What is forward-deployed engineering?
Forward-deployed engineering (FDE) means working directly with a business and its staff to solve real operational problems. A forward-deployed engineer learns the workflow, builds the solution, connects it to existing systems, and helps the people using it put it to work.
For AI projects, that means understanding the models, the business data, and the software around them. It also means working with leadership on priorities and with employees on what will make their jobs more productive.
What our AI engineers can implement
- Invoice processing: extract information from incoming documents and pass it into accounting workflows, with review where it is needed.
- Customer support: connect AI to your knowledge base and support systems so it can answer recurring questions and route cases to the right people.
- Sales and marketing: follow up with leads, keep records current, and launch campaigns through the tools your team already uses.
- Physical automation: integrate scanners, sensors, and device controls when a workflow involves equipment as well as software.
The starting point is your business problem. The model, tool, or custom software comes after we understand what needs to change.
From a business problem to a working system
- Learn the operation. Map the task with the people doing it. Find the repeated work, delays, handoffs, and missed opportunities.
- Test on real examples. Use representative inputs and check whether the approach produces useful results before expanding the project.
- Build and integrate. Connect the solution to the systems, data, and hardware the workflow depends on. Plan access, review, and exception handling around the actual work.
- Train and hand over. Technical staff learn to understand, monitor, and maintain the integration. Other staff learn to use it productively and give feedback.
- Improve what matters. Review costs, output, revenue opportunities, and feedback from the people using the system. Keep improving the parts that make a difference.
When do you need an FDE?
A ready-made AI feature can be enough for a standard task. Forward-deployed AI engineering becomes useful when the work crosses several systems, depends on your own data, includes physical devices, or needs changes to how people work.
For example, reading an invoice is one step. Matching it to a purchase order, handling exceptions, requesting approval, and updating the accounting system is an operational workflow. We help connect the whole process.
How do you choose the best forward-deployed engineer for AI?
Look for someone who can understand your business and deliver a working integration in your actual workflow. Ask how they will test with your data, work with your existing engineers, handle the handoff, and establish whether the result is useful.
Our guide to choosing an AI consultant gives you practical questions to ask before starting a project.