FDE is a forward deployed engineering team. We embed inside your company, take one real AI workflow from prototype to production in six weeks, and hand the code, the evals, and the runbook back to your team. Fixed fee. Your repo. Your IP.
01/The Problem
The models are not the problem. The gap between a vendor demo and your production environment is. Messy data, undocumented APIs, missing ontologies, compliance friction, and a 58 day hiring cycle for ML engineers. Pilots stall, budgets evaporate, and the board asks why.
of companies struggle to achieve and scale value from AI.
Source: BCG, 2024
of GenAI deployments fail to meet the ROI leadership expected.
Source: NTT DATA
of corporate AI initiatives fail. Leadership and integration are the most cited reasons.
Source: Fortune, 2024
is the average time to a first PR via an in house ML hire. Then six to twelve weeks to ramp.
Source: Hiring market
02/The Model
A forward deployed engineer embeds inside your organization. Your repo, your standups, your Slack. They ship production code. Palantir invented the role in 2003 to deploy Gotham inside the CIA. Today OpenAI, Anthropic, and Databricks all run forward deployed teams. FDE productizes that model for companies that cannot justify hiring it in house at $300k to $600k in total comp.
Read the full guide on what a forward deployed engineer is| Capability | FDE Agency | Consultant | Staff Aug | Solutions Engineer |
|---|---|---|---|---|
| Primary output | Production code in your repo | Decks and recommendations | Billable hours | Demo, pre deal only |
| Outcome ownership | Outcome accountable | Advisory | Time based | Pre sales |
| Time to first PR | 7 days | N/A | Weeks | N/A |
| IP ownership | 100% client | Vendor | Mixed | N/A |
| Feedback loop | Direct to product | Report, then forgotten | None | CRM note |
| Typical duration | 6 weeks per embed | Project based | Open ended | 0 to 3 months |
03/Services
Fixed scope · Fixed fee · Your IP
Know what to build before you spend six figures finding out.
A two week embedded discovery. We map your data, interview the people who will actually use the system, and hand back a production architecture with a prioritized list of use cases.
One workflow. In production. In six weeks.
A full build of a single AI workflow such as a RAG pipeline, document processing, copilot, or agentic automation. Working prototype by week two, production by week six.
An agent that does a real job, not a chatbot.
Multi step autonomous agents with tool use, retrieval, guardrails, and human in the loop review. Deployed on your cloud. The IP is yours from day one.
A senior engineer inside your repo, every month.
A named forward deployed engineer on a quarterly basis. Standups, architecture, continuous deployment, monthly roadmap reviews with your team.
Connect your AI to Salesforce, SAP, and Snowflake in four weeks.
Production grade integrations between an existing AI capability and the systems your business actually runs on. PII safe by design.
AI that clears legal, compliance, and security before it ships.
End to end engagement for HIPAA, SOC 2, SOX, attorney privilege, and FedRAMP. Includes compliance architecture, audit trail, and VPC isolated or on prem deployment.
04/Process
One production outcome. A milestone rubric. Access provisioning.
GitHub, CI/CD, Slack, standups. First PR inside seven days.
A working prototype on your stack, against your data, behind a feature flag.
Production integration. Eval harness. Review queue. Compliance wiring.
Running on real traffic. Audit trail live. SLAs met.
Runbook, eval suite, CI/CD in your repo. Team trained. IP fully yours.
05/What we build
06/Who we work with
Series A to C AI companies winning enterprise deals
Banks, asset managers, insurers under SOC 2 and SOX
Health systems and payers building HIPAA compliant AI
Law firms, contract review, privilege aware systems
Workflow automation across legacy systems of record
07/Pricing
No hourly billing. No open ended retainers. Every engagement has a fixed scope, a milestone rubric, and a price band published below. The same numbers we would quote on a sales call.
AI Readiness Sprint, two weeks
Fixed fee six week production build
Embedded engineer, quarterly minimum
Regulated industry deployment
Minimum engagement: $8,000 USD · IP transfer included
08/FAQ
A forward deployed engineer is a senior software engineer who embeds inside your organization. Your repo, your standups, your Slack. They ship production code. Palantir invented the role in 2003 to deploy Gotham inside the CIA and NSA. OpenAI, Anthropic, Databricks, and Cohere have all adopted the model. FDE brings it to companies that cannot justify a $300k to $600k in house hire.
A consultant delivers a deck and leaves. A forward deployed engineer has commit rights on your stack and is accountable for a production outcome. Different deliverable, different incentive, different hiring bar.
You do. 100 percent. The code lives in your repo from day one. We sign IP transfer in writing before week one starts. No vendor lock in, no platform tax.
Two weeks from signed SOW to first PR is typical. We hold a small number of slots open each quarter to make that possible.
$8,000 for the AI Readiness Sprint over two weeks, or $25,000 for a Production Workflow Build over six weeks. No hourly billing, and no open ended retainers below a quarterly commitment.
Yes. Healthcare under HIPAA, financial services under SOC 2 and SOX, legal work that must respect privilege, and federal work that needs to be FedRAMP ready. Our Regulated Industry Deployment ships with a compliance architecture document and a security review package.
Whatever you use. We have shipped on AWS Bedrock, Azure OpenAI, GCP Vertex, and on prem. Models from OpenAI, Anthropic, and open weights such as Llama, Mistral, and Qwen. Orchestration with LangGraph, Pydantic AI, or custom code. We meet your stack rather than importing ours.
Remote first, with onsite as the engagement requires it. For regulated work that demands it, we operate inside your security perimeter.
A 15 minute scoping call is enough to know if we are a fit. We take on three new engagements per quarter.