“The state of AI reveals a landscape defined by both wider use…and stubborn growing pains, with the transition from pilots to scaled impact remaining a work in progress at most organizations.”
– McKinsey – State of AI 2025
AI Today
Enterprises universally recognize AI’s transformative potential for innovation, efficiency, and competitive advantage. McKinsey reports a near-doubling of AI usage in the past three years, with 88% of organizations investing in the technology. However, ROI remains uneven.
Despite the common availability of AI tools, most organizations struggle to fully embed them into workflows and processes to achieve meaningful, enterprise-wide results. The core issue? Bridging the significant gap between developing AI prototypes and successfully deploying and scaling them into production environments to achieve real business impact.
While McKinsey’s survey shows overall only 20% of AI & ML projects achieve business impact, a recent MIT study says 95% of Generative AI pilots fail because they lean on generic tools – great for demos and prototypes, brittle in actual enterprise workflows.
Introducing Wallaroo – Unified AI Orchestration Platform for Enterprise AI
Wallaroo is a game-changer. Our platform enables seamless deployment, orchestration and operation of enterprise-grade AI inference. By bridging the gap between AI prototypes and AI ROI – and between AI developers and AI infrastructure – Wallaroo turns ambitious AI visions into tangible, measurable business value. Wallaroo.AI provides:
- A single software system purpose-built for Enterprise AI that radically simplifies deployment, scaling, optimization and management across any cloud, on-premise, edge or hybrid environment with privacy and security
- The flexibility and control to run ML, Vision, Gen AI and Agentic AI where you need it to run, with full compliance and integration into enterprise workflows, and on diverse AI silicon.
- Enterprise AI success via a customer AI enablement team with deep AI expertise and a successful track record in solving enterprise AI deployment and scaling challenges.
At its core, Wallaroo.AI addresses critical challenges in the productionization of AI. Traditional approaches to AI deployment are plagued by manual processes and the lack of enterprise-ready tooling that lead to delays, inefficiencies and ultimately failure. Key problems include:
Day 1: Get AI into production
- Lack of Specialized Expertise: Keeping up with the rapidly evolving AI landscape and the technical skills required for deployment.
- Enterprise Integration and Compliance: Meeting strict enterprise demands for security, privacy, and seamless integration into existing enterprise systems & workflows.
- Complexity of Use Cases: Deploying advanced AI, such as multi-modal models or Agentic AI, can be difficult.
- Infrastructure Diversity: The necessity for extensive, custom engineering to deploy models across various environments (e.g., on-premise clusters, hybrid clouds, or edge locations) or use new AI chips.
Day 2: Optimizing and Scaling Model and Infrastructure Performance
- Difficulty in quickly iterating to improve both model and infrastructure performance.
- High inference costs, particularly for resource-intensive models like LLMs.
- Slow and complex update processes coupled with a lack of live model feedback.
Day 3 & Beyond: Ongoing operations & AI effectiveness; scaling to more & more deployments
- Operational Risk and Downtime: Undetected model issues, lack of real-time anomaly detection, and inadequate monitoring/validation lead to significant business & compliance risks and costly operational downtime
Inefficient and Error-Prone Production: The absence of automation, repeatable processes, and robust troubleshooting tools results in an expensive and error-prone production environment.
The Solution
Wallaroo.AI solves these by offering a purpose-built platform for the full lifecycle of Enterprise AI, delivering faster return on investment (ROI), enhanced scalability, and reduced operational overhead. We deliver fast, effective enterprise-grade AI inference that works with any model, any hardware, anywhere. Our platform has 3 key elements:
Wallaroo AI Hub: The AI Hub serves as a centralized control plane for many forms of automation, including model packaging, deployment, orchestration, observability, and workflow automation while ensuring enterprise-grade security with features like encryption, user access control, audit logs, and support for air-gapped AI operations. .
Wallaroo ToolKit: SDK, APIs and connectors for popular AI tools (e.g., OpenAI SDK, vector databases, model registries) designed to make it easy for AI developers to ship, scale and manage fast AI inference via a few lines of Python or an API call. The toolkit works out-of-the-box in all common data and AI environments such as Google Vertex and Databricks and for any type of model, including arbitrary code.
Wallaroo Inference Stack: State-of-the-art Inference Software that delivers production-ready, enterprise-grade ultrafast and scalable AI inference across any AI silicon, cloud, on-prem, and edge environment with built in authentication, auditability and observability. This stack can work with any AI acceleration library, runtime, or engine – ONNX, PyTorch, vLLM, SGLang, Llama.cpp, TF, including custom libraries.Our platform enables customers to package and deploy production-ready inference in minutes, migrate workloads seamlessly, and update models inline without downtime—achieving up to 4-6X faster time-to-value, 80% lower infrastructure usage, 12X faster inferencing, and sub-millisecond latency.
The Benefits
Enterprises of all sizes can deploy AI like a startup, yet operate AI like a mature, technically sophisticated enterprise meeting security, compliance, and scalability requirements. We democratize AI for enterprises by bridging the gap between AI and IT – transforming AI from a siloed experiment into a scalable and effective driver of business success.
The Wallaroo platform enables AI developers (ML engineers, data scientists, software engineers, and infrastructure specialists) to automate complex AI deployment, scaling, and operations workflows. This saves up to 40% of their time, accelerates time-to-value by 4-6x, and reduces production costs by up to 80%. And for enterprises without the full range of AI skills or bandwidth, our AI Enablement team with deep expertise across industries, infrastructure, and model frameworks will help get AI into production and then scale it as needed.
That means enterprises can focus on driving value for the business, instead of complex engineering and infrastructure tasks.
To be specific:
| Stage | Wallaroo Key Enabling Features |
| Day 1: Ship AI fast to anywhere with no engineering fuss | Easy deployment via autopackaging and orchestration of models and supporting assets into an easily deployable inference serviceProduction-ready, Enterprise-grade Inference stack with flexible enterprise integration with authentication and encryptionEdge/On-Prem/Self-hosted/Private AI SupportHeterogenous AI HW & Runtime supportML, Vision, Generative AI, Agentic AI, and arbitrary code support |
| Day 2: Run Optimized AI at Scale, low-cost | State-of-the-art Inference: Top to bottom coordinated orchestration, routing, batching and disaggregated serving to maximize HW utilization, minimize costBuilt in load-balancing, smart batching & autoscaling, and disaggregated inference serving across AI hardwareRealtime AI inference performance observability metricsWorkflow automation for repeatable AI deployments across use cases and infrastructure. |
| Day 3: Unified Operations and management | AI Hub with centralized management of distributed cloud to on-prem/edge compute and AI deployments Proactive Feedback loops: real-time model logging, monitoring with zero downtime production updates for rapid iterations at scaleReal-time model and infrastructure analytics and alerts for troubleshooting |
Our Customers
- Go from prototype to production fast for any AI use case: Quickly build enterprise-grade, production-ready pilots, easily move pilots into production, and scale deployments as needed for business impact
- Can deploy anywhere: AWS, Azure, GCP, OCI, IBM Cloud, Neoclouds, on-premise setup, or edge locations, as well asHybrid, private, or air-gapped environments to meet stringent compliance and data sovereignty requirements. Wallaroo also enables seamless workload migration across environments.
- Can run inference on any AI silicon: Nvidia, AMD, IBM, Qualcomm, Intel, ARM, TPU’s, Tranium, etc.
AI Developers
Data scientists and Data engineers can focus on building and scaling data pipelines & AI models while taking advantage of Wallaroo’s self service capabilities to manage & automate AI deployment and inference workloads without being bottlenecked by infrastructure complexity.
- Data scientists and Data engineers can focus on building and scaling data pipelines & AI models while taking advantage of Wallaroo’s self service capabilities to manage & automate AI deployment and inference workloads without being bottlenecked by infrastructure complexity.
- AI & ML engineers can finetune, package and deploy LLMs with state-of-the-art AI inference on diverse AI infrastructure taking advantage of Wallaroo’s pre-built AI runtimes and engines across the most common AI silicon offerings (NVIDIA, AMD, Arm, IBM, Qualcomm, etc.)
- DevOps, Infrastructure and Software engineers can leverage Wallaroo’s pre-packaging and pre-optimized AI inference microservices to enhance and modernize enterprise applications & systems while eliminating the friction from “containerization” and “AI re-engineering” when transitioning from AI development to AI deployment on production infrastructure.
Ultimately, C-level executives and business stakeholders see accelerated ROI from AI, as they develop realistic pilots faster, go from pilot to production faster, and scale AI easier and at lower cost across users, data, locations, and use cases.
In summary, Wallaroo.AI supercharges your AI strategy.
Additional Resources
