K-Judge
Korean-specialized AI evaluation model comprising Kgrammar for Korean grammar error checking and Keval for qualitative answer evaluation of generative AI outputs, released as open source.
What it does
Korean-specialized AI evaluation model comprising Kgrammar for Korean grammar error checking and Keval for qualitative answer evaluation of generative AI outputs, released as open source.
- AI-based stock investment information
- news analysis
- AI performance evaluation
- nuclear power plant operations data management
- Category
- AI evaluation and observability
- Users
- financial institutions, enterprise companies, individual stock investors
- Public API
- Not offered
Not yet disclosed: deployment options, platforms, languages and support channels.
Pricing
Pricing isn't published
2Digit Co., Ltd. doesn't list prices publicly. Ask them for a quote.
Security and compliance
As reported by 2Digit Co., Ltd.. Ask for audit reports before you buy.
- encryption-at-rest
- encryption-in-transit
- access-controls
- intrusion-detection-system
- access-log-monitoring
- security-program-installation
- physical-access-controls
- employee-security-training
Reviews
No reviews yet
Reviews come from people who use K-Judge at work. Share how your team uses it to help other buyers decide.
Alternatives
Tokenshire
by Olam Labs
Simulated town of AI agents running autonomously for long horizons, socializing and managing government, economy, and resources under constraints.
DataCenterBench
by Robocurve
Evaluating robots on data-center construction tasks, including racking servers, routing cable, and the physical work behind the compute supply chain.
LLM evaluation
by Openlayer
Rigorous evaluation for GenAI and LLMs—test every prompt, trace every response, and validate every output.
Self Diagnostics
by Raindrop
Capability for agents to proactively report their own failures via SDK instrumentation.
Evaluates and improves AI on meaningful use cases via production-grade RL environments, accelerating custom evals and post-training data creation.
Loss Analyses
by AfterQuery
Identifies where and why models fail in professional contexts through systematic study, pinpointing the precise failure modes and distributional gaps that inform dataset and env...
Is this your product?
Claim it to keep details accurate and submit evidence for the next ranking review.
Claim K-Judge