FAQ
Frequently Asked Questions (FAQ)
Exhaustive answers to real engineering, research, security, performance, and architecture questions about NeuronScope.
- AI Observability
How does NeuronScope observe an AI application without modifying code?
NeuronScope attaches non-invasive context managers and framework hooks (vians.Scope) to model forward passes, API requests, vector retrieval calls, and agent steps. When the context exits, all hooks are safely cleaned up with zero permanent modifications to model logic. - AI Observability
What is the overhead of recording telemetry during production inference?
NeuronScope uses zero-copy asynchronous streaming into lock-free ring buffers. Under production monitoring profiles, latency overhead is typically under 1.5% to 3.0%, with zero impact on main thread computation loops. - AI Evaluation
How are hallucination scores and quality metrics calculated?
The Evaluation Engine compares generated completion tokens against retrieved RAG context documents, ground truth benchmarks, and semantic consistency metrics. Standard evaluators includeHallucinationScore,RetrievalRelevance,ToxicityGuard, andFactualAccuracy. - AI Profiling
Can NeuronScope profile token throughput and GPU VRAM usage?
Yes. The Profiling Engine monitors GPU memory allocation (CUDA, Apple Metal, ROCm), token generation rates (tokens/sec), first-token latency (TTFT), and per-step wall-clock execution breakdown. - Fingerprinting
Does changing Python version or OS alter a fingerprint?
No. Fingerprints are canonical 32-byte BLAKE3 digests over normalized model parameter order, prompt text, and dataset schemas. Moving between Linux, macOS, or Windows yields identical fingerprints. - Fingerprinting
Does fingerprinting support Vector Databases and RAG Indexes?
Yes.fp:datasetcomputes canonical digests over vector database schemas, embedding dimensions, distance metrics (Cosine/Euclidean), and document ID ordering across Pinecone, Qdrant, Chroma, and Milvus. - Governance & Security
How does NeuronScope enforce prompt injection defense and security guardrails?
The Governance Engine inspects incoming user variable bindings against security policy rules prior to model invocation, blocking prompt injection patterns, role overrides, and unauthorized PII leakage. - Governance & Security
Is RBAC and compliance audit logging supported for enterprises?
Yes. Role-Based Access Control (RBAC), encrypted payload storage, and immutable audit logs are built directly into the Storage & Governance layer for SOC2 and ISO compliance verification. - Storage
What is the .nsz file format and can it stream from cloud buckets?
The.nszformat is a versioned, columnar telemetry container. It supports O(1) range queries, allowing remote readers to stream specific layer activations or execution steps directly from S3, GCS, or Azure Blob storage without downloading whole artifacts. - Architecture
What are the 8 layers of the NeuronScope platform architecture?
The 8 layers are: 1. Dashboard, 2. Surface (REST API • SDK • CLI), 3. Platform Core, 4. Execution Engine (Workflow/Scheduler/Agents), 5. Intelligence Layer (Explainability/Evaluation), 6. Observability Layer, 7. Governance & Storage Layer, 8. Infrastructure & Cloud Adapters.