Faros AI is a powerful engineering intelligence platform built for organizations that want highly customizable metrics and deep integration with their existing data stack. It's a compelling choice for companies with a dedicated data engineering team who need to build bespoke analytics on top of engineering data.
But for most engineering teams, the complexity and cost of Faros AI are barriers, not benefits. Velocinator takes the opposite approach: deliver the right insights out of the box, with AI that works immediately.
What Is Faros AI?
Faros AI is an "EngOps" platform that positions itself around customizability and using AI to reveal hidden causes behind engineering performance metrics. It connects to 20+ tools including GitHub, GitLab, Jira, Jenkins, AWS CodeDeploy, and Azure Pipelines, and offers open-source Community Edition components.
Faros AI's Lighthouse AI layer uses statistical analysis, machine learning, and GenAI to surface insights. It's particularly strong for organizations that want to build custom dashboards and define their own engineering KPIs.
Where Faros AI Falls Short
Slow Dashboards. A consistent complaint from Faros AI users is dashboard load times. When you're trying to quickly check team status or run a sprint retrospective, long dashboard load times create friction and reduce the platform's daily utility.
Steep Learning Curve. Faros AI's power comes with a corresponding learning curve. New users frequently describe the onboarding experience as steeper than expected. Getting comfortable with the platform's data models and customization capabilities takes time.
Setup Investment for Custom Builds. Faros AI's flexibility is most valuable for teams with complex or non-standard data sources. For teams with "messy data or homegrown tools," users report feeling the limitation of the platform's out-of-the-box connectors.
Limited Alerting. Users have specifically called out the need for better automated alert notifications and subscription options for dashboards. This means teams have to proactively check the platform rather than getting notified when something important changes.
Price. At $29+ per contributor per month, Faros AI is nearly 3x the cost of Velocinator for comparable base functionality.
Velocinator vs Faros AI: Feature Comparison
| Feature | Velocinator | Faros AI |
|---|---|---|
| DORA Metrics (automated) | ✅ Out of the box | ✅ |
| PR Analytics | ✅ | ✅ |
| AI Team Performance Insights | ✅ Automated recommendations | ✅ (Lighthouse AI) |
| Release Summaries (AI-generated) | ✅ Per deployment | ⚠️ Requires custom config |
| Developer 360 View | ✅ Per-contributor profiles | ⚠️ Custom setup |
| Team Comparison | ✅ | ✅ |
| Work Log AI Highlights | ✅ | ⚠️ Custom |
| Custom Metric Building | ❌ (opinionated defaults) | ✅ (Faros' core strength) |
| Open-Source Connectors | ❌ | ✅ |
| Dashboard Load Speed | ✅ Fast | ⚠️ Reported slow |
| Setup Time to First Insight | ✅ Minutes | ⚠️ Weeks for full config |
| Alerting / Notifications | ✅ AI-driven alerts | ⚠️ Limited |
| Free Trial | ✅ 14 days, no credit card | ⚠️ Community Edition |
| Price | $10/active member/month | $29+/contributor/month |
Pricing Comparison
For a team of 30 engineers:
- Faros AI: $870+/month
- Velocinator: $300/month
That's a 65% cost reduction — and Velocinator starts delivering value from day one without a setup sprint.
Two Different Philosophies
Faros AI and Velocinator take fundamentally different approaches:
Faros AI is a platform for teams that want to build their own engineering intelligence. If you have a data engineering team, complex multi-tool data pipelines, and a desire to define custom metrics, Faros AI gives you the building blocks to do that.
Velocinator is for teams that want the insights now, not after a three-month implementation. It's opinionated about what matters — DORA metrics, PR analytics, AI insights, Developer 360, release summaries — and delivers those things out of the box, beautifully and immediately.
What Velocinator Delivers Out of the Box
AI Insights Without the Engineering Effort
Velocinator's AI layer automatically analyzes your team's performance data and surfaces recommendations — no custom model building required. Connect GitHub and Jira, and your first AI-powered insight appears in minutes.
This is the key difference from Faros AI: Velocinator makes the AI work for you immediately, without requiring you to become an EngOps engineer.
Release Summaries for Every Deployment
Every deployment automatically generates an AI-written summary covering contributors, linked PRs, and what shipped. No custom pipeline needed — this works out of the box from your GitHub integration.
Fast Dashboards That Load Immediately
Velocinator is built for daily use. Dashboards load immediately, and navigation is designed for engineering managers who need quick answers, not data analysts building custom queries.
Proactive Alerts When Metrics Drift
When your DORA metrics trend in the wrong direction or PR cycle time spikes, Velocinator surfaces the alert automatically — you don't have to check dashboards. This is a core design principle that Faros AI users have specifically requested but not yet received.
The Bottom Line
Faros AI is a powerful platform for organizations with the resources and team to build custom engineering intelligence. If that's not you — if you want clear, AI-powered insights from a connected GitHub and Jira in minutes, not months — Velocinator is the better choice.
$10 per active member per month. 14-day free trial. No data engineering team required.
Start your free trial and see your first AI insight in under an hour.
Frequently Asked Questions
- Is Velocinator cheaper than Faros AI?
- Yes. Faros AI starts at $29 per contributor per month. Velocinator costs $10 per active contributor per month — about 65% less. Velocinator also starts delivering value immediately without requiring a data engineering investment.
- Does Velocinator offer the same customization as Faros AI?
- Faros AI is designed for high customization with open-source connectors and custom metric building — ideal for organizations with dedicated data engineering teams. Velocinator takes an opinionated approach: it delivers the right metrics out of the box without requiring custom configuration, making it faster to value for most engineering teams.
- How quickly can I get insights from Velocinator vs Faros AI?
- Velocinator is designed to deliver meaningful insights within minutes of connecting your GitHub and Jira accounts — no data pipeline setup required. Faros AI's customization capabilities come with a corresponding setup investment that can take weeks to fully realize.
