TrueFoundry AI Gateway screenshot

TrueFoundry AI Gateway

5.0 (1)
OtherPaid

Unify, govern, and scale GenAI with one OpenAI‑compatible gateway.

Last updated May 6, 2026

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What is TrueFoundry AI Gateway?

TrueFoundry AI Gateway is an enterprise-grade LLM proxy that unifies access to 250+ models (OpenAI, Claude, Gemini, Groq, Mistral, and more) through a single OpenAI-compatible API, with centralized key management, multi-model routing/failover, guardrails, rate limiting, observability, and flexible deployment options (SaaS, customer cloud, or on‑prem) built for high-scale, compliant GenAI workloads.

TrueFoundry AI Gateway's Top Features

Key capabilities that make TrueFoundry AI Gateway stand out.

Unified OpenAI-compatible API for chat, completion, embedding, and reranking

Access to 250+ LLMs (OpenAI, Claude, Gemini, Groq, Mistral, and more) via one endpoint

Centralized API key management, SSO, RBAC, and team/workspace authentication

Multi-model orchestration with intelligent routing, retries, and failover

Rate limiting, quotas, and policy enforcement per user/team/model

Input/output guardrails for toxicity, bias, hallucinations, PII, and policy violations

Comprehensive observability: requests, tokens, cost, latency by model/team/user/metadata

OpenTelemetry exports and integrations with Prometheus, Grafana, and Elastic

Audit logging and full request tracing for governance and debugging

Playground for experimentation, prompt templating, and code snippet generation

Native MCP support for agent workflows and secure enterprise tool access

Streaming and non-streaming support with tool/function calling and structured outputs

On-premise and hybrid deployments with data residency controls

Low-latency, in-memory decisioning using stateless gateway pods and NATS

High-scale performance (10B+ requests/month, multi-region, 99.99% uptime targets)

ClickHouse-backed analytics and Postgres for configuration/state

Compatibility with LangChain and popular OpenAI SDKs (no app code changes)

Cost and usage breakdowns by model, team, user, environment, or metadata

Fallback rules, caching, and health‑based routing for reliability

Compliance-ready posture (e.g., SOC 2, HIPAA, GDPR) and air‑gapped support

Use Cases

Who benefits most from this tool.

Platform teams

Provide a single secure endpoint and API key for all LLM providers across the company.

ML/AI engineers

A/B test and route across multiple models based on cost, latency, or output quality.

Application developers

Ship features faster using OpenAI-compatible SDKs, tool calling, and prompt templates.

Security/compliance

Enforce RBAC, quotas, audit logs, and guardrails for PII/toxicity across all LLM traffic.

SRE/DevOps

Ensure reliability with retries, failovers, caching, and real-time health-based routing.

FinOps/operations

Track and optimize spend with token and cost analytics by model, team, and user.

Data privacy teams

Deploy on-prem or in a controlled cloud for data residency and regulatory compliance.

Product managers

Experiment in a Playground, compare models, and standardize prompts and configurations.

Agent builders

Use MCP to connect enterprise tools (Slack, GitHub, Confluence) with policy controls.

Enterprises migrating vendors

Switch models/providers without app changes via the unified OpenAI-compatible interface.

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Tags

LLM proxyunified access250+ modelsOpenAI-compatible APIcentralized key managementmulti-model routing/failoverguardrailsrate limitingobservabilityflexible deployment optionshigh-scalecompliant GenAI workloads

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Frequently Asked Questions

What is TrueFoundry AI Gateway?
It’s an enterprise-grade proxy between your apps and LLM providers/MCP servers, offering a unified OpenAI-compatible API to access 250+ models with built-in governance, security, and observability.
How does the AI Gateway work?
Your application calls a single gateway endpoint using one API key; the gateway routes to the configured model or tool, handling authentication, policies, retries, and failovers.
Which models and integrations are supported?
OpenAI, Anthropic (Claude), Google Gemini, Groq, Mistral, and 250+ LLMs; plus MCP servers for tools like Slack, GitHub, Confluence, and Datadog. Supports chat, completion, embedding, reranking, tool calling, and safety services.
What deployment options are available?
Fully managed SaaS, hybrid (data in your storage), or self-hosted on-prem/cloud with components like stateless gateway pods, NATS, Postgres, and ClickHouse for data residency and low latency.
What governance and security features are included?
Centralized API keys, SSO/RBAC, OAuth2 tool policies, rate limiting/quotas, input/output guardrails (toxicity, bias, PII, hallucinations), audit logging, and policy-based routing/fallbacks.
What observability and analytics does it provide?
Per-request metrics for requests, tokens, cost, and latency, broken down by model, team, user, and metadata; tracing via OpenTelemetry and exports to Prometheus, Grafana, Elastic; analytics stored in ClickHouse.
Does it support on-premise deployment?
Yes. On-prem delivers the same unified API with in-memory decisions for ultra-low latency and includes governance (access control, rate limits, guardrails, audit logs) without external calls.
Can it handle tool calling and agent workflows?
Yes. It supports native MCP for secure tool access with OAuth2/RBAC, and simulates function/tool calls with structured outputs and per-call policies.
What performance and scale can it handle?
Designed for high-scale production (10B+ requests/month), streaming/non-streaming, and multi-region; supports failover, retries, and intelligent routing to meet 99.99% uptime goals.
Is the API compatible with existing SDKs?
Yes. It’s OpenAI API–compatible, so you can use existing OpenAI clients and LangChain without code changes when switching models or providers.