Pangea is a security platform for AI applications, with guardrails for prompts, outputs, data access, and logging. Secure LLM workflows via APIs, SDKs, AI tools, or API gateways.

Pangea

Overview

Pangea is a security platform for AI applications. Its site describes security guardrails that help organizations ship generative AI and LLM apps with protections for prompts, outputs, data access, logging, and related security workflows.

The documentation centers on composable services rather than a single monolithic product. Examples include Prompt Guard and AI Guard for content handling, Redact for sensitive data treatment, AuthN and AuthZ for identity and permissions, Secure Audit Log for tamper-resistant logging, and Vault for secret and key operations.

Features

Composable security services

Services mentioned across the docs include Prompt Guard, AI Guard, Redact, Threat Intel, Secure Audit Log, AuthN, AuthZ, and Vault. The site positions them as composable security services for AI applications and related access-control workflows.

Prompt and response guardrails

The AI security docs describe filtering and transforming user inputs and context data, then sanitizing outputs to reduce prompt manipulation and harmful content exposure at inference time.

Identity and access control

Documentation covers authentication and authorization for enterprise AI apps, including policies based on roles, groups, relationships, attributes, and source permissions.

Logging and auditability

The tutorials describe logging prompts, responses, and system events, including LLM details, to support attribution and accountability.

Multiple integration paths

The integration page states that Pangea can be integrated directly with APIs and SDKs, or through AI tools and API gateways. SDKs are listed for Python, JavaScript, Go, Java, and C#.

Service-level billing structure

The pricing page lists service-level billing categories for AI Guard, Prompt Guard, Secure Audit Log, Redact, Embargo, File Intel, IP Intel, Domain Intel, URL Intel, AuthN, Vault, User Intel, File Scan, Secure Share, AuthZ, and Sanitize.

Use Cases

  • Secure an LLM chat or assistant

    Add controls around user prompts and model outputs to reduce exposure to prompt injection, insecure output handling, and accidental disclosure of sensitive information.

  • Control access to enterprise context

    Protect enterprise AI applications that use internal documents or RAG workflows by enforcing authentication, authorization, and permission checks before data is surfaced to the model.

  • Monitor AI activity and investigations

    Log prompts, responses, and system events so teams can trace outcomes, review model interactions, and keep an audit trail for AI activity.

  • Embed guardrails in an application stack

    Use direct APIs, SDKs, or AI tool integrations when you want application-level controls with low-latency integration in a specific language or framework.

  • Apply controls at the gateway layer

    Route traffic through an API gateway when you want centralized policy enforcement across multiple systems or applications rather than per-app controls.

Pros and Cons

Pros

  • Covers multiple AI security needs in one platform, including prompt handling, access control, logging, and data protection.
  • Supports several integration approaches, including direct APIs, SDKs, AI tools, and API gateways.
  • Provides SDKs for Python, JavaScript, Go, Java, and C#, which can reduce implementation effort for common stacks.
  • Documentation ties the services to concrete LLM security workflows such as prompt injection defense, output sanitization, and enterprise data access control.

Cons

  • The published pricing page text does not show actual prices or plan limits.
  • Some documentation and service descriptions are partial in the provided source set, so a few capabilities are only described at a high level.

FAQ

What is Pangea used for?

Pangea provides security guardrails for AI applications and documentation for securing LLM apps with services such as Prompt Guard, AI Guard, Redact, Threat Intel, Secure Audit Log, AuthN, and AuthZ.

How can Pangea be integrated into an application?

The integration options page says Pangea can be used in-app through APIs, SDKs, or AI tools such as LangChain integrations, or placed behind an API gateway.

What parts of an AI application does Pangea help secure?

The AI security tutorial describes securing user prompts, model inputs and outputs, access to enterprise data, and logging or monitoring for prompts, responses, and system events.

Does the site show pricing details?

The pricing page shows service-based billing details, but the rendered page text does not expose specific prices or plan limits.

Quick Facts

Category
AI security platform
Primary use
Security guardrails for AI applications and LLM workflows
Integration options
APIs, SDKs, AI tools, and API gateways
SDK languages
Python, JavaScript, Go, Java, C#
Pricing evidence
Service-based billing is documented, but no public prices are shown in the rendered text
Domain
pangea.cloud