LakeQuest: A Three-Domain Benchmark for Grounded Question Answering across Data
While modern question answering (QA) systems excel on clean, schema-aligned corpora, real-world knowledge is rarely so neatly packaged. Answering questions over enterprise and scientific data lakes requires systems to navigate heterogeneous
https://arxiv.org/abs/2607.12310v1 ↗Thesis fit
Good fit
Within your typical scope; diligence still required.
In your usual scope
Idea match
Light
How close the company’s idea is to your thesis statement
Sector
ai
Overlap with sectors you care about
Geography
Unknown
Location unknown — scores 0
Your thesis: “We back exceptional technical founders building AI-first products and infrastructure, deploying $100K checks within 24 hours.”
Founder → stable
Traction → stable
Idea vs market ↑ improving
▸ Add / edit details
Correct facts used on the next screening or memo.
People
M
Michael Solodko
1.0
low confidence
S
Steven Gong
1.0
low confidence
G
Guangwei Yu
1.0
low confidence
S
Satya Krishna Gorti
1.0
low confidence
J
Jesse C. Cresswell
1.0
low confidence
V
Victor Zhong
1.0
low confidence
Activity & evidence
Similar baseline plays (YC · idea space)
Tiago Passinato
Plasticity
· Acquired
Natural language processing APIs for developers.
Ajay Patel
Alex Sands
Giuseppe Ancona
Simone Di Somma