# Aviator

## About

AI-powered development platform with repeatable AI workflows for code migrations, intelligent merge queues, automated code review, and deployment management. Ship faster with AI agents.

- Customers: 100
- Verified: Yes

## Services

### DevOps & Continuous Delivery
- [DevOps & Continuous Delivery](https://bilarna.com/ai/devops-and-continuous-delivery/devops-and-continuous-delivery)

### Software Development & Automation
- [Software Development & Automation](https://bilarna.com/services/software-development-and-automation/software-development-and-automation)

## Pricing

- Model: freemium

## Trust & Credentials

### Certifications
- SOC2 (SOC2)
### Compliance
- SOC2
### Data Security
- SOC2

## Frequently Asked Questions

**Q: What are the benefits of using an AI-powered development platform for software delivery?**
A: An AI-powered development platform streamlines software delivery by automating repetitive tasks such as code migrations, merge queue management, code reviews, and deployment processes. This automation reduces manual overhead, minimizes errors, and accelerates release cycles. Developers benefit from fewer interruptions and less time spent managing pull requests, enabling faster and more reliable software releases. Additionally, AI workflows can proactively detect issues before they affect the main codebase, preventing outages and improving overall software quality. Such platforms are especially valuable for large teams working in complex environments like monorepos, where managing simultaneous contributions can be challenging.

**Q: How does automated merge queue management improve development workflows?**
A: Automated merge queue management helps development teams by organizing and sequencing pull requests to be merged in a controlled and efficient manner. This reduces conflicts and build failures caused by simultaneous merges, which can disrupt the main branch stability. By automating the merge process, developers no longer need to manually monitor and coordinate merges, freeing up time and reducing frustration. It also enables faster integration of changes, allowing teams to maintain a continuous flow of updates without bottlenecks. This approach is particularly beneficial for large teams working in shared repositories where many engineers contribute concurrently, ensuring smoother collaboration and higher code quality.

**Q: Why is automation important in managing pull requests and deployments in large engineering teams?**
A: Automation is crucial for managing pull requests and deployments in large engineering teams because it reduces manual workload and the risk of human error. Large teams often face challenges like blocked pull requests, merge conflicts, and deployment delays due to the volume and complexity of contributions. Automating these processes ensures that pull requests are handled efficiently, rebases and merges happen seamlessly, and deployments occur reliably without constant manual intervention. This leads to faster release cycles, less developer frustration, and more stable main branches. Automation also enables teams to 'set and forget' workflows, allowing engineers to focus on coding rather than administrative tasks, which improves productivity and software quality.

## Links

- Profile: https://bilarna.com/provider/aviator
- Structured data: https://bilarna.com/provider/aviator/agent.json
- API schema: https://bilarna.com/provider/aviator/openapi.yaml