Description
Valohai is an advanced MLOps platform tailored for AI products that combine large language models (LLMs) with specialized models. It allows users to compare, evaluate, and ship configurations based on real data within their own cloud environments, ensuring complete lineage from data to deployment.
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The platform recognizes that while calling the LLM is straightforward, the complexities of deploying AI products require robust infrastructure. Specialized models perform critical tasks such as classifying support tickets, detecting anomalies, and predicting customer churn, all while working in tandem with LLMs to deliver precise results tailored to specific domains.
As AI products evolve, the number of models in use can quickly exceed expectations, necessitating effective management and evaluation. Valohai simplifies this process, enabling software engineers to build and deploy models without needing dedicated ML engineers. This democratization of model training leads to increased features and use cases, but also requires ongoing management as models need retraining and data drifts over time.
Valohai's platform provides a comprehensive solution for tracking costs and quality, ensuring that users can manage their cloud expenses and maintain high standards of model performance. The platform supports a variety of workflows, allowing users to define their processes through connected steps, implement conditional logic, and execute tasks in parallel.
With features like human-in-the-loop approvals, versioned datasets, and smart caching, Valohai enhances collaboration and transparency among teams. The platform also offers deep tracing capabilities, allowing users to track model lineage and understand the data that informs their models. This traceability is crucial for maintaining quality and compliance in AI applications.
Valohai's operations dashboard consolidates various metrics, providing insights into costs, performance, and resource utilization. This holistic view helps teams identify bottlenecks and optimize their workflows effectively. The platform is designed to run on any cloud or on-premises infrastructure, ensuring that users retain control over their data and compute resources. Overall, Valohai empowers teams to build AI products that remain accurate and efficient, with a focus on continuous improvement and adaptability.
- CategoryMLOps & Model Deployment
- Pricing ModelFreemium
- DeploymentCloud and On-Premises
- PlatformsWeb
Valohai's Core Features
Versioned datasets
Human-in-the-loop approvals
Parallel execution
Conditional logic & quality gates
Deep tracing with Langfuse
Operations dashboard
Model registry
Experiment tracking
How to use Valohai?
Define your workflow: create a pipeline that outlines your model training and evaluation steps.
Integrate your data: upload datasets and configure them for versioning and caching.
Run experiments: execute your pipeline and monitor results in real-time.
Evaluate models: compare performance metrics across different configurations.
Valohai's Use Cases
- Support Ticket Classification
- Anomaly Detection
- Churn Prediction
- Model Evaluation
- Data Versioning
