TrueFoundry is an enterprise platform for deploying, governing, and monitoring AI and machine-learning workloads. It provides an AI gateway, model and agent deployment tools, infrastructure orchestration, and observability for organizations operating AI applications across cloud, virtual private cloud (VPC), on-premises, or hybrid environments.

Key Capabilities

AI gateway and agent management: Routes model traffic and supports agent workflows, including tool use, memory, and action planning.
MCP and agent registry: Maintains discoverable registries of Model Context Protocol (MCP) tools, APIs, and agents with schema validation and access controls.
Model deployment and fine-tuning: Hosts large language models (LLMs), embedding models, and custom models; supports fine-tuning jobs, experiment tracking, and production deployment.
Prompt lifecycle management: Versions, manages, and monitors prompts to support repeatable agent behavior.
Observability: Traces prompt, tool, and model execution; tracks latency, outcomes, token usage, cost, and underlying GPU, CPU, and cluster resources.
Governance: Provides role-based access control, audit logging, policy enforcement, rate limits, usage quotas, and data-residency controls.

Audience & Use Cases

Audience: ML platform teams, DevOps and platform engineers, data scientists, and enterprise AI teams.
Use cases: Deploying production AI agents and models, operating GPU-backed inference infrastructure, governing model access, monitoring AI workloads, and integrating AI services with existing observability tools.

Technical Specifications

Deployment options: Public cloud, VPC, on-premises, air-gapped, hybrid, and multi-cloud environments.
Inference backends: Supports model-serving backends including vLLM, Text Generation Inference (TGI), and NVIDIA Triton.
Integrations: OpenTelemetry-compatible and designed to work with tools such as Grafana, Datadog, and Prometheus.

TrueFoundry

What is TrueFoundry?

Categories & Use Cases