Prism by Block Convey - 2026 Pricing, Features, Reviews & Alternatives

Prism by Block Convey is an AI observability and governance platform built for teams deploying LLM-powered applications and AI agents in regulated production environments. It captures every LLM call, tool invocation, retrieval step, and agent handoff into structured traces and conversation sessions, then scores each trace automatically on arrival using both deterministic methods and LLM-as-Judge evaluation, at no credit cost. Guardrails cover 30+ built-in detectors spanning PII, PHI, prompt injection, toxicity, secrets, SQL injection, code safety, and content moderation, operating in either Monitor or Enforce mode with real-time redaction at ingestion. Deployment options include cloud-hosted SaaS and self-hosted VPC for data-residency-sensitive workloads at the Enterprise tier.

The platform targets compliance officers, Chief Risk Officers, CISOs, and AI engineers in financial services (fintech, banking, credit scoring, AML/KYC, fraud detection, neobanking, wealth management), healthcare payers, insurance carriers, and any organization subject to regulatory AI oversight. Prism by Block Convey pre-maps evidence to 12 regulatory frameworks, including NIST AI RMF, ISO 42001, EU AI Act, SOX, DORA, PCI DSS, HIPAA, ECOA, SR 11-7, NY DFS Part 500, and NAIC Model Bulletin, and exports immutable, signed, timestamped audit evidence packs in under sixty seconds. Regulatory classification automatically detects industry context within conversations and applies domain-specific checks, such as rate-promise flags for financial conversations, PHI exposure detection for healthcare, and privilege-risk detection for legal contexts.

Additional capabilities include an Agent Intelligence module that summarizes production traffic in prose and surfaces recurring failure themes, Root Cause analysis that clusters failing traces into patterns and links each back to the responsible prompt or code, and AI-powered remediation recommendations generated from those clusters. An adversarial red-teaming catalog with severity-tagged findings and reproducer prompts supports pre-production vulnerability identification. The Model Inventory auto-populates from trace metadata, eliminating manual registration. Integrations span a Python SDK with support for LangChain, LangGraph, Google ADK, LiteLLM, and OpenAI Agents SDK; a zero-code proxy for Anthropic, OpenAI, and Gemini; OpenTelemetry; HTTP endpoints; and native connectors for Databricks, Snowflake, Azure AI Foundry, and AWS Bedrock. A free tier provides full core observability on live production traffic before any payment is required.