Frontier vs. Coworker
A side-by-side comparison based on G2 review data.
| Metric | Frontier | Coworker |
|---|---|---|
| Overall rating | 4.3 | 4.8 |
| Review count | 64 | 12 |
| Ease of use | 9.2 | 9.4 |
| Ease of setup | 9.1 | 8.7 |
| Quality of support | 9.0 | 9.2 |
| Meets requirements | 9.0 | 9.2 |
| NPS | 50.793651 | 91.666667 |
| Small Business | 62.5% | 25.0% |
| Mid-Market | 21.9% | 75.0% |
| Enterprise | 15.6% | 0.0% |
| Total page views | 566 | 413 |
| Total LLM citations | 133 | 231 |
Frontier
Frontier is a new enterprise AI platform from OpenAI for building, deploying, and managing autonomous AI agents across a company’s tech stack. It’s basically a centralized place to run “AI coworkers” that can interact with real systems and workloads, not just chat.
Coworker
Coworker is an enterprise AI platform that routes each task to the right model with the right context. Teams get frontier-quality outputs at about 82% lower cost per task, and run roughly 5x more inference per dollar than they would on direct Claude or OpenAI consumption. Overview. Coworker is built for companies whose AI usage is growing faster than their AI budget. As frontier model adoption has scaled, customers face a tradeoff between slowing down adoption and cutting headcount to control spend. Coworker takes a different approach.