Lantern

Lantern is an LLM observability and security tool for African companies deploying AI, providing real-time monitoring, guardrails, and cost controls for production LLM applications.

Key capabilities include:

• Request and cost monitoring: Logs every LLM call with inputs, outputs, latency, token usage, and cost, plus hourly and daily analytics and per-app and per-model cost breakdowns.
• Guardrails for threats and data leaks: Detects prompt injection attempts, performs PII redaction before prompts reach the model, and filters toxic outputs before responses reach end users. Guardrails support hard-block or soft-log modes.
• Africa-focused PII detection: Identifies and redacts PII formats commonly used in Kenya, Nigeria, and South Africa, including phone numbers, M-Pesa codes, and national IDs.
• Budgets, alerts, and auditability: Supports daily budget limits, automatic request pausing, cost-spike alerts (for example, usage exceeding a baseline), custom tags, and a searchable events log with export for audits.

Available via a web dashboard with Python SDK integration (shown wrapping an existing Anthropic client); it is designed to work with no proxy server and no infrastructure changes.

Lantern targets B2B AI teams in Africa that build or operate LLM-powered products and need visibility into model usage, security controls, and predictable API spend.

Notable in the African market context, it is positioned as built for African companies and includes region-specific PII detection for KE, NG, and ZA formats, alongside monitoring and compliance-friendly logging for LLM applications.