Engineers who embed, then ship AI that runs.
Our forward deployed engineers join your team, find the workflow costing you most, and build the AI that runs it, inside your systems.
How an FDE engagement runs.
Embed
In your tools, data, and standups from day one.
Find
The workflow eating the most hours, plus a firm quote.
Engineer
Agent, loop, and harness, built against live systems.
Operate
We run it, tune it, and train your team to own it.
What our FDEs found, and fixed.
Found: monthly client reports built by hand in a portal with no API.
Found: the real blocker was the data feed, not the matching logic.
Built: per-task model routing, so models swap in config, not code.
Nine industries, every one delivered forward deployed. See all deployments →
Your FDE options, side by side.
| Quantilus FDE | AI-lab FDE teams | Traditional consultancy | Hire in-house | |
|---|---|---|---|---|
| Model | Any, chosen after we see your data | The lab's own model | Often a partner platform | Whatever your hires know |
| Who builds | Senior engineers in your systems | Lab engineers | Strategy team, then a build team | You recruit and manage |
| Sized for | Mid-market and enterprise | Mostly large enterprise | Large programs | Teams with time to hire |
| After launch | We operate it, or hand it off | Varies | Usually a new contract | Your team carries it |
FDE questions, answered.
What is a forward deployed engineer (FDE)?
A software engineer who works embedded inside a customer's team and systems, building production software against real data instead of handing over a spec. Palantir popularized the role; OpenAI and Anthropic now run FDE teams for AI. Read the explainer.
What do forward deployed engineering services include?
Embedding, finding the costly workflow, building the agent and its production harness, integrating with your CRM, ERP, and document systems, and operating it after launch.
How is FDE different from consulting or staff augmentation?
Consultants advise. Staff augmentation adds hands you manage. A forward deployed team owns the outcome: it finds the problem, ships the fix to production, and runs it.
Do you provide FDEs for mid-market companies?
Yes. We work with companies of roughly 20 to 2,000 employees as well as large enterprises, including teams with no in-house AI group.
Remote or on-site?
Both. We are headquartered in New York with delivery teams across the US and Asia. Engineers live in your tools every day and come on-site when it matters.
How does an engagement start, and what does it cost?
With a fixed-scope Strategy & Discovery Sprint of 4 to 8 weeks. It ends with the target workflow, a build plan, and a firm quote. How we engage.
Which AI models do your FDEs use?
Whatever fits: Claude via AWS Bedrock, GPT via Azure OpenAI, Gemini via Vertex AI, or open-weight models in your own VPC. Private deployment options.