GIIP FDE Proposal | AI Development Team as a Service

Before → After

Your “use of AI” — isn't it still on the left side of this picture?

Most teams ask AI directly and ship the single output as-is. GIIP FDE turns that same request into a real, running production service.

NOW (BEFORE)

Ask the AI directly — and that's it

You ask Claude directly and get a single HTML page. Fast, but with no infrastructure, security, data, deployment, operations, or continuity. It demos, but it can't serve real customers — because the service infrastructure isn't there.

GIIP FDE (AFTER)

Just “talk” in Slack — and a real service comes out

We build real production infrastructure — End User → CDN → Firewall → Web → DB → Backup — with GitHub source control, a Slack+Claude operations channel, and FDE oversight. Customers simply say what they need in Slack, like briefing an outsourced dev team.

This is the “technology” we sell

“Leave one line in Slack, like handing it to an outsourced dev team — and the AI FDE behind it designs, builds, deploys, and operates it end to end.”

You don't need to know servers, networks, deployment, or security. Ask in plain words for the service you want, and FDE delivers a result that actually runs.

Talk to FDE Ops See the 90-day roadmap

Problem

AI projects fail because execution teams are missing, not because models are weak.

Most companies already have models and cloud. What you want is not a good AI model, but an AI assistant that properly performs your tasks. What they lack is a team that can wire AI into real workflows and run it under production constraints.

AI Talent Shortage

Hard to hire AI Architect, Agent Engineer, MLOps, and Fine-Tuning talent at once.

Stall After PoC

Demos work, but permission, data flow, and operations block production rollout.

Business Language Gap

AI does not naturally understand company-specific instructions and terminology.

AX Hiring Risk

Hiring AX talent without AX expertise is a blind, high-stakes bet.

AX capability is not a resume keyword game. It is proven only by end-to-end execution across prompt systems, agent workflows, data governance, operational automation, and quality control.

Risk 1: Non-experts cannot identify real AX performers

"I know AI" in an interview is not production execution. One bad hire can cost quarters in delays, architecture rewrites, and expanded security/data exposure.

Risk 2: Capability gap and pay reality are brutal

Top AX talent can deliver x20 to x100 productivity over general engineering roles. You will not secure that level with standard compensation assumptions, and hiring without AX expert screening is reckless.

Solution

GIIP does not deliver a tool. We activate your AI engineering force.

FDE is not advisory overhead. It is an execution unit that converts requirements into code, agent workflows, and production operations inside your environment.

Capability

AI Architect, Agent Engineer, Fine-Tuning Engineer, Data/RAG Engineer, MLOps Engineer, Infra Engineer as one squad.

Differentiation

Users do not learn AI. AI learns the customer organization.

Fine-tuning is not only about model scores. It captures customer instructions, review style, incident handling, and reporting norms.

Typical Adoption

Users adapt their process to AI.

GIIP FDE

AI adapts to the customer's real process.

Execution Plan

90-day roadmap to activate an AI engineering team

Not a long consulting report. We deliver concrete outcomes every 30 days.

Day 30

AI work map, data integration, first agent, success criteria.

Day 60

Production pilot with permissions, logs, evaluation, and operations process.

Day 90

Scale to multiple departments and institutionalize internal operation.

Stop burning quarters on hiring.
Deploy an AI engineering team
right now.

📦 Simplest AI Adoption: AI FDE Box