Fine-tuning is easier than ever. Evaluation isn’t. Are your models grounded? Reliable? Explainable under pressure?
KDCube ExpertFactor trains, evaluates, and benchmarks your AI models against real-world business tasks—with a progressive curriculum approach designed for scalable, explainable results.
We build tailored language models that embody your organization's unique expertise and knowledge base. We train specialized LLMs using your proprietary data, industry terminology, and internal knowledge resources. Unlike generic models that excel on academic benchmarks but fail on specialized tasks, your custom LLMs will speak your organization's language and understand your unique context—delivering more accurate, relevant, and trustworthy responses for your specific applications.
Transform your AI capabilities by fine-tuning LLMs through a comprehensive curriculum-based evaluation framework grounded in your organization's expert knowledge. Reveal both current model capabilities and future learning trajectories, while adapting seamlessly to your architecture—whether you're fine-tuning open-source models, deploying RAG pipelines, or training from scratch.
Build AI systems that integrate regulatory requirements directly into model architecture and behavior. Our framework embeds regulatory guidelines as native constraints within model parameters and decision boundaries. We provide auditable decision paths with documentation that maps directly to GDPR, HIPAA, FCRA, etc. Resulting models naturally operate within your compliance boundaries while delivering high-performance results—reducing risk, streamlining audits, and building stakeholder trust in your AI applications.
KDCube’s Expert Factory brings subject-matter expertise directly into the model development loop—boosting performance, reducing inference and retraining costs, and accelerating productivity. All within a controlled, auditable AI environment designed for enterprise-grade reliability.
Design a Curriculum of Tasks
Break down your use case into structured evaluation modules—like reasoning steps, compliance checks, or domain-specific problem solving.
Train and Align with Feedback
Plug your models into our evaluation engine, track performance at every skill level using AI or human evaluators, and pinpoint where fine-tuning is needed.
Benchmark and Iterate
Compare models across releases, architectures, or vendors—using task-focused metrics aligned to your KPIs.
|
Feature |
KDCube |
Static Benchmarks |
Manual Eval Loops |
|
Task-specific evaluation |
✅ |
❌ |
✅ (slow) |
|
Curriculum-based skill progression |
✅ |
❌ |
❌ |
|
Plug-and-play for any LLM or RAG |
✅ |
❌ |
⚠️ (custom only) |
|
Auditability & explainability |
✅ |
⚠️ |
❌ |
|
Scalable across teams & releases |
✅ |
❌ |
⚠️ |
Designed for AI teams, researchers, and regulated industries that need precise, explainable model evaluation at scale – aligned with compliance frameworks and business objectives.
Let us show you how curriculum-based evaluation brings clarity to model development. Request a demo today!
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