ACM Distinguished Paper of the Year 2025

The Data Engine for Code Intelligence

Our agentic transpiler translates code between languages at 73.9% accuracy, outperforming GPT, Claude, Gemini, and Qwen. The resulting code data trains better AI models at scale.

73.9%
Functional Correctness
12.4×
More Tests per Contract
94.2%
Compilation Rate
6
Models Benchmarked
The Problem

AI Code Translation Is Broken

Current models generate code that looks right but doesn't work. Enterprise can't ship AI-translated code into production. The entire pipeline, from translation to verification, needs to be rethought.

78%
of AI-translated code fails to compile

Models produce syntactically plausible but fundamentally broken translations requiring extensive manual repair.

$4.2M
avg. enterprise migration cost

Manual code translation is slow, expensive, and error-prone. Most migrations run 2–3× over budget.

18 mo
average migration timeline

Enterprise migrations take months or years with current tooling, creating significant delays and cost overruns.

Benchmarks

Shinso Beats GPT, Claude, Gemini & Qwen

Validated on smart contract translation, among the most demanding code domains, where a single error can be catastrophic. Our peer-reviewed research chose the hardest possible domain to validate that the architecture generalizes to any language and complexity level.

Overall Performance

Average score across all translation benchmarks

100 80 60 40 20 0
73.9
Shinso
45.6
Claude 4.5
33.7
Gemini 3 Pro
28.6
Gemini 2.5
21.9
Qwen3 Coder
21.3
GPT-5.2 Pro
Shinso
94.2%
Compile
73.9%
Functional
71.3%
Test Pass
Evaluated Languages
PythonTypeScriptRustGoC++JavaSolidityMove
Data Engine

Powering the Next Generation of Code AI

Frontier models are bottlenecked by data quality. Shinso's transpiler doesn't just translate code. It generates verified, production-grade parallel corpora at scale. The same engine that outperforms every model becomes the data factory that trains better ones.

The Data Flywheel

Better data → better models → better translations → more data. Shinso creates a compounding advantage that no foundation model lab can replicate internally.

10M+
Verified Code Pairs
Parallel translations across 15+ language pairs. Each pair verified by compilation and test suites.
94.2%
Compilation Verified
All generated pairs compile. No garbage data. No hallucinated syntax. Clean signal only.
8
Target Languages
Python, TypeScript, Rust, Go, C++, Java, Solidity, and Move, with more on the roadmap.

Why This Matters

For AI Labs

Train better code models with verified, high-signal parallel data, not noisy web scrapes.

For Enterprise

Migrate codebases with the only AI that produces output you can actually ship to production.

For Researchers

Access the largest verified code translation dataset ever created. Built for advancing code intelligence.

Scale for code. Scale AI built the data infrastructure that powered the LLM revolution. Shinso is doing the same for code. Our transpiler generates verified training data that major labs need but can't produce internally.

Technology

The Shinso Transpiler

An agentic system that translates, verifies, and self-corrects code across languages. The output compiles, runs, and passes tests.

Multi-Language Support

Translate between Python, TypeScript, Rust, Go, C++, Java, Solidity, and Move with high accuracy across 15+ language pairs.

Agentic Self-Healing Pipeline

Multi-pass verification with automated error correction. The system iterates until output compiles and passes generated test suites.

3 Years of Curated Training Data

Proprietary training corpus built from 3 years of research at University of Houston. Designed specifically for code translation, not general-purpose web scrapes.

Automated Test Generation

Translations ship with generated test suites that verify functional equivalence automatically. No manual QA.

Translation Pipeline
1
Source Code
2
AST Parse
3
Semantic Map
4
Generate
5
Self-Heal
6
Test
7
Output
Architecture

Roadmap to 99% Accuracy

3 years of R&D. A multi-stage pipeline combining specialized models, formal verification, and reinforcement learning, where each layer compounds the accuracy of the last.

Multi-Agent Pipeline

Specialized agents work in sequence, each handling a different dimension of code translation.

1
Security Analysis
Detect vulnerabilities and anti-patterns
2
Repair Planning
Architect the optimal translation strategy
3
Code Generation
Produce target-language output
4
Iterative Refinement
Self-correct until compilation succeeds

Formal Verification

Translations are verified through multiple independent signals, not surface-level pattern matching.

1
AST & Type Analysis
Deep structural parsing of source code
2
Intermediate Representation
Language-agnostic typed IR preserves semantics
3
Compiler Feedback Loops
Real compiler and prover signals guide generation
4
Agentic Repair Pass
Fix anti-patterns and preserve semantic equivalence

Accuracy Roadmap

6 months to production. Each milestone builds on the last.

M1 – M2 75%

Baseline translator + compile loop integration

M3 – M4 85%

Agentic repair + formal prover integration

M5 – M6 90–99%

RL with compiler signals + model tuning + test harness

Why this can't be replicated. Shinso's architecture isn't a prompt wrapper. It's a vertically integrated system of specialized models, proprietary training data, and formal verification built over 3 years. Each layer reinforces the next. Replicating this requires rebuilding the entire stack.

Team

Leadership

Multi-exited founders backed by 3 years of dedicated AI research at the University of Houston.

SB

Sam Beni

CEO

Pioneer of "Complex AI." Accelerated 49 unicorns.

Tech NationIntel AIImperial
EV

Elod Varga

CTO

Built, launched, and exited 2× successful tech protocols.

TaraxaEWOR
RK

Dr. Rabimba Karanjai

CSO / CAIO

World-renowned AI language translation researcher.

U of HoustonGooglePayPal
Recognition

Peer-Reviewed & Award-Winning

ACM Distinguished Paper

Distinguished Paper of the Year 2025, awarded by ACM for demonstrating breakthrough results on the most rigorous code translation benchmarks.

University of Houston

3 years of dedicated AI research partnership advancing code translation research.

Backed by Leading Investors

Backed by investors with deep expertise in AI infrastructure and developer tools.

The Data Layer for Code AI

Whether you're training frontier models or migrating enterprise codebases, Shinso delivers the verified code data and translations you need.