Most enterprise AI procurement follows a familiar script: sign the contract, get credentials, attend a webinar, then figure out the rest on your own. SaaS onboarding works for email tools and project management software. But it doesn't work when your data can't leave the network, your workflows have no off-the-shelf equivalent, and the gap between "installed" and "useful" is measured in months.
Forward deployed engineering is a different model. The AI vendor sends engineers to work alongside your team—on your infrastructure, with your data, inside your security perimeter. They don't hand you a login. They sit next to your people and build with them.
How Forward Deployed Engineering Differs from SaaS Onboarding
| SaaS入门 | 前置部署 | |
|---|---|---|
| Data location | Data moves to the vendor's cloud | The vendor works on your infrastructure |
| Customization | Configuration within product limits | Built for your workflows |
| Knowledge transfer | Documentation and support tickets | Engineers working alongside your team |
| Security model | Trust the vendor's cloud | Data never leaves your control |
Why It Works for Enterprise AI
Enterprise AI projects fail at the data stage, not the model stage. Forward deployed engineering addresses this directly:
Engineers see the real data. Not sanitized samples. The actual data, with all its inconsistencies, gaps, and formatting issues.
Domain experts stay involved. When the vendor's engineers sit next to your team, domain experts can answer questions in real time.
Security is built in from the start. No "wait, can we send this data to their servers?" moment.
The output actually works in production. Because the pipeline is built on your infrastructure with your data, there's no translation step between "demo" and "deployment."
Typical Engagement Structure
Week 1: Discovery and data audit Weeks 2-3: Pipeline building Week 4: Validation and handover
How Ertas Does Forward Deployed Engineering
At Ertas, forward deployed engineering is how we deliver enterprise data preparation. Our engineers embed with your team to build AI-ready data pipelines on your infrastructure. We work with your data, in your environment, under your security policies.
If you're evaluating AI data preparation options and want to find out whether forward deployed engineering is right for your organization, book a discovery call.