datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
production-ai-observability-20260909-dataset
Production AI Observability Monitor Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Production AI teams need trace-level signals for latency, token growth, tool failures, and low-quality outputs.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/production-ai-observability-20260909-dataset.production-ai-observability-20260830-dataset
Production AI Observability Monitor Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Production AI teams need trace-level signals for latency, token growth, tool failures, and low-quality outputs.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/production-ai-observability-20260830-dataset.production-ai-observability-20260919-dataset
Production AI Observability Monitor Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Production AI teams need trace-level signals for latency, token growth, tool failures, and low-quality outputs.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/production-ai-observability-20260919-dataset.production-ai-observability-20260731-dataset
Production AI Observability Monitor Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Production AI teams need trace-level signals for latency, token growth, tool failures, and low-quality outputs.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/production-ai-observability-20260731-dataset.production-ai-observability-20260820-dataset
Production AI Observability Monitor Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Production AI teams need trace-level signals for latency, token growth, tool failures, and low-quality outputs.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/production-ai-observability-20260820-dataset.ai-observability-events
AI Observability Events
AI Observability Events is a small synthetic reference dataset for AI observability, tracing and telemetry.
It contains structured example events representing execution across modern AI systems such as:
LLM calls
retrieval and reranking
AI agents
tool calls
retries and fallbacks
memory access
verification
validation
human approval
permissions
cost controls
inference performance
goal drift
privacy redaction
The dataset is published by the Observability… See the full description on the dataset page: https://huggingface.co/datasets/observability/ai-observability-events.production-ai-observability-20260810-dataset
Production AI Observability Monitor Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Production AI teams need trace-level signals for latency, token growth, tool failures, and low-quality outputs.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/production-ai-observability-20260810-dataset.