TrueFoundry Agent Gateway
Control layer for governing and observing AI agents in production
- Tool type
- Agent control layer and gateway
- Made for
- Platform and engineering teams
- Runs on
- Web console, APIs and self-hosted deployments
- SaaS, VPC, on-prem and air-gapped deployment are listed; the web console is used for setup and monitoring.
What it does
TrueFoundry Agent Gateway is a control layer that runs AI agents through a single governed execution path. It takes in agent actions, model calls and tool invocations and routes them to LLMs, MCP servers or REST APIs, applying policies, retries, fallbacks and timeouts so multi-step agent workflows behave predictably.
Teams use it to standardize how agents call models and tools, enforce role-based access and token or cost quotas, apply guardrails such as PII filtering, and keep audit trails. It records step-level traces, execution logs, latency and error metrics, and attributes token usage and cost to agents, workflows, teams or environments. It is described as framework-agnostic, naming LangChain, CrewAI and custom agents.
It suits platform and engineering teams running autonomous agents at organizational scale. Deployment options listed include VPC, on-prem, air-gapped and multi-cloud. Agent Gateway pricing is custom, so buyers contact sales for terms.
What it can do
- Route agent tool calls through registered MCP servers with OAuth2 and RBAC policies
- Trace agent steps, model calls and tool interactions end to end
- Enforce token or cost quotas and budgets per agent, workflow or environment
- Automatically retry failed agent steps and define fallback paths for model or tool calls
- Apply guardrails such as PII filtering and restricted-action policies
- Attribute token usage and cost to agents, teams or environments
Works with
- Slack
- GitHub
- LangChain
- CrewAI
- AutoGen
Before you choose
- Agent Gateway pricing is custom for now; contact sales for a quote.
- Model provider charges (OpenAI, Anthropic, AWS, etc.) are billed separately from TrueFoundry.
- Getting started with models in the console uses the AI Gateway setup flow: add model accounts, then create tokens.
Listed under
Get started
Sign up at TrueFoundry; enterprise teams can book a demo for a custom deployment.
- Sign up at TrueFoundry and verify your email.
- Add model provider accounts and models under AI Gateway > Models using your provider API keys.
- Create a Personal Access Token or Virtual Account Token in the Access section and use the Gateway Base URL in your code.
Plans and prices
Agent Gateway pricing is custom for now. Model-provider costs for LLMs used through the gateway are billed separately by those providers.
TrueFoundry Agent Gateway doesn’t publish prices. You get a quote by contacting sales. See their pricing page ↗
Sources for this overview
Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.
- Agent Gateway: Control Layer for AI Agents | TrueFoundry ↗www.truefoundry.com
- Quick Start Guide: Setup & Integration - TrueFoundry Docs ↗www.truefoundry.com
- TrueFoundry | Pricing ↗www.truefoundry.com
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Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.