Enterprise Ready : VPC | On-Prem | Air-Gapped

The Only Production-Grade Enterprise AI Platform

Portkey stops at LLM routing. TrueFoundry’s high-performance AI gateway lets you run models with low latency, full infrastructure control, and enterprise observability to ship faster and spend less.

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Key Competitive Differentiators
TrueFoundry
Portkey
Performance & Latency
Ultra-low latency gateway (~3ms), scales linearly to thousands of RPS
Adds ~20–40ms latency due to proxying
Deployment & Control
Runs in your VPC (cloud or on-prem). Full infra & data control
Cloud-first or self-hosted gateway; limited infra control
LLM Flexibility
Access to 250+ models (including OpenAI, Anthropic, open-source LLMs, local & remote)
Hosted LLMs only (OpenAI, Anthropic, Cohere, etc.)
MCP & Advanced Routing
Enterprise MCP gateway with auth, access control, task execution, and discovery
Limited MCP support, not enterprise-ready
Observability
Full-stack observability: Real-time logs, metrics, traces and UI-based debugging for each deployment.
Limited visibility into underlying infra (since it doesn’t host models)
Ecosystem Integration
Broad integration: CI/CD & GitOps ready, Kafka/SQS support, cloud-agnostic with open APIs.
Less integration for non-LLM workflows (e.g., ETLor CI/CD).

Key Evaluation Questions

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Question
How TrueFoundry Fixes It
Portkey considerations
“Are we facing latency or hosting issues?”
A one-stop solution to host open-source LLMs + Gateway layer. Best in class performance with low latency of ~3ms
No option to host open-source LLMs on their platform. You might face higher latency than expected
“Can we optimize our LLM usage costs?”
TrueFoundry can cut costs 40–50% by letting you run models on spot instances or GPUs at scale.
You still pay per API call (OpenAI, etc.), and hosting local models isn’t automated.
“Are we looking to try more functionalities on MCP servers?”
TrueFoundry’s MCP Gateway enables enterprise-grade agent execution with built-in tracing, audit logs, and seamless tool integrations.
Portkey provides limited functionality
“Will we outgrow the platform’s capabilities?”
TrueFoundry is a modular platform for training, serving, and monitoring that scales beyond LLMs—without future tool migrations.
Portkey focuses on LLM inference only—scaling to the full ML lifecycle requires adding more tools.

Govern, Deploy, Scale & Trace Agentic AI in One Unified Platform

Govern, Deploy, Scale & Trace Agentic AI in One Unified Platform

Integrations

Framework-agnostic integrations for everything from low-code agent builders to GPU-level performance evaluation.

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Made for Real-World AI at Scale

99.99%

Uptime

Centralized failovers, routing, and guardrails ensure your AI apps stay online, even when model providers don’t.

10B+

Requests processed/month

Scalable, high-throughput inference for production AI.

30%

Average cost optimization

Smart routing, batching, and budget controls reduce token waste. 

Made for Real-World AI at Scale

99.9%

Uptime
Centralized failovers, routing, and guardrails ensure your AI apps stay online, even when model providers don’t.

10B+

Requests processed/month
Scalable, high-throughput inference for production AI.

30%

Average cost optimization
Smart routing, batching, and budget controls reduce token waste.

Real Outcomes at TrueFoundry

Why Enterprises Choose TrueFoundry

3x

faster time to value with autonomous LLM agents

80%

higher GPU‑cluster utilization after automated agent optimization

Aaron Erickson

Founder, Applied AI Lab

TrueFoundry turned our GPU fleet into an autonomous, self‑optimizing engine - driving 80 % more utilization and saving us millions in idle compute.

5x

faster time to productionize internal AI/ML platform

50%

lower cloud spend after migrating workloads to TrueFoundry

Pratik Agrawal

Sr. Director, Data Science & AI Innovation

TrueFoundry helped us move from experimentation to production in record time. What would've taken over a year was done in months - with better dev adoption.

80%

reduction in time-to-production for models

35%

cloud cost savings compared to the previous SageMaker setup

Vibhas Gejji

Staff ML Engineer

We cut DevOps burden and simplified production rollouts across teams. TrueFoundry accelerated ML delivery with infra that scales from experiments to robust services.

50%

faster RAG/Agent stack deployment

60%

reduction in maintenance overhead for RAG/agent pipelines

Indroneel G.

Intelligent Process Leader

TrueFoundry helped us deploy a full RAG stack - including pipelines, vector DBs, APIs, and UI—twice as fast with full control over self-hosted infrastructure.

60%

faster AI deployments

~40-50%

Effective Cost reduction of across dev environments

Nilav Ghosh

Senior Director, AI

With TrueFoundry, we reduced deployment timelines by over half and lowered infrastructure overhead through a unified MLOps interface—accelerating value delivery.

<2

weeks to migrate all production models

75%

reduction in data‑science coordination time, accelerating model updates and feature rollouts

Rajat Bansal

CTO

We saved big on infra costs and cut DS coordination time by 75%. TrueFoundry boosted our model deployment velocity across teams.

Frequently asked questions

What’s the key difference between TrueFoundry and Portkey?

The difference between Portkey and TrueFoundry is that Portkey is an AI Gateway. It routes and monitors your API calls to external model providers. TrueFoundry is a complete AI infrastructure platform. Yes, our Gateway handles routing just like Portkey does, but we also manage the actual compute underneath. That means you can train models, fine-tune them, and deploy them on your own infrastructure, not just route traffic to someone else's API.

Which solution provides more advanced debugging tools?

Between TrueFoundry vs Portkey, TrueFoundry gives you full-stack visibility. Portkey logs your API requests: inputs, outputs, that kind of thing. Useful for debugging prompts. TrueFoundry connects those logs with your infrastructure metrics like GPU memory, pod health, and container logs. So when something breaks, you can see whether it's a model issue or an infrastructure problem like an OOM error. Portkey can't do that because it doesn't touch your infrastructure.

How does model deployment differ in TrueFoundry vs Portkey?

There is a critical distinction in model deployment in Portkey vs TrueFoundry. Portkey does not deploy or host models; it routes traffic to models already hosted elsewhere (like OpenAI or Anyscale). TrueFoundry acts as an orchestration engine. We allow you to take an open-source model (like Llama 3), containerize it, and deploy it directly onto your own cloud or on-premise infrastructure. We handle the autoscaling, GPU provisioning, and health checks, giving you ownership of both the model and the compute it runs on.

Is TrueFoundry better than Portkey for production workloads?

If you are comparing TrueFoundry vs Portkey for strict data sovereignty requirements, TrueFoundry is usually the better fit. We run everything (compute, gateway, storage) inside your VPC or air-gapped environment. Native integration with your Kubernetes clusters, IAM, RBAC, and secrets management. Your model weights, training data, and everything stay inside your controlled infrastructure. Both platforms offer private deployments, but TrueFoundry gives you complete control from day one.

How does Portkey being free and open source compare to TrueFoundry as a paid platform?

TrueFoundry’s value is in the savings and efficiency gains it delivers. In practice, our customers report substantial cost savings (e.g. 40%+ cloud cost reduction) that often outweigh the platform fees. Also, the time saved in engineering (deployment automation, troubleshooting) translates to saved $$$ in manpower. Portkey being free addresses only one slice of the problem – you might still incur higher cloud bills and dev costs. TrueFoundry optimizes the whole pipeline, typically leading to a lower total cost of ownership.