re excited to announce that @AfterQuery has raised a $30M Series A at a $300M valuation and that we’ve since surpassed $100M in annual revenue run rate, to build the data layer of professional AI.

[Spencer Mateega @spencermateega]

@AfterQuery will be at ICLR next week!

We’ll be at booth 404. Happy to chat about anything related to tool use/agents, RL environments, code gen, or evals. 

DM me if you wanna meet up!

[Alex Shaw @alexgshaw]

AfterQuery post-trained GPT-OSS-20B using Harbor + Tinker and saw a 14% bump on TB2 performance.

Love seeing people pick up Harbor for more than just evals.

[AfterQuery @AfterQuery]

https://t.co/iixZEj2zVy

[AfterQuery @AfterQuery]

https://t.co/UPgzGvQCp8

[Y Combinator @ycombinator]

YC and @GoogleDeepMind are hosting the Multimodal Frontier Hackathon this Saturday.

Most AI apps still don't utilize the full multimodal stack. So we’re giving you access to Gemini 3.1, Lyria, & NanoBanana 2 to see what you can build!

Sign up at: https://t.co/AyMfFHlSxi

[AfterQuery @AfterQuery]

Paper: https://t.co/kEJWijHevt

[AfterQuery @AfterQuery]

Introducing IDE-Bench!

A multi-language, full-stack benchmark evaluating LLMs acting as autonomous IDE agents

IDE-Bench assesses agents' ability to navigate, reason, and modify complex repositories using the same tools available in modern AI-native IDEs like Cursor

Models tested from @AnthropicAI, @OpenAI, @Alibaba_Qwen, @GoogleDeepMind, @xai, @deepseek_ai, @Meta, and @cohere

Check out the full results at https://t.co/MdqB7SL5JY!

[AfterQuery @AfterQuery]

RT @spencermateega: Congrats to @ValsAI team for launching Finance Agent Benchmark v1.1!

Proud that @AfterQuery could contribute finance e…

[AfterQuery @AfterQuery]

Our findings show that current models lack the ability to perform even the most basic tasks in high-impact, real-world domains like quantitative trading.

We hope Market-Bench can serve as a shared framework to evaluate models’ understanding of trading strategies and code generation for quantitative finance.

Excited to track how these capabilities evolve!

[AfterQuery @AfterQuery]

Introducing Market-Bench by @AfterQuery! The first-of-its-kind benchmark on LLMs for quantitative finance.

We challenged models to attempt a frequent introductory quantitative trading task: coding an executable backtester from a natural-language strategy description and market assumptions.

> 13 models build backtesting systems for directional, pair trading, and delta hedging strategies

> evaluated on reliability (executable passes) and accuracy (MAE) across 5 attempts per strategy

> real order book data with exchange delays and liquidity constraints

> @xAI’s Grok 4 achieved the overall lowest mean MAE (deviation from the golden backtest), followed closely by @OpenAI’s GPT 5.2

> @AnthropicAI's Sonnet 4.5 and @AlibabaGroup's Qwen 3 Max at perfect executability but high MAE

> Models from @Meta, @Amazon, @NVIDIA, and @Cohere continued to fail to produce executable backtesters

Leaderboard & full paper below!

[AfterQuery @AfterQuery]

Leaderboard: https://t.co/A9TdYvmyRJ
Paper: https://t.co/HxNLnfTOBD

[Spencer Mateega @spencermateega]

How far can vibe coding actually go?

Introducing App-Bench by @AfterQuery, a benchmark for end-to-end web app development.

We tested 6 production web apps on 10 coding agents from @OpenAI, @GoogleDeepMind, @AnthropicAI, @cursor_ai, @budapp, @v0, @boltdotnew, @Replit, and @Lovable.

One shot generation. Zero human edits. 4,530 evaluations.

[AfterQuery @AfterQuery]

@cigdemoztabak_ 👀

[shrawberry @shrawberryy]

Really excited to have contributed to this sick creative vision and brought the @AfterQuery website to life 😎😎

[AfterQuery @AfterQuery]

Today, humanity is shackled by scarcity of expertise. When expertise becomes infinitely scalable, humans will be freed to tackle problems we can't even conceive of today.

Introducing @AfterQuery. We’re building a world where expertise is abundant.

Domain by domain, profession by profession, AfterQuery is crafting datasets that encode excellence into forms that machines can learn.

Data is the final frontier.

[AfterQuery @AfterQuery]

@shrawberryy @sashabirukoff shrawberry 🙌

[Spencer Mateega @spencermateega]

The frontier begets the frontier.

I highly recommend reading @jaminball's latest Clouded Judgement article which spells out the AfterQuery thesis

(thread)

[AfterQuery @AfterQuery]

Excited for UI-Bench to be the leading benchmark for UI/web design!

Congrats to the @figma make team for claiming the #2 ranking

[Dylan Field @zoink]

while leaderboards are fun and motivating, this is just the start for figma make. can't wait to share all the improvements we are making over coming days / weeks / months!

[Spencer Mateega @spencermateega]

Introducing UI-Bench by @afterquery. The first and only rigorous eval of vibe coding tools.

> 4,000+ blinded pairwise judgments
> @budapp, @figma make, and @lovable take the lead
> @v0 and @replit ranked dead last
> performance gaps = differences in LLM orchestration, prompting, design templates, and post-processing
> link to our paper in the comments!