UbiOps
Data science and machine learning platforms
MLOps platforms
Auto scaling software
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What is UbiOps
UbiOps is an MLOps platform for deploying, running, and monitoring machine learning models and other Python-based services as scalable APIs. It targets data science and engineering teams that need to operationalize models across development, staging, and production environments. The product focuses on packaging code into deployable versions, managing runtime infrastructure, and supporting autoscaling for online inference and batch jobs. It is typically used when teams want a managed deployment layer without building and maintaining their own serving stack.
Managed model deployment workflows
UbiOps provides a structured way to package code, create versioned deployments, and promote changes across environments. This helps teams standardize how models move from experimentation to production. It reduces the amount of custom DevOps work required to expose models as APIs and keep them running. The workflow emphasis aligns with common MLOps needs compared with broader analytics platforms that prioritize data prep and BI.
Autoscaling for inference workloads
The platform supports scaling compute resources based on demand, which is important for spiky online inference traffic. Autoscaling can reduce manual capacity planning and helps control costs by scaling down when idle. This is useful for teams serving multiple models with varying usage patterns. It also supports running workloads without requiring users to directly manage Kubernetes primitives.
API-first operational integration
UbiOps exposes functionality through APIs and integrates with common CI/CD and MLOps toolchains. This enables automation of deployments, rollbacks, and environment management from existing engineering workflows. It supports building model endpoints that can be consumed by applications with standard HTTP interfaces. The approach fits organizations that want to embed model serving into product systems rather than keep it inside notebooks.
Less end-to-end DS tooling
UbiOps focuses on deployment and operations rather than providing a full data science workbench for exploration, feature engineering, and collaborative analysis. Teams may still need separate tools for notebooks, data preparation, and experiment management depending on their workflow. This can increase the number of systems to integrate and govern. Buyers looking for an all-in-one analytics and ML environment may find gaps outside the serving layer.
Platform fit depends on stack
Organizations with mature internal Kubernetes-based serving or standardized cloud-native MLOps patterns may see overlap with existing capabilities. In those cases, the value depends on whether UbiOps’ abstractions and managed operations outweigh the cost and migration effort. Some teams may prefer direct control over infrastructure for specialized performance, networking, or compliance requirements. Evaluations typically require a proof of concept with representative workloads.
Cost and governance complexity
As usage grows across many deployments, environments, and teams, costs can become harder to predict without careful monitoring and quota management. Central governance (access control, auditability, and environment separation) needs to be configured to match organizational policies. Enterprises may require additional due diligence on data residency, security controls, and vendor risk management. These considerations can lengthen procurement compared to self-managed open-source stacks.
Plan & Pricing
Pricing model: Pay-as-you-go (compute credits billed based on GB RAM × seconds) Free tier/trial: Free plan available (permanent, all features, no duration limit) — enough compute to get started How billing works: Active deployments consume compute credits; compute credits = provisioned GB RAM × active time (seconds). Compute credits reset monthly; overage leads to suspension if limit reached. Plans / Packages:
- UbiOps Cloud — Hosted by UbiOps; on-demand compute, pay per use.
- UbiOps Private — Installed/managed on customer's private environment; custom pricing and SLA. Example costs: No public per-credit or per-instance unit prices are published on the official site; specific rates require contacting UbiOps / sales. Discounts / special programs: Start-up accelerators / VC credits, bring-your-own-cloud credits, and negotiated volume/commitment discounts (handled via sales/contact). Notes: Official documentation defines compute credits and subscription limits; pricing details are not listed publicly on the vendor site.
Seller details
UbiOps B.V.
The Hague, Netherlands
2019
Private
https://ubiops.com/
https://x.com/ubiops
https://www.linkedin.com/company/ubiops/
