Forward-deployed AI engineering · For owner-led businesses

AI, where
the work
happens.

Feinity embeds a senior AI engineer inside your business to find one workflow worth automating, build it end to end, and keep it running. Fixed scope, live in weeks, no internal AI team required.

  • First deployment 2–6 weeks
  • Engagement Fixed scope, fixed price
  • At handoff Code and accounts are yours

01 / The gap

The demo works.
Production is a different job.

AI can answer a clean question. Your business runs on exceptions, handoffs, and systems that were never designed to talk to each other. That is where most AI projects stall.

01

The brief misses the work.

The rules that keep things running live in people's heads. A requirements doc never captures them.

02

The tool doesn't know your business.

Generic automation cannot judge a good lead, a bad quote, or the job that needs a person.

03

Nobody stays for the messy part.

Launch is the easy part. Quality drifts when no one is watching the workflow in production.

Feinity puts one engineer inside the work, from the first observation to the daily operation.

02 / The model

One engineer.
The whole loop.

A forward-deployed engineer works inside the business, not at arm's length from it. They learn how the work actually gets done, build the system in the middle of it, and stay accountable for what happens after launch.

At Feinity, that is one senior engineer: the same person who shadows your team, writes the blueprint, ships the build, and owns the runbook.

Enterprise FDE teams are built for Fortune 500 rollouts. Feinity brings the same discipline to owner-led businesses: one senior engineer, one workflow, one fixed price, and a system you own.

FDE / right-sized for owner-led business
The FDE loop Observe → ship → operate
01

Shadow

We watch the real work: calls, inboxes, spreadsheets, and handoffs. We find where time leaks and where AI can be trusted.

Output Opportunity map

02

Blueprint

We map the data, systems, exceptions, and acceptance tests into a fixed-scope build plan.

Output Architecture + scope

03

Build

We ship in phases against real examples, with a working review every week.

Output Production system

04

Operate

We monitor quality, cost, and failure modes, then improve the workflow as the business changes.

Output Runbook + care plan

Production feedback changes the next build.

The same engineer owns every step. There is no handoff between the person who understands the workflow and the person who builds it.

03 / Where we deploy

AI for the work that keeps the lights on.

We work with owner-led businesses where a missed lead, a slow quote, or a manual handoff has a direct cost.

01

E-commerce

Keep product data clean, order exceptions moving, and support tickets out of your inbox.

  • Support triage
  • Order exceptions
  • Product data
  • Supplier documents

First buildAI chatbot

02

Home services

Recover missed calls, qualify jobs, follow up on quotes, and keep the calendar full.

  • Missed-call recovery
  • Quote follow-up
  • Scheduling
  • Review requests

First buildAI voice agent

03

Professional services

Turn client intake, documents, and proposals into a workflow that does not depend on memory.

  • Client intake
  • Document extraction
  • Proposal drafts
  • CRM hygiene

First buildAI document processing

04

Delivery & field ops

Handle route exceptions, proof-of-delivery, driver questions, and the daily closeout.

  • Exception handling
  • Proof of delivery
  • Driver support
  • Daily closeout

First buildBusiness workflow agent

Not on the list? If the work runs on calls, email, documents, and a CRM, we can map it.

Bring us the process

04 / The deployment

Shadow first.
Ship in weeks.

A first deployment is intentionally small: one workflow, real data, production use. You see working software every week.

Week 0

Shadow & assess

Observe the current workflow, review systems and data, and choose the first build.

OutputOpportunity memo

Week 1

Blueprint

Fixed scope, architecture, data access, acceptance tests, and a price you approve.

OutputBuild plan

Weeks 2–4

Build

Ship in phases and test against real examples. Review working software every week.

OutputAlpha system

Weeks 5–6

Deploy

Beta with your team, training, documentation, and a two-week warranty.

OutputProduction handoff

Ongoing

Operate

Monitor, evaluate, fix, and improve under a Care plan or as needed.

OutputRunbook + reviews

A focused first build usually runs 2–6 weeks after scope is agreed. Integrations can extend the timeline; the proposal states the schedule before build starts.

05 / Pricing

Published ranges.
Fixed scopes.

Every proposal names the workflow, the systems, the acceptance tests, and the price. If the scope changes, we quote it before we build.

Start with one workflow that has a clear cost when it fails or slows down. We scope the build, test it against real examples, and put it into production.

Typical: $2.5k–$8k

AI chatbot

Answer common questions, qualify leads, and hand off to a person with context.

$1,500–3,000

AI lead management

Capture, qualify, route, and follow up across calls, forms, and your CRM.

$2,500–5,000

AI voice agent

Answer or return calls, book appointments, and capture job details.

$3,000–7,000

AI document processing

Extract, validate, and route data from PDFs, email, and scans.

$3,000–8,000

CRM integration

Connect the tools your team already uses and keep records clean.

$3,000–8,000

Business workflow agent

Multi-step workflows with approvals, exceptions, and human handoff.

$5,000–15,000

Most first builds land between $2,500 and $8,000. Delivery: 2–6 weeks.Fixed scope before build.

06 / The handoff

Everything we build is yours.

A system you cannot inspect is a system you do not own. At handoff, you get the source code, the accounts, the documentation, and the runbook. Run it yourself, or keep us on to operate it.

  • Source code in your repository
  • Cloud and API accounts in your name
  • Architecture and data-flow documentation
  • Runbook with failure and escalation paths
  • Team training and a recorded walkthrough
  • Two-week post-launch warranty

No proprietary runtime. No hosting lock-in.

07 / The practice

Senior work,
directly.

Feinity is a California-based AI engineering practice founded in 2026 by Fei Shen. Fei has spent 15 years building backend and data platforms, with a Master's in Computer Science. He started Feinity because small and midsized businesses need the same caliber of embedded engineering that large companies take for granted.

Every engagement is led by the engineer doing the work. No account managers, no handoff to a junior team.

Fei Shen

Founder · Forward-deployed engineer

01

Scope before code.

Fixed price and acceptance tests before the build begins.

02

Work in the open.

Weekly demos, shared docs, and no surprises.

03

Leave you stronger.

Your team gets the system, the training, and the runbook.

08 / Questions

The things owners ask first.

If your question is not here, ask it directly. A short call is usually faster than a proposal.

What is a forward-deployed engineer?
A senior engineer who works inside your business rather than at a distance. They observe the real workflow, build the system, and stay accountable for production. Feinity's model is one engineer from assessment through handoff.
Do we need to know what to automate?
No. The assessment starts with observation, not a tool demo. We look for work that is repetitive, measurable, and tolerant of a human check where needed.
How long until something is live?
A focused first build usually takes 2–6 weeks after the scope is agreed. Audits are shorter. The proposal sets the schedule before build starts, and you see working software every week.
What does it cost?
Audits start at $500. Project builds range from $1,500 to $15,000. Care plans start at $299 per month. Every scope is fixed before work begins.
How is this different from hiring an agency?
An agency usually separates sales, project management, and delivery. Feinity is one senior engineer from assessment through handoff. You get a fixed scope, one workflow, and a system that is documented and handed over, not a handoff chain.
Who owns the code and the accounts?
You do. We build in your repository and, where possible, under your cloud and API accounts. At handoff you receive the source code, documentation, and runbook.
Is our data safe?
We use least-privilege access, work in your accounts where possible, and document the data flow in the proposal. Client data is not used to train models without written permission. Workflows that need judgment include a human approval step.
Who pays for model and API usage?
You do, directly with the providers. We estimate usage and include it in the proposal so there are no surprise pass-through bills.
What if AI is not the right answer?
We will say so. Sometimes a rule, a form change, or a cleaner CRM setup solves the problem for less. The audit is designed to answer that before you commit to a build.
Do you work outside California?
Yes. Delivery is remote-first across the US and internationally. Work is billed in USD.

09 / Start

Tell us what
eats your week.

Bring one process: a missed call, a slow quote, a document pile, a handoff that keeps breaking. We will tell you whether an AI workflow is worth building.

Email
Mailing
2108 N St #11297
Sacramento, CA 95816

What happens next: a 20-minute call, a short workflow map, and a go/no-go. No deck, no pressure.