Pipeshift has announced a $2.5 million seed round aimed at providing enterprises with the infrastructure needed to efficiently build, deploy, and manage open-source AI models. As more than 80% of companies move toward open-source GenAI, Pipeshift’s solution removes common bottlenecks related to privacy, control, and the engineering overhead of stitching together multiple components.
Revolutionizing MLOps for GenAI
Pipeshift’s new-age Platform-as-a-Service (PaaS) accelerates AI orchestration by offering a modular MLOps stack that runs on any environment—cloud or on-premises. This end-to-end service covers a wide range of workloads, including LLMs, vision models, audio models, and more. Rather than acting as a GPU broker, Pipeshift hands enterprises direct control of their infrastructure, enabling them to:
- Scale from day one with in-built autoscalers, load balancers, and schedulers
- Fine-tune or distill open-source models in parallel with real-time tracking of training metrics
- Save on GPU costs by hot-swapping fine-tuned models without GPU memory fractioning
- Maintain enterprise-grade security to keep proprietary data and IP fully in-house
By consolidating these capabilities into a single platform, Pipeshift simplifies deployment workflows and drastically reduces time-to-production.
Strong Industry Backing
The $2.5 million seed round was led by Y Combinator and SenseAI Ventures, with additional support from Arka Venture Labs, Good News Ventures, Nivesha Ventures, Astir VC, GradCapital, and MyAsiaVC. Esteemed angels like Kulveer Taggar (CEO of Zuess), Umur Cubukcu (CEO of Ubicloud and former Head of PostgreSQL at Azure), and Krishna Mehra (former Head of Engineering at Meta and co-founder of Capillary Technologies) also participated.
Arko Chattopadhyay, Co-Founder and CEO of Pipeshift, stated: “2025 marks the year when GenAI transitions into production and engineering teams are witnessing the benefits of using open-source models in-house. This offers high levels of privacy and control alongside enhanced performance and lower costs. However, this is a complex and expensive process involving multiple components being stitched together. Pipeshift’s enterprise-grade orchestration platform eradicates the need for such extensive engineering investments by not only simplifying deployment but also maximizing the production throughput.”
Rahul Agarwalla, Managing Partner of SenseAI Ventures, observed: “Enterprises prefer open-source GenAI for the benefits of privacy, model ownership, and lower costs. However, transitioning GenAI to production remains a complex and expensive process requiring multiple components to be stitched.” He continued: “Pipeshift’s enterprise-grade orchestration platform eliminates the need for such extensive engineering investments by not only simplifying deployment but also maximizing the production throughput.”
Yash Hemaraj, Founding Partner at Arka Venture Labs and General Partner at BGV, remarked:“We invested in Pipeshift because their innovative platform addresses a critical need in enterprise AI adoption, enabling seamless deployment of open-source language models. The founding team’s deep technical expertise and track record in scaling AI solutions impressed us immensely. Pipeshift’s vision aligns perfectly with our focus on transformative Enterprise AI companies, particularly those bridging the US-India tech corridor, making them an ideal fit for our portfolio.”
Why Pipeshift Stands Out
Founded by Arko Chattopadhyay, Enrique Ferrao, and Pranav Reddy, Pipeshift’s core team has been tackling AI orchestration challenges long before this seed funding. Their experience includes scaling a Llama2-powered enterprise search app for 1,000+ employees on-premises, highlighting firsthand how tricky and resource-intensive private AI deployments can be.
Key differentiators include:
- Multi-Cloud Orchestration: Pipeshift seamlessly handles a mix of cloud and on-prem GPUs, ensuring cost optimization and quick failover.
- Kubernetes Cluster Management: An end-to-end control panel allows enterprises to create, scale, and oversee Kubernetes clusters without juggling multiple tools.
- Model Fine-Tuning & Deployment: Engineers can finetune or distill open-source models using custom datasets or LLM logs, with training metrics viewable in real time.
- 360° Observability: Integrated dashboards track performance, enabling quick troubleshooting and efficient scaling.
Built for Production, Not Just Experimentation
Companies often face limitations with generic API-based solutions that aren’t built for in-house privacy. Pipeshift flips this model by focusing on secure, on-prem or multi-cloud deployments. The platform supports over 100 large language models, including Llama 3.1, Mistral, and specialized offerings like Deepseek Coder. This diverse selection helps meet the specific performance, cost, and compliance needs of each project.
Some notable benefits include:
- Up to 60% in GPU infrastructure cost savings
- 30x faster time-to-production
- 6x lower cost compared to GPT/Claude
- 55% reduction in engineering resources
Looking Ahead
Having already collaborated with over 30 companies, including NetApp, Pipeshift plans to further its mission of delivering powerful open-source AI solutions without the usual complexity. Its single-pane-of-glass approach to MLOps, combined with dedicated onboarding and ongoing account management, ensures enterprises can stay focused on leveraging AI for business outcomes rather than wrestling with infrastructure.
With private data protections, hybrid cloud compatibility, and modular flexibility at its core, Pipeshift is poised to meet the diverse needs of enterprise AI projects. By bridging the gap between open-source innovation and enterprise-grade requirements, the company is paving the way for a new era of agile, secure, and cost-effective AI deployments.
Pipeshift offers end-to-end MLOps orchestration for open-source GenAI workloads—embeddings, vector databases, LLMs, vision models, and audio models—across any cloud or on-prem GPUs..