
Core Mobile & AI Observability
AI Observability for Regulated Environments
In regulated industries, visibility into AI and machine learning systems is essential, not just for operational oversight, but for building trust, meeting compliance obligations, and ensuring secure, auditable outcomes.
Core Mobile’s PCSIP™ platform integrates observability as a core capability, offering full traceability of AI and large language model (LLM) operations. Whether powering ambient dictation, decision support, or intelligent automation, PCSIP provides real-time insight into every AI-generated action, enabling organizations to monitor, audit, and validate their AI pipelines with confidence.
Seamless Integration with Leading Observability Frameworks
PCSIP supports a range of open and enterprise observability solutions, giving organizations the flexibility to build within their existing infrastructure while maintaining data security and governance:
OpenTelemetry (OTel): A vendor-neutral, open-source observability framework that can be fully self-hosted. OTel’s Generative AI Semantic Conventions (GAI semconv) enable detailed tracing of LLM usage, including inputs, outputs, latency, cost, and token consumption. Integrates with enterprise tools like Splunk, Grafana, and Datadog—no external SaaS dependency required.
LangSmith: A LangChain-native solution offering deep insight into AI toolchains, including token-level traces and prompt-response evaluation. LangSmith can be deployed within a private cloud or on-premises environment, with built-in PII redaction and audit-friendly version tracking.
Weights & Biases (W&B Weave): For teams using W&B for model development and lifecycle management, PCSIP adds observability for LLM and generative AI pipelines. HIPAA-compliant cloud deployments include audit logging, secure BAAs, and optional export to OpenTelemetry-compatible systems.