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MVP Investment

$19K - $27K
4-6 months
Engineering
$18,000
Cloud Hosting
$600
SaaS Stack
$300
Domain & Legal
$100

6mo ROI

2-4x

3yr ROI

10-20x

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Talent Scout

K

Kunhang Lv

SKLCS and Key Laboratory of System Software, ISCAS, Beijing, China

Y

Yuhang Dong

Laboratory of Parallel Software and Computational Science, ISCAS, Beijing, China

R

Rui Han

SKLCS and Key Laboratory of System Software, ISCAS, Beijing, China

F

Fuqi Jia

SKLCS and Key Laboratory of System Software, ISCAS, Beijing, China

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Founder's Pitch

"AquaForte turbocharges SMT solvers by using AI to understand math problems better, solving 80% more cases than Z3. It's like giving your math solver superpowers."

AI-Powered SMT SolvingScore: 8.7View PDF ↗

Commercial Viability Breakdown

Breakdown pending for this paper.

Sources used for this analysis

arXiv Paper

Full-text PDF analysis of the research paper

GitHub Repository

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Why It Matters

Current solvers are like trying to solve a puzzle blindfolded. They miss easy solutions because they can't see the math behind the symbols.

Product Angle

'AI glasses for math solvers.'

Disruption

Traditional solvers are slow because they can't 'see' the math. AquaForte changes the game by making them smarter.

Product Opportunity

SMT solvers are used in software verification and model checking. AquaForte can make these processes faster and more reliable, saving companies time and money.

Use Case Idea

Imagine a math teacher that helps your computer solve homework faster. It finds the right answers by understanding the problem deeply.

Science

AquaForte uses AI to 'see' the math behind the symbols, like giving solvers glasses. It understands math patterns and suggests smart solutions.

Method & Eval

Tested on 1,481 benchmarks, AquaForte improved solver performance by 80% for Z3 and 183.6% for CVC5.

Caveats

The AI is great at finding solutions but struggles with proving something can't be solved.

Author Intelligence

Kunhang Lv

SKLCS and Key Laboratory of System Software, ISCAS, Beijing, China
lvkh@ios.ac.cn

Yuhang Dong

Laboratory of Parallel Software and Computational Science, ISCAS, Beijing, China

Rui Han

SKLCS and Key Laboratory of System Software, ISCAS, Beijing, China

Fuqi Jia

SKLCS and Key Laboratory of System Software, ISCAS, Beijing, China

Feifei Ma

Laboratory of Parallel Software and Computational Science, ISCAS, Beijing, China
maff@ios.ac.cn

Jian Zhang

SKLCS and Key Laboratory of System Software, ISCAS, Beijing, China
zj@ios.ac.cn