Enterprise AI adoption · FDE forward deployed engineers
We send engineers to your office,
rolling out AI department by department.
An FDE (Forward Deployed Engineer) is an engineer placed on site inside your company and accountable for business results. Starbox sends a team that understands both the business and AI to your office, starts with one department to hand daily repetitive work over to AI agents, and expands to other departments quarter by quarter once proven.
¥2,000,000 annual retainer · paid in 4 quarterly installments¥50,000 kickoff deposit · credited in full upon signing
to the whole company
Our foundation
Understand the business thoroughly first, then build agents.
Summary
Starbox FDE follows the forward deployed engineer model proven by Palantir and adds 15 years of client service experience: diagnose the company and map its processes first, then build agents. Phase one usually starts in marketing, runs the full DDABC marketing chain, and rolls out department by department over 12 months. Annual retainer is ¥2,000,000, launched with a ¥50,000 deposit. The measure of success is that after Starbox leaves, your own team keeps working efficiently with AI.
Source: Starbox FDE Enterprise AI Adoption V2 and Technical White Paper V3 (2026).
Why FDE
When enterprises adopt AI, most money is wasted on trial and error.
Over the past two years, almost every company has tried AI, but few have AI doing real work every day and improving over time. The bottlenecks usually come down to three issues, with little to do with model quality:
Tools are activated, yet employees stick to old habits. Without process redesign, AI is just another app nobody opens.
Everything works in the demo, then stalls in real work: scattered data, inconsistent wording, no one accountable for results.
Tech teams can build agents but cannot say how the business should change; business teams know the pain but not how far AI can go.
What FDE is
Engineers deployed on site, working until the system is truly usable.
Forward Deployed Engineer. Pioneered by Palantir in the 2010s and later adopted by OpenAI, Anthropic, Databricks and others: full-stack engineers embedded in the client's real environment solve problems end to end, then feed what they learn back into the platform.
No demo pitches. They are there to do the work.
What they deliver is a system that runs.
They take part in redesigning the business process.
Field experience goes back into the product, which keeps improving.
In short, FDE combines platform and on-site engineers delivered against business results, leaving you with workflows that are already fully operational.
Sources: Palantir, "A Day in the Life of an FDSE"; Wikipedia; The Pragmatic Engineer; Everest Group.
Starbox FDE
Starbox FDE brings one more thing: 15 years of enterprise client service.
| Comparison | Traditional FDE | Starbox FDE |
|---|---|---|
| Core | Built around engineers | Understand the company first, then build agents |
| Foundation | Strong in technical delivery and platform | 15 years of consulting, marketing, outsourcing and training |
| Industry experience | Mostly large clients with mature data | Industry know-how from 500+ companies |
| Where requirements come from | Tech-driven; the client must spell out needs | We diagnose what the client cannot yet put into words |
| Reusable assets | Platform and systems | Own platform + a reusable cross-industry solution library |
What we do
We do six concrete things, from identifying issues to getting systems working.
Consulting methods to understand the organization and processes before writing any code.
Organization · process · bottlenecksUncover the real needs the company itself cannot articulate. This is the core FDE skill.
Real needs · prioritiesStandardize the process first, then apply AI. Agents only add value once the process is right.
Standardized · documentedCustom agents for each kind of repetitive human work.
Role workflow codification · dedicated agentsTake one whole department onto AI, then roll out to the next.
One department firstProven methods and reusable assets cut the cost of trial and error.
Solution library · reusableOur boundary: FDE orchestrates, reviews, and coaches hands-on, but does not do employees' jobs for them. The goal is to get your own team proficient so you do not rely permanently on outside staff.
Method
Marketing follows the 5-step DDABC chain, prioritizing what comes first and next.
Phase one typically begins in marketing, running through the full five-stage journey and turning key role practices into "role SOPs + dedicated agents". Even if staff turn over, best practices remain inside the company.
Pin down target customers, the core selling points and the channel mix. Customer profiles · selling points · positioning.
Make sure target customers come across you on every platform and in search. Video IP matrix · product posts · SEO / GEO · ad creative.
Prove reliability from several angles. Expert content · reviews · cases · credentials.
From interest to enquiry to sale. Answer scripts · campaigns · closing.
Repeat purchases, reviews and referrals. Community · review content · referral programs.
The content mix differs by sector. In trust-driven sectors with long decisions, trust content takes the largest share; in traffic-driven sectors, "discover" comes first. Below is the mix for a K-12 education client:
12-month roadmap
12 months, from one department to the whole company.
- Platform foundation
- Company knowledge base
- Full DDABC chain live
- Key role experience codification
- Complete SOPs
- First agents live
- Dedicated work agents built for operations, customer service, and support
- Marketing moves to steady-state operation
- AI rolled out to corporate functions and admin
- Prepare next year's marketing along DDABC
- AI locked in across all departments
- Second marketing push
- Industry solutions and benchmark cases documented
Q1 sets up the platform, builds the knowledge base, runs the marketing chain, codifies key role experience, drafts all SOPs, and deploys the first agents, so effort is concentrated up front; the remaining three quarters roll out and optimize department by department, with effort naturally tapering.
After one year
After one year, these eight assets stay with your company.
A dedicated company workspace on our own platform; platform content production costs are included in the engagement.
Experience scattered across files, chats and senior staff, cleaned and stored so it can be searched and used.
Standardize first, then apply AI; everything documented and turned into process.
Key role workflows and know-how organized into actionable materials that even new hires can follow.
First department agents live, then rolled out company-wide quarter by quarter.
Define → Discover → Assure → Buy → Continue, with the mix and pace tailored to your sector.
Roadshows, team training, and internal rollout guidance so employees can and want to use it.
Customer success support all year; in Q4, an industry solution and benchmark case.
The outcome we measure is:
After Starbox leaves, your team continues using AI to get work done well on their own.
How we engage
Five steps: see results first, then sign for the full year.
An in-depth conversation to pin down your real needs and AI direction; confirm intent and start with a ¥50,000 deposit.
KickoffAn AI adoption plan for your company, and a first set of agents deployed in one department (for example marketing).
15–30 daysPresent the plan, deploy the first agents and coach the internal rollout.
Organizational pushValidate results in real use, collect feedback and adjust the plan.
About 1 monthOnly after this trial period do we confirm the 12-month annual agreement: ¥2,000,000, with the deposit credited in full.
Formal agreementIf you sign the annual agreement, the ¥50,000 is credited in full against the annual fee; if not, it converts into the deployment fee for the initial plan and first agent batch, non-refundable.
Start with ¥50,000 to get a tailored adoption plan and see the first agents running in actual operations before committing to a full engagement.
Pricing
Pricing: ¥2,000,000 for the full year, paid across four quarters.
Full Enterprise AI Adoption
12 months · paid in 4 quarterly installments
- Enterprise diagnosis + end-to-end SOP optimization
- Single-department first agent deployment + hands-on onboarding
- Quarter-by-quarter company rollout full enterprise AI adoption
- Cross-industry reusable solution library support
¥50,000 Kickoff Deposit
See the plan and first agents before committing
- If signed the ¥50,000 is credited in full against the annual agreement
- If not signed converted to deployment fees for the initial plan and agents, non-refundable
- 15–30 days first batch of agents running in a single department
- ~1 month trial period decide on full engagement based on real-world results
Annual agreement includes: FDE on-site service · Starbox platform · knowledge base construction · process mapping & SOP optimization · development & deployment of first departmental agents · team training · platform content generation allowance · ongoing customer success support. Final terms subject to official agreement.
Want to explore FDE case studies? Real-world cases across K-12 education AI admissions, packaging AI quoting, and supermarket store management are available in our Case Studies.
View case studiesUnsure of your direction? Start with an AI maturity diagnosis and roadmap from an AI consultant, starting at ¥100,000 per quarter.
Explore AI consultingOnly need a lightweight solution? Starbox Starbox! is a standalone product: it puts your knowledge base and team workflows directly into chat, with no on-site deployment needed.
About Starbox Starbox!FAQ
Enterprise AI Adoption (FDE) FAQ
What is the difference between AI Advisory and Enterprise AI Deployment (FDE)?
AI Advisory provides a team of four advisors who give the business leader strategic direction, methodologies, and decision support, while execution is handled by the client's internal team (CNY 100,000 per quarter, CNY 300,000 per year). Enterprise AI Deployment (FDE) embeds an on-site team within the company, starting in one department and expanding AI across the entire organization over 12 months, taking full ownership of deployment outcomes (CNY 2,000,000 annual contract). You can start with advisory to set the direction before deciding whether to move forward with FDE.
What does FDE mean?
FDE stands for Forward Deployed Engineer, a model pioneered by Palantir in the 2010s: engineers are deployed directly on-site with clients to solve problems end-to-end until systems are fully operational. It is not sales, consulting, IT implementation, or outsourcing; it delivers working business operations.
How does Starbox FDE differ from traditional FDE?
Traditional FDE is engineer-led, primarily serves large enterprises with mature data infrastructure, and requires clients to articulate their own technical requirements. Starbox FDE builds on technical engineering with 15 years of B2B experience across consulting, marketing, outsourcing, and training, backed by insights from serving over 500 enterprises: we diagnose your business and map your processes before building AI agents, structuring the requirements even when you cannot fully articulate them.
What exactly does enterprise AI implementation (FDE) do?
Six steps: enterprise audit and mapping, in-depth requirement discovery, end-to-end SOP optimization, agentifying repetitive tasks, department-level AI adoption, and using proven methods to minimize trial and error. Stage one typically starts with marketing, expanding department by department each quarter across the entire company.
Why start with the marketing department?
Marketing feels the pain most acutely, results are quantifiable, the learning curve is low, and best practices are easily replicated, making it easiest to deliver results first. Starbox uses the DDABC full-funnel marketing model (Positioning, Discovery, Trust, Conversion, Retention) to fully validate the workflow in marketing before rolling it out to operations, customer service, and back-office functions.
What will your enterprise retain after one year?
Eight proprietary enterprise assets: the platform foundation, enterprise knowledge base, process and SOP systems, role capability distillation, custom workplace AI agent matrix, DDABC full-funnel marketing tailored to your industry, your team's operational AI capabilities, and industry-benchmark solutions built through year-round coaching.
Does the FDE team do the work for client employees?
No. FDE consultants orchestrate, supervise, and provide hands-on coaching without doing the employees' daily work for them. Success means that once Starbox steps back, your own team continues working efficiently with AI, rather than relying indefinitely on external staff.
How does an engagement begin?
Five steps: initial alignment to confirm direction; developing an implementation plan and deploying the first AI agents in a single department (about 15–30 days); roadshow and internal rollout guidance; fine-tuning in real-world workflows for about 1 month; and finalizing an annual agreement after the trial period. An initial intent deposit is paid at kickoff and fully credited toward the annual contract upon signing.
How does the 12-month rollout work?
Q1 focuses on overall rollout and initial department implementation, completing platform infrastructure, the knowledge base, the full DDABC lifecycle, role competency distillation, complete SOPs, and the first wave of AI agents—representing the most intensive investment. Q2 and Q3 expand department by department with ongoing optimization. Q4 solidifies across all departments, establishing industry solutions and benchmark case studies.
What types of companies are suitable for FDE?
Enterprises that already recognize the value of AI, want systematic rollout, and require deep customization tailored to their specific workflows. If you only need standard products, you can directly use Starbox GEO, the New Media Content Factory, or Starbox Starbox!.
How is enterprise AI implementation (FDE) priced?
Annual master agreement: ¥2,000,000 for 12 months, paid in four quarterly installments. Includes FDE on-site consulting, the Starbox platform, knowledge base setup, workflow mapping and SOP optimization, R&D and deployment of the first batch of departmental AI agents, team training, platform content production usage, and ongoing customer success support. A ¥50,000 deposit is required at kickoff: fully credited toward the agreement fee if signed; if not signed, converted into the fee for upfront planning and initial agent deployment, non-refundable.
Guides
Methods and field notes
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