Sold by: TrueFoundry
TrueFoundry AI Gateway is a unified interface for accessing 1000+ LLMs, MCPs, Agents, with enterprise-grade security, observability, and governance.
4.6
Overview
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TrueFoundry's AI Gateway brings together the LLM Gateway, MCP Gateway, and Agent Gateway into a unified infrastructure layer that sits between your applications and every AI resource they touch: models, tools, and agents. At its core, the LLM Gateway normalizes access to 250+ LLMs behind a single API. Intelligent routing selects the fastest, most cost-effective model in real time, with automatic failover when providers go down. Token usage, cost, and latency are tracked centrally by team, environment, or workload. As AI moves beyond inference into tool use, the MCP Gateway extends this control to MCP Servers, giving agents governed, discoverable access to enterprise systems like Slack, GitHub, and internal APIs. Every tool call is authenticated via OAuth2 and RBAC, traced end-to-end, and auditable. For agentic workloads, the Agent Gateway registers and invokes agents through a standardized execution layer, managing retries, timeouts, guardrails, and agent-to-agent delegation without scattering that logic across individual applications. One control plane with centralized governance and observability across every model, tool, and agent your organization runs. Platform teams get full visibility into cost, performance, and access while security teams get the audit trails and policy enforcement they need. Deployable in VPC, on-prem, or air-gapped. SOC 2, HIPAA, GDPR compliant.
Highlights
- Unified API Access to 250+ LLMs: Streamline integration with a wide array of LLMs through a single, standardized API, simplifying development and deployment processes.
- Comprehensive Observability & Insights: Gain real-time visibility into model usage, performance metrics, and operational costs, facilitating informed decision-making and optimization.
- Robust Access Control & Performance Optimization: Implement granular rate limits and RBAC to ensure secure access and optimal resource utilization, while intelligent load balancing and low-latency processing maintain high system reliability.
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
LLMGTW | LLM Gateway Contract | $1,000.00 |
Vendor refund policy
All fees are non-cancellable and non-refundable except as required by law.
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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Support
Vendor support
For support related to our products, you can contact us via our support page at https://www.truefoundry.com/support or email us at support@truefoundry.com .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
Michelle A.
Simplify the AI infrastructure exceptionally
Reviewed on Dec 09, 2025
Review provided by G2
What do you like best about the product?
The most useful thing is that it simplifies the AI infrastructure.
What do you dislike about the product?
It can be a bit expensive for small projects.
What problems is the product solving and how is that benefiting you?
It prevents me from complicating things with technology and makes my AI models work quickly and well.
Moises A.
Accelerate teamwork, but there is still room for improvement
Reviewed on Nov 06, 2025
Review provided by G2
What do you like best about the product?
I like that TrueFoundry helps data teams work faster.
What do you dislike about the product?
there is nothing specific that I don't like but I think it can still keep improving.
What problems is the product solving and how is that benefiting you?
Solve the problem of complexity in development and this benefits me because it allows me to focus more on the strategic and analytical part.
Neha J.
Fast, Scalable, and Secure AI Deployment with TrueFoundry
Reviewed on Oct 17, 2025
Review provided by G2
What do you like best about the product?
TrueFoundry is fast, scalable & works across cloud or on prem setups while saving GPU and infra costs. It is secure and compliant (SOC2, GDPR, HIPAA) with full monitoring, logging, and access control for sensitive data. Easily implementable to many AI models and helps teams launch AI products faster with ready tools and templates.
What do you dislike about the product?
A bit complex to learn. Enterprise features, on prem deployments, GPU usage etc. likely come at a higher cost. If you don’t already have cloud setup or Kubernetes knowledge, you may need to invest in setup and maintenance. Even though many integrations are possible, deeply custom workflows might require building custom components or workarounds
What problems is the product solving and how is that benefiting you?
TrueFoundry helps companies easily build, run, and manage AI tools without handling complex tech setup. It keeps data secure and follows rules like GDPR and HIPAA while cutting down infra and GPU costs.
andré P.
Streamlined Platform for Managing and Deploying Machine Learning Workflows
Reviewed on Oct 16, 2025
Review provided by G2
What do you like best about the product?
What I appreciate most about TrueFoundry is how it simplifies the end-to-end management of machine learning models. The interface is clean and intuitive, allowing teams to deploy, monitor, and iterate on models with minimal friction. Integration with popular frameworks like TensorFlow and PyTorch is seamless, and the automation features save significant time, especially for repetitive tasks. Their customer support is responsive and knowledgeable, making onboarding and troubleshooting much smoother. I use it regularly in daily ML workflows, and it has quickly become an indispensable tool.
What do you dislike about the product?
The main limitation is that setting up highly customised pipelines can require a bit of effort, especially for very complex model architectures. Some of the more advanced monitoring features also have a learning curve, but once mastered, they are extremely powerful.
What problems is the product solving and how is that benefiting you?
TrueFoundry addresses the challenges of deploying and maintaining ML models at scale. It helps detect issues like model drift, performance degradation, or data inconsistencies in real time, which previously required manual oversight. By centralising monitoring and automating deployments, it reduces errors, saves time, and ensures models remain reliable in production. This has led to greater confidence in ML-driven decisions and improved collaboration across data science and engineering teams.
Subrat M.
Helps simplify ML deployment and monitoring
Reviewed on Oct 13, 2025
Review provided by G2
What do you like best about the product?
TrueFoundry makes it much easier to deploy and manage ML models without spending too much time on DevOps setup. The interface is simple, and the integration with existing tools like Kubernetes and GitHub is smooth. I also like how it standardizes the workflow for model training and deployment, which saves a lot of time.
What do you dislike about the product?
Some features still feel early-stage and could use more polish. The documentation can be improved in a few areas, especially for first-time users setting up pipelines. Apart from that, the platform performs well.
What problems is the product solving and how is that benefiting you?
It helps automate and streamline the entire ML lifecycle from experimentation to production. We no longer have to manually handle deployment scripts or deal with environment inconsistencies. It’s reduced our model deployment time and made collaboration between ML and DevOps teams smoother.