AI Automation & Workflows

Design, run, and scale automated AI workflows across models, tools, and data sources - with reliable orchestration and production infrastructure.

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Fragmented AI Tools Break Automation at Scale

Disconnected models, scripts, and services make AI workflows brittle, slow to ship, and hard to monitor in production.

Workflow logic lives in scattered scripts

AI workflows are often stitched together using notebooks, cron jobs, and custom glue code. This makes pipelines fragile, hard to standardize and maintain.

Model switching and scaling is manual

Teams must manually switch between models as cost, latency, and workload needs change. Without automated routing and scaling, workflows become inefficient and harder to optimize.

No visibility into AI task performance

Many AI workflows lack tracing, logs, and version control. When failures or quality drops occur, teams struggle to debug quickly and ensure reliable outputs.

Keep AI Workflows Reliable, Observable & Scalable

Multi-Step AI Pipelines

Build multi-step AI pipelines that connect models, tools, & APIs into structured, repeatable workflows.

Model Routing & Fallbacks

Route traffic to the right model based on cost, speed, or quality. With automatic fallback handling.

Event-Driven Automation

Trigger AI workflows from API calls, file uploads, queues, or schedules to automate tasks at the right time.

Batch + Real-Time Runs

Support both large batch jobs & real-time AI inferences using a single scalable workflow infrastructure.

Workflow Observability

Monitor runs with logs and step traces so teams can debug faster and maintain reliable AI outputs.

Reusable Workflow Blocks

Create reusable workflow components that can be shared, versioned, and deployed across multiple projects.

Recommended Models for Automation & Workflows

Production-ready models optimized for automated pipelines, task chaining, and tool-driven workflows.

GPT-OSS 20B

Welcome to the gpt-oss series, OpenAI's open-weight models designed for powerful reasoning, agentic tasks, and versatile developer use cases. gpt-oss-20b is a 21.5B parameter model with Mixture-of-Experts (MoE) architecture, featuring 3.6B active parameters during inference. It's optimized for lower latency and local or specialized use-cases, supporting configurable reasoning depth for agentic applications.

GPT-OSS 120B

Introducing gpt-oss-120B, OpenAI's flagship open-weight model in the gpt-oss series, built for advanced reasoning, large-scale agentic workloads, and enterprise-grade automation. With 120B parameters and a highly optimized Mixture-of-Experts (MoE) architecture, it activates 12B parameters during inference, delivering exceptional intelligence while maintaining competitive latency. Designed for complex reasoning, multi-task agents, and long-horizon planning, gpt-oss-120B brings frontier-level capability to commercial and self-hosted deployments.

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Take Control of Your AI Workflows - Build, Automate, and Scale with us

Building multi-step AI pipelines or model-driven automations? Deploy reliable, observable workflows on secured infrastructure.

Deploy AI Workflows

"Qubrid helped us turn a collection of AI scripts into structured production workflows. We now have better reliability, visibility, and control over every run."

AI Infrastructure Team

Automation & Orchestration