Backed by Y Combinator

Make AI, your own.
Build with AI that's actually open!

Fast, scalable, production-ready infrastructure orchestration, to build with open source LLMs, VLMs, audio models, embeddings, and vector databases, when performance, security, and reliability matter the most.

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Build with flexibility. 
Deploy with ease. 
Scale with control.

Train and deploy open source AI models, embeddings, and vector databases to scale your AI apps, copilots and agents.
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Migrate from closed models in production using OpenAI-compatible APIs while ensuring security and governance.

Fast, scalable model inference

Deploy and scale open-source, custom, and fine-tuned AI models on inference infra purpose-built for production environments. Run seamlessly in our cloud or yours.

High speed + Low latency

Deploy your models on a state-of-the-art inference stack designed for peak performance.

Autoscaling + Scale-to-zero

Dynamically scale GPU resources with intelligent autoscaling and scale-to-zero.

Efficient GPU utilization

Maximize performance with advanced GPU scheduling and orchestration.

Blazing fast cold starts

Rapid model readiness ensures responsiveness in any deployment scenario.

Multi-region deployment

Comply with the residency needs of your AI workloads across regions.

Vector database hosting

In-house RAG pipelines with private instance(s) of your vector database.

Dynamic GPU fractioning

Serve multiple models by segementing GPU memory dynamically.

Model usage metrics

Track usage and performance trends across all your models.

Precise, efficient model training

Train your custom models — LLMs, VLMs, ASR models and embeddings — on our optimized training stack, purpose-built for the running parallel training jobs at scale.

Your data = Your model

Use your own data to train generative AI models that understand your context and outcomes.

Multi-modal training stack

Unlock the potential of AI by training models across modalities and building truly compound AI.

Multi-GPU + Multi-node training

Get faster training times by running your workloads across multiple GPUs and nodes.

Training console and metrics

Track training time, loss curves, gradient norms and more from our console directly.

Supervised Fine-tuning

Use instruction data to fine-tune LoRA adapters for various models with SFT.

Continual Pre-training

Train any model towards what is called "domain adaptation" using CPT.

Reinforcement Fine-tuning

RFT helps you utilize reward functions to train your own reasoning models.

Embedding Fine-tuning

Enhance your retrieval capabilities by training your custom embeddings.

Built for modern teams

Effective and secure collaboration is at the core of any modern team, and Pipeshift is designed keeping those needs in mind.

Team settings and access control

Manage your workloads while complying with your org-structure.

100% infrastructure agnostic

Pipeshift can be deployed and scaled on any cloud or on-prem.

Connect your own data sources

Access your data from your preferred data vendor or warehouse.

Get notified in your Slack

Track training jobs, deployments and more, all within your Slack.

DevEx meets Reliability

Cloud consoles are a rabbit-hole of hidden costs, software bloat and steep learning curves. Pipeshift is designed with DevEx at it's core, combined with transparency, security and unparalleled scalability.

Deploy on our cloud or yours

100% cloud agnostic
Data warehouse integrations
On-premise deployment

Enterprise ready security

Data encryption
SOC 2 Type II compliant
ISO 270001 compliant

Built for scaling

Redefined DevEx and console
Auto-scaling and scale-to-zero
Schedulers and load balancers

“Pipeshift’s ability to orchestrate GPUs to deliver over 500 tokens/second without any compression or quantization is extremely impressive. It helps reduce compute footprint and avoid cost creeps, while delivering a secure and reliable environment when your AI is in production.”

Anu Mangaly

Director Software Engineering, NetApp

Achieve your AI outcomes. On your own terms.

Open source AI models are faster, more efficient to run, more customizable to verticals, and unlock privacy, control and ownership on all levels of your stack.