What is an AI model evaluation platform?

An AI model evaluation platform measures how well a model performs on tasks that matter to your business — accuracy, hallucination rate, latency, cost, regression against past versions — and produces audit-grade reports. VDF Data Suite does this for any open or proprietary LLM, runs entirely on-premise, and ties every evaluation to the dataset, model version, and prompt template used. That makes it the AI model evaluation platform regulated industries can actually defend to an auditor.

How does dataset generation work?

VDF Data Suite ingests structured and unstructured data from your databases, APIs, documents, and knowledge bases, then synthesises fine-tuning datasets — instruction pairs, preference data, classification labels, RAG ground-truth — using configurable templates and quality filters. Every generated row is traceable back to the source record, so PII rules, retention policies, and lineage requirements stay intact through training.

Can fine-tuning run on-premise?

Yes. Fine-tuning, parameter-efficient tuning (LoRA / QLoRA), and full SFT all run on your hardware — your GPUs, your network, your storage. No training data, gradients, or model weights leave your perimeter. The platform supports common open-weight families (Llama, Mistral, Qwen, Gemma, Phi) and any custom architecture you can run locally.

What audit trails are provided?

Every dataset preparation step, fine-tuning run, and evaluation run produces immutable logs that capture inputs, configuration, model version, compute resources, and outputs. Reports are exportable as PDF and CSV, and the platform can emit events to your existing SIEM. The audit trail is designed to satisfy EU AI Act high-risk system documentation, financial model risk management frameworks, and sector-specific validation requirements.

AI Model Evaluation, Fine-Tuning, and Dataset Generation Platform

VDF Data Suite generates fine-tuning datasets from your databases, APIs, documents, and knowledge bases, then runs on-premise model fine-tuning and accuracy testing with full audit traceability.
The AI model evaluation and fine-tuning platform for regulated enterprises — text, image, and structured data pipelines with zero cloud data exposure.

Deployment:

On-premises, no cloud data exposure

Data Sources:

Databases, APIs, documents, knowledge bases

Outputs:

Fine-tuning datasets, evaluations, audit-ready logs

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PLATFORM VIEW

VDF Data Suite fine-tuning and evaluation workspace

CAPABILITIES

Data Operations for Fine-Tuning and Model Evaluation

Prepare Fine-Tuning Data from Any Source

Ingest and normalize training data from databases, APIs, documents, and knowledge bases with transformation and quality controls built in.

On-Prem Fine-Tuning Pipeline

Run the complete model fine-tuning pipeline on-premises so sensitive data never has to leave your environment or pass through public cloud tooling.

Model Accuracy Testing

Evaluate LLMs with automated benchmarks and manual review workflows, all without cloud dependency and with consistent test datasets.

Multi-Modal Data Pipelines

Support text, image, and structured data pipelines so teams can prepare and evaluate multimodal datasets in one controlled environment.

Audit-Ready Output

Every evaluation run is logged with prompts, datasets, model versions, reviewer decisions, and results for full traceability and compliance review.

Governed Data Preparation

Track lineage from raw source to final training and evaluation set so teams can reproduce runs and understand exactly what data shaped each model outcome.

WORKFLOW

From Raw Sources to Trusted Evaluation

1. Ingest

Collect raw data from databases, APIs, documents, and knowledge bases into a controlled preparation workspace.

2. Prepare

Clean, label, and structure text, image, and structured data into multimodal datasets for fine-tuning and evaluation.

3. Fine-Tune & Test

Run on-premises fine-tuning plus automated and manual accuracy testing with no cloud dependency in the loop.

4. Audit

Export audit-ready outputs with complete traceability across datasets, runs, reviewers, and model versions.

USE CASES

Where Teams Use Data Suite

Training Data Operations

Prepare fine-tuning corpora from internal systems, APIs, document repositories, and knowledge bases without custom one-off scripts.

On-Prem Model Programs

Support regulated teams that need model fine-tuning, evaluation, and reporting entirely inside their own infrastructure.

Evaluation & QA

Run automated benchmarks alongside manual review to measure model accuracy before promoting a model into production use.

Audit & Compliance

Give security, legal, and governance teams full traceability for every evaluation run, dataset revision, and reviewer decision.

Ready to prepare, fine-tune, and evaluate models on-prem?

Bring together fine-tuning data preparation, multimodal pipelines, model accuracy testing, and audit-ready traceability in one controlled environment. Start your free trial or schedule a personalized demo to see how Data Suite fits your model development workflow.