usageguard
UsageGuard is an enterprise-ready AI development, observability, security, and cost-management platform that provides a single unified API to integrate, monitor, and govern multiple large language models across cloud, private cloud, and on‑premise deployments.
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Quick Overview
Best for: Security
What it does
Security software for decision-makers comparing workflow fit and alternatives.
Best fit
Security
Pricing snapshot
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usageguard
UsageGuard is presented as a complete platform for building and monitoring AI applications with capabilities spanning AI development, observability, security & governance, and cost control. It targets enterprises and development teams that need a unified inference endpoint to integrate multiple LLM providers, monitor performance and usage, enforce security and compliance policies, and control AI spend. The platform supports deployment on public cloud, private cloud, and fully on‑premise (air-gapped) environments, and emphasizes enterprise features such as SOC2 Type II and GDPR compliance.
Platform for building and monitoring AI applications with security, cost control, and tracking.
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Unified inference endpoint
One API that provides a single endpoint to access multiple LLM providers and models without changing application code.
Model‑agnostic integrations
Support for major LLM providers including OpenAI, Anthropic, Meta Llama, Mistral, Google Gemini and more, allowing switching between providers.
Real-time streaming & low latency
Real-time streaming support with typical additional latency described as minimal (50–100ms per request) and overall platform latency metrics shown on the site.
Observability & analytics
Monitoring, logging, tracing, metrics, request monitoring, session management, and real-time insights into AI operations.
Security & governance
Content filtering, PII protection, prompt sanitization, customizable security policies, data isolation, end-to-end encryption, and compliance controls.
Cost control & spend management
Usage tracking, budget controls, automated cost management tools, and optimizations to reduce AI spend.
Document processing & Enterprise RAG
Capabilities for building applications with documents, including enterprise retrieval-augmented generation workflows.
Agents (Beta)
Tools to build and deploy autonomous agents (noted as Beta).
Flexible deployment
Options to deploy on public AWS regions, private cloud, or fully on-premise with air-gapped deployments and custom security policies.
Enterprise SLAs & support
24/7 enterprise support with guaranteed SLAs and options for enterprise demos and dedicated support.
Pricing
Current pricing details are not available from the vendor source.
Use Cases
Multi‑provider LLM integration
Unify access to multiple LLM providers through one API to simplify model switching and provider management without code changes.
Enterprise AI observability
Monitor model performance, trace requests, view usage patterns, and get real-time analytics for production AI applications.
Security and compliance for AI
Apply content filtering, prompt sanitization, PII protection, and custom security policies to meet enterprise compliance needs like SOC2 and GDPR.
Cost management and optimization
Track usage, enforce budgets, and optimize model usage to control and reduce AI spending.
Document-driven applications and RAG
Build enterprise retrieval-augmented generation (RAG) workflows and document-based AI features using unified document processing capabilities.
On‑premise and private deployments
Deploy the platform within private cloud or on-premise data centers for full data isolation and custom security policies.
Integrations
OpenAI
Access OpenAI GPT models through UsageGuard's unified API.
Anthropic
Integrate Anthropic Claude models via the platform's single endpoint.
Meta Llama
Support for Meta Llama family models as part of multi‑provider model integrations.
Mistral
Mistral model support listed among supported providers.
Google Gemini
Google Gemini mentioned as a supported model provider.
Benefits
Limitations
Frequently Asked Questions
How does UsageGuard work?
Which LLM providers does UsageGuard support?
Will I need to change my existing code to use UsageGuard?
Can I use multiple LLM providers through UsageGuard?
Does using UsageGuard affect performance?
Can UsageGuard prevent prompt injection attacks?
Can I customize security policies for different projects or teams?
How does UsageGuard ensure the privacy of our data?
How can I get support if I encounter issues?
Getting Started
- 1 Request a demo or enterprise trial to evaluate the platform and get onboarding (site includes 'Request Demo' and enterprise demo options).
- 2 Set up the platform integration (the site states setup takes a few minutes) and deploy connectors for your application.
- 3 Update your application to point to the UsageGuard unified API endpoint and include your UsageGuard API key and connection ID as described in the quickstart guide.
- 4 Configure connections, security policies, usage limits and monitoring per project or team, then deploy to your chosen environment (cloud, private cloud, or on‑premise).
Support
Docs
Quickstart guide and documentation referenced on the site for integration and onboarding.
Status page
A status page is available for known issues (referenced on the site).
Email / Support team
The site asks users to email the support team if they can't find answers in the docs.
Enterprise support
24/7 enterprise support with guaranteed SLAs and enterprise demo / onboarding options.
API
Quickstart guide and developer docs referenced on the site (see docs/quickstart guide on the UsageGuard website).
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