Enterprise AI Safety at Scale
General Analysis provides the infrastructure you need to ship safe, reliable AI features. Our platform combines real-time guardrails, automated red teaming, and agent-level protection so security teams and developers can move fast without compromising safety posture.
Whether you are building customer-facing chatbots, internal copilots, or autonomous agent workflows, General Analysis gives you the tools to detect harmful content, prevent prompt injection, and stress-test your models against adversarial attacks — all through a unified Python SDK and managed API.
Book an AI security demo with us to access our platform. Or email General Analysis and we’ll help you get started.
Platform overviewPlatform overview
General Analysis is built around three complementary products that form a layered defense for AI applications. Each product can be adopted independently or combined for full-stack protection. For a conceptual introduction to each product area, see our guides on what AI guardrails are and what automated AI red teaming is .
Why General AnalysisWhy General Analysis
Organizations deploying large language models face a growing surface of risks — from jailbreak attacks and data exfiltration to hallucinated medical or legal advice. Off-the-shelf content filters catch only the most obvious violations and degrade under adversarial pressure.
General Analysis tackles these challenges with a research-first approach. To understand how these capabilities compare with alternatives, read our guide on the best AI guardrails in 2026 .
- Adversarial hardening: Every guardrail model is trained against outputs from our own red teaming pipeline, not just curated datasets, so defenses hold up against novel attack patterns.
- Long-context support: Guards accept up to 256 000 tokens per request, which means you can moderate full agent transcripts, RAG document chains, and multi-step tool logs without splitting or truncating.
- Low-latency inference: Guard Core delivers verdicts in 20–35 ms and Guard Lite in 10–20 ms, making inline moderation practical even for streaming chat interfaces.
- Unified SDK: A single
pip install generalanalysisgives you access to guardrails, red teaming, and MCP Guard. Async and sync clients, typed responses, and built-in audit logging come out of the box. - Compliance mapping: Policy labels map to NIST AI RMF, ISO/IEC 42001, and EU AI Act categories so that moderation decisions translate directly into audit evidence.
Quick startQuick start
Install the Python SDK and run your first guard evaluation in under a minute:
pip install generalanalysisimport generalanalysis
client = generalanalysis.Client()
result = client.guards.invoke(guard_id="ga_guard_core", text="Check this message for policy violations")
print(result.block, result.policies)From here you can explore the AI Guardrails SDK guide for production integration, the AI Red Teaming quickstart for adversarial testing, or the MCP Guard quickstart to protect your MCP-based agents.
Getting helpGetting help
If you need assistance:
- Documentation search: Use the search bar at the top to find specific topics.
- Join the community: Join the General Analysis Discord to connect with other users and devs.
- Contact support: Reach out to our team at info@generalanalysis.com.
- Schedule a demo: Book an AI security consultation with our experts.