Overview: The Evaluation & Benchmarking Engine
ResultBench is the evaluation and benchmarking engine for Dataknobs.
It enables consistent, transparent, and measurable assessment of AI, data, and product results for various applications.
Mission: Develop a standardized benchmarking framework enabling teams to measure performance, evaluate settings, and build confidence in AI-powered choices.
ResultBench converts ABExperiment outcomes into metrics, leaderboards, and benchmarks—ensuring every model, prompt, or assistant is assessed transparently and fairly.
Core Capabilities
- Unified Evaluation Framework: Evaluate any AI system (model, assistant, workflow) using standardized metrics.
- Multi-Metric Scoring Engine: Compute dimensions like accuracy, coherence, cost, speed, factuality, and satisfaction.
- Custom Benchmark Definition: Define domain-specific benchmarks (e.g., finance, legal, tax, healthcare).
- Human + AI Hybrid Evaluation: Combine automated scoring with human judgments for holistic assessment.
- Result Normalization: Normalize scores across different models and datasets for fair comparison.
- Prompt & Response Comparison: Compare outputs from multiple prompts, models, or settings side-by-side.
- Quality Index Generation: Aggregate metrics into an overall “Quality Index” per variant.
- Bias & Hallucination Detection: Detect content bias, repetition, and factual hallucinations in outputs.
- Reference Dataset Integration: Upload datasets to evaluate consistency and domain alignment.
- Ground Truth Alignment: Evaluate AI responses against human-curated ground truths.
- LLM-as-a-Judge Framework: Leverage external LLMs to evaluate answers using rubrics (clarity, accuracy, tone).
- Cross-Experiment Leaderboards: Aggregate results from multiple ABExperiments to rank best-performing configurations.
- Visualization & Analytics: Graphical dashboards for performance trends, distribution plots, and metric deltas.
- Benchmark Versioning & History: Track changes in benchmarks, datasets, and scoring rules over time.
- Result Report Generator: Generate shareable PDF, CSV, or JSON reports summarizing evaluation outcomes.
Key Modules
1. Evaluation Engine
Integrated scoring system for text, data, and multimodal inputs. Enables accuracy and semantic metrics (BLEU, ROUGE, cosine similarity, etc.).
2. Benchmark Manager
Create, manage, and repurpose benchmark setups. Includes templates for finance, healthcare, legal, and conversational AI.
3. Scoring Dashboard
Dashboard for comparing outcomes, tracking trends, and ranking configurations. Allows manual overrides and adds annotation layers.
4. Quality & Bias Analyzer
Identifies bias, repetition, and hallucination issues. Offers bias mitigation tips and factuality summaries.
5. LLM-as-a-Judge System
Employs several LLMs to assess subjective factors (clarity, creativity, tone). Enables cross-model evaluation to spot scoring discrepancies.
Key Benefits
- Objective Measurement: Quantify results across all models, prompts, or assistants.
- Standardized Benchmarks: Ensure apples-to-apples comparison across experiments.
- Explainable Results: Transparent scoring with interpretable criteria.
- Continuous Tracking: Monitor performance trends over time and across updates.
- Cross-Product Integration: Works seamlessly with Knobs, KnobsScope, and ABExperiment.
- Enterprise Ready: Supports governance, lineage, and domain-specific benchmarks.