Valohai
- Company typePrivate
- Founded2016
- HeadquartersTurku, Finland
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
Valohai firmographics
Firmographics- Name
- Valohai
- Legal name
- Valohai Oy
- Website
- https://valohai.com
- Company type
- Private
- Founded year
- 2016
- Operating status
- Operating
- Headcount range
- 11–50 employees
- Ownership category
- akta.pro rank
Valohai industry classification
Industry- Product category
- MLOps Platform
- NAICS
- Computer Systems Design and Related Services (5415), Software Publishers (5132)
- SIC
- Services-Computer Integrated Systems Design (7373)
- akta.pro primary industry
- End-to-End MLOps & ML Platform Suites (HDAAABAA)
- akta.pro secondary industries
- LLMOps & Generative AI Platforms (Prompt/Agent Orchestration, RAG) (HDAEANAD), End-to-End Enterprise AI Platforms (MLOps & Model Lifecycle Management) (HDAEANAA), AI/ML Solution Integration & MLOps Enablement (BPAEAAAJ)
Keywords
Where Valohai is headquartered
LocationHeadquarters
- HQ city
- Turku
- HQ country
- Finland
- HQ region
- Europe
Offices2 records
Markets served
Valohai business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Infrastructure, Marketing or Sales, Operations
Revenue model
- Platform SaaS Subscription: Valohai operates as a SaaS MLOps platform with subscription-based pricing. Customers pay for platform access based on usage of compute resources, team size, and feature tiers. The platform offers a free trial for self-service onboarding, with enterprise accounts likely on negotiated contracts.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Freemium | Monthly | Free trial available for self-service onboarding |
| Subscription | Annual | Enterprise plans with custom pricing |
Go-to-market motion2 records
Distribution channels4 records
Marketing channels7 records
Valohai product offering
Product offeringCore offering
Valohai sells an enterprise MLOps and LLMOps platform that automates, versions, and orchestrates the machine learning lifecycle across hybrid-cloud, multi-cloud, and on-premises environments. The platform provides experiment tracking, dataset management, pipeline automation, model lineage and reproducibility, distributed training, and LLM-specific workflows (context pipelines, model comparison, regression testing, cost analysis) as a subscription SaaS product.
Product overview
Valohai is an enterprise MLOps and LLMOps platform that provides CI/CD for machine learning, offering a comprehensive suite of tools for the full ML lifecycle. The platform centers on the Valohai MLOps Platform as its core product, which includes LLM Workflows for managing large language model operations (model comparison, context pipelines, regression testing, cost analysis), Model Workflows for dataset management, compute scaling, experiment iteration, and pipeline automation, Multi-Cloud Orchestration for running workloads across any cloud or on-premises, and Lineage and Reproducibility for automatic versioning and full traceability. Key features include Agent Skills for AI-powered migration, an Operations Dashboard for unified visibility, Model Hub for centralized model management, Dynamic GPU Allocation for optimized resource utilization, Smart Instance Selection for intelligent compute selection, Pipeline Caching and Dataset Packaging for performance optimization, On-Demand Inputs for flexible data access, LLM Evaluations for comprehensive model assessment, Webhooks and Notifications for workflow automation, and Distributed Training support. The platform is complemented by Valohai Academy, an educational service offering free courses and certifications. Together, these products enable enterprises to automate ML workflows, scale operations across hybrid environments, and maintain complete reproducibility from experimentation to production.
Differentiator
Problem solved
Functional benefit
Products and services
- LLM Workflows Productized module of the Valohai platform providing LLM operations capabilities: model comparison across multiple providers, context pipelines, regression testing, and cost-per-token analysis. Designed for teams building LLM-powered applications that require systematic evaluation and quality control.
- Model Workflows Productized module of the Valohai platform covering the full traditional machine learning lifecycle: dataset management, compute and scaling, experiment iteration, pipelines and automation, debugging and visibility, and API and extensibility. Designed for data science teams building and deploying production ML models.
- Multi-Cloud Orchestration Productized module of the Valohai platform providing infrastructure flexibility to run ML workloads on any cloud, any region, or on-premises hardware simultaneously with consistent workflow management. Includes multi-cloud orchestration, support for clouds without a platform, on-prem and hybrid deployment, GPU efficiency, and dataset caching.
- Lineage and Reproducibility Productized module of the Valohai platform providing automatic versioning and full lineage tracking from data through execution to deployed model, with one-click reproduction, audit and compliance support, and team collaboration.
- Valohai MLOps Platform The overarching enterprise MLOps and LLMOps platform that provides CI/CD for machine learning, full traceability, reproducibility, and pipeline automation across hybrid-cloud, multi-cloud, and on-premises environments. The core subscription product sold to enterprise and mid-market ML teams.
- LLM Evaluations Standalone evaluation product for LLM-powered applications, providing multi-model comparison, RAG evaluation, systematic sweeps across chunk sizes, embedding models, and retrieval strategies, and Langfuse integration for deep tracing of prompt chains, token counts, and latency.
- Valohai Academy Free educational service offering the Applied LLM Certification course (6 modules) and Valohai MLOps Course, providing structured upskilling on MLOps and LLM operations.
Quantifiable outcome
- Doubled biomarker pipeline speed and halved training costs for Onc.AI on the Valohai-OCI platform
- +4 more outcomes
Companies that use Valohai
Customer profileNamed customers14 records
Segments4 records
Ideal customer profiles3 records
Valohai technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration9 records
AI capability10 records
Feature13 records
Valohai partnerships and signals
Strategic signalPartnerships
Seven partnerships are on record, tiered core.
- OraclecoreValohai launched its enterprise MLOps platform on the Oracle Cloud Marketplace, offering organizations a combined solution for automating and versioning the ML lifecycle with Oracle Cloud Infrastructure (OCI). This marketplace listing provides joint enterprise GTM for Valohai within Oracle's customer base. Customer Onc.AI demonstrated real-world success with the combined platform.
- AWS (Amazon Web Services)coreAWS is listed as a cloud infrastructure partner on Valohai's Partners page. Valohai runs its own application on AWS and supports customers running ML workloads on AWS infrastructure. AWS is part of the multi-cloud orchestration ecosystem.
- Microsoft AzurecoreMicrosoft Azure is listed as a cloud infrastructure partner. Valohai supports ML workloads on Azure, including customers like Preligens who use Azure as one of multiple cloud providers in their hybrid setup.
- NVIDIAcoreNVIDIA is listed as a partner with Valohai having published integrations supercharging NVIDIA NeMo (Speech AI) and NVIDIA MONAI (Medical Imaging AI). These integrations enable optimized distributed training and inference on NVIDIA GPU infrastructure.
- OVHcloudcoreValohai announced a partnership with OVHcloud to solve GPU shortage and control cloud costs. The integration allows Valohai users to leverage OVHcloud's scalable GPU instances directly from the Valohai platform. Both companies support principles of reversibility to prevent vendor lock-in. The partnership emphasizes GPU availability, cost management, security, and sustainability.
- Hugging FacecoreValohai introduced a Hugging Face integration giving teams immediate access to the Hugging Face model library. Users can fine-tune Transformers and run batch inference directly from Valohai without writing custom code, streamlining experimentation across thousands of pre-trained models.
- OVHcloudcoreOVHcloud partnership announced publicly on the Valohai blog in August 2024, emphasizing joint go-to-market for GPU shortage solutions and cloud cost control. Both companies position against vendor lock-in and offer competitive pricing models.
Scale indicators3 records
Recent moves6 records
Expansion highlights6 records
Valohai competitors and assessment
Company assessmentDirect peers
- Neptune.ai: Experiment tracking and model registry platform for ML teams. Comparable to Valohai's experiment tracking, lineage, and metadata management capabilities, particularly for research-heavy and production ML use cases.
- Weights & Biases: Direct competitor offering experiment tracking, model management, and MLOps tooling for ML teams. Closely comparable to Valohai on target buyer (enterprise ML teams) and core capabilities (experiment tracking, model registry, sweeps), with a stronger LLM-focused narrative.
- ZenML: Open-source MLOps platform focused on pipeline orchestration and reproducibility, explicitly benchmarked alongside Valohai in 2025 LLMOps comparisons. Overlaps on pipeline definition, lineage, and cloud-agnostic execution.
- ClearML: Open-source MLOps suite covering orchestration, experiment tracking, and data management. Comparable to Valohai on self-hosted, cloud-agnostic deployment and enterprise ML lifecycle automation.
- MLflow: Open-source MLOps platform from Databricks covering experiment tracking, model registry, and deployment. Listed in Valohai's own competitive context as part of the 'DIY ML stack' (MLflow + Airflow + Kubernetes) that Valohai replaces.
- Comet: Direct competitor providing experiment tracking, model production monitoring, and LLM evaluation. Comparable in customer base (data science and ML engineering teams) and overlap with Valohai's LLM Workflows module.
- TrueFoundry: Kubernetes-native MLOps and LLMOps platform serving enterprise ML teams. Listed alongside Valohai in 2025 LLMOps market comparisons, with comparable focus on production deployment and GPU efficiency.
Broad incumbents
- Google Vertex AI: Google Cloud's unified MLOps and LLMOps platform with strong GenAI capabilities. Hyperscaler incumbent that Valohai positions against with its cloud-agnostic, multi-cloud orchestration story.
- Azure Machine Learning: Microsoft's enterprise MLOps platform integrated with Azure cloud and the broader Microsoft Fabric data stack. Competes for the same enterprise ML teams that Valohai serves (e.g., Preligens).
- Amazon SageMaker: AWS's flagship ML platform offering end-to-end MLOps capabilities tightly integrated with the AWS ecosystem. Represents the hyperscaler bundled alternative to Valohai's cloud-agnostic platform.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks5 records
Key highlights8 records
Customer concentration
Valohai social profiles
Digital presenceValohai compliance and trust
Trust signalCompliance3 records
Valohai financial estimates
Financial estimateRevenue estimate
Valuation estimate
Valohai leadership team
Management profileNumber of profiles
Profiles14 records
Valohai funding detail
Funding detailFunding overview
Funding rounds2 records
Investors4 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Valohai M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Valohai
What does Valohai do?
Valohai sells an enterprise MLOps and LLMOps platform that automates, versions, and orchestrates the machine learning lifecycle across hybrid-cloud, multi-cloud, and on-premises environments. The platform provides experiment tracking, dataset management, pipeline automation, model lineage and reproducibility, distributed training, and LLM-specific workflows (context pipelines, model comparison, regression testing, cost analysis) as a subscription SaaS product.
Is Valohai a public or private company?
Valohai is a private company. It is classified as founder individual operated bootstrapped and is currently operating.
When was Valohai founded?
Valohai was founded in 2016. It employs 11 to 50 people.
Where is Valohai based?
Valohai is headquartered in Turku, Finland, in the Europe region.
How does Valohai make money?
One revenue line is on record: platform SaaS Subscription.
Who are Valohai's main competitors?
Direct peers on record are Neptune.ai, Weights & Biases, ZenML, ClearML, MLflow, Comet and TrueFoundry. Broad incumbents are Google Vertex AI, Azure Machine Learning and Amazon SageMaker.
Does Valohai have an API?
Yes. Valohai provides an API-first architecture that allows full access to the platform's suite of features through the API, CLI, and Web UI. Any new features added to the platform are available through all three interfaces. The platform syncs files with cloud storage, versions every run, and enables programmatic access for automation. Developer documentation is at docs.valohai.com.
What industry is Valohai in?
Valohai's product category is MLOps Platform. Its primary akta.pro industry code is HDAAABAA, End-to-End MLOps & ML Platform Suites, with a secondary code of HDAEANAD, LLMOps & Generative AI Platforms (Prompt/Agent Orchestration, RAG). Its NAICS code is 5415 and its SIC code is 7373.