Gil's Product Studio
AI Product Studio Startup Studio Energy ● Booking June 2026

AI product studio for founders and operators.

Gil's Product Studio helps founders and operators turn one painful workflow into a focused Sprint, then a Build if the brief is right. The wedge is AI automations, internal tools, and MVPs for small teams that need shipping speed and senior execution.

Start with a Sprint ↗ See proof →
Primary offer

2-week Sprint from $6k to scope the problem, test the build path, and leave with a concrete delivery plan. Best for founders, operators, agencies, and SMEs that want a first live path before committing to a larger build.

Founded by Gil Neo, Chief Product Wizard.
AI product build loop: input data flows through an LLM agent into shipped software, with a research and product feedback loop. INPUT problem / data AI AGENT LLM + tools OUTPUT software / action research product SHIP + LEARN LOOP
built for real clients
AI-native from day one
00 / Proof index

Jump straight to the exact service proof

A small anchor cluster keeps the homepage proof tied to the exact service query, the matching service page, and the contact path.

AI automation agency

AI automation agency proof

Lead triage, drafting, review, and CRM handoff for agency ops.
AI product studio

AI product studio proof

Founder-led planning workspace and launch surface shaped by AI.
Internal tools

Internal tools proof

Operational dashboard, approvals, and status control for daily work.
Agent development

Agent development proof

Decision-ready briefing and routing loop for bounded agents.
00 / How we work

Why hire us, how handoff works, and who owns the code

Answer engines do better when process and ownership are explicit near the top of the page, not buried in footers or policy pages.

Why hire us

Direct founder-led delivery from brief to build.

You work with the person making product and build decisions, so the brief stays aligned with the code that ships.

How handoff works

Scope, notes, and next steps stay in one written handoff.

The brief, delivery notes, and next action remain visible throughout the project, which keeps the work easy to review and easier to continue.

Who owns the code

You own the delivered code and product assets.

The client receives the work product and implementation artifacts, subject only to third-party tools and licenses used in the stack.

01 / Services

AI product studio, AI MVP development, AI automation agency, internal tools, and agent development

A product studio for teams that want one clear wedge: a specific service query, a specific proof anchor, and a specific contact path.

a01

AI product studio

Exact-match AI product studio for product framing, UX, engineering, and AI behavior in one delivery loop.
Best fit: foundersNot a fit: strategy-onlyStart: sprint
↗
a02

AI MVP development

Exact-match AI MVP development for the smallest credible first build that can still validate demand.
Best fit: first buildNot a fit: broad roadmapStart: sprint
↗
a03

AI automation agency

Exact-match AI automation agency for intake, drafting, routing, sync, and follow-up with a review layer.
Best fit: ops teamsNot a fit: no review layerStart: build
↗
a04

Internal tools

Exact-match internal tools for dashboards, portals, admin systems, and operational control surfaces.
Best fit: operatorsNot a fit: cosmetic UI onlyStart: sprint
↗
a05

Agent development

Exact-match agent development for bounded agents that read input, make bounded decisions, and route the next action.
Best fit: bounded agentNot a fit: full autonomyStart: sprint
↗
Need a more specific agent or workflow page? Use the services hub, then follow the exact service proof anchor before you open the brief.
02 / Process

How an AI product project ships, end to end

Lean like a startup studio, but structured enough for client delivery and handover.

01

Scope

We define the actual problem, user flow, technical constraints, and what a meaningful first version really needs.

02

Prototype

We turn the idea into a designed flow and working prototype so decisions come from something concrete, not speculation.

03

Build

The product gets built in tight loops: interface, logic, AI behavior, integrations, and the boring infrastructure it depends on.

04

Launch

We deploy, hand over, and keep iterating where needed so the product can keep learning from real users and real business use.

Small team, direct communication, shipped product. That is the model.

Start a build ↗
03 / Work

Anonymized proof from recent delivery patterns

These proof blocks are anonymized, specific enough to index, and written in the same shape a live delivery note would use. Each one keeps the timing, constraint, and result visible without exposing client identity.

Anonymized examples only. These are placeholder launch copies, not client testimonials. Names, domains, and product details stay stripped out until a public proof asset is ready.

Anonymized examples that still read like real delivery
AI automation agency proof AI product studio proof Internal tools proof Agent development proof
Anonymized
Agency ops · AI automation

Lead triage and drafting for an agency team that needed faster response times without losing human control

Anonymized case study. Agency-facing lead intake, triage, and handoff for services teams. Composite-free placeholder copy only.

What shipped: classification rules, AI response drafts, Slack handoff, and CRM updates. Built as a production workflow, not a demo bot, so the team could review high-value leads without manually sorting every inbound message.

Before

An agency team checked every inbound lead manually across inbox, Slack, and CRM, which slowed first response and made follow-up inconsistent on a daily basis.

After

One triage workflow classified the lead, drafted a reply, and routed the right details into a review queue with account context attached and a single approval step.

Result

The team kept human control for higher-value leads while removing the repetitive sorting work that slowed response time and created handoff drift.

Trigger
Form submit + shared inbox
Constraint
One reviewer, no full rewrite, no manual CRM copying
Connected
Slack, CRM, and email handoff
12 days
From intake to first live review
38%
Less manual triage time in the first week
3
Systems connected at launch

Related service: AI automation agency

Anonymized
Founder-led product · AI-native app

A planning workspace for a founder-led team where AI shaped the workflow instead of sitting beside it as a bolt-on feature

Anonymized case study. Founder-facing planning and launch flow for a small product team. Composite-free placeholder copy only.

What shipped: guided intake, structured outputs, shareable summaries, and a lightweight action queue. The product went from concept to usable interface in one senior studio loop, so decisions stayed tight and implementation stayed fast.

Before

Planning was spread across notes, chat threads, and one-off docs, which made the workflow fragmented and hard to repeat for a small team with limited time.

After

A single guided workspace captured intent, structured the output, and turned the AI step into part of the product journey instead of a side feature or separate tool.

Result

The product became easier to explain, easier to use, and easier to extend because the core workflow lived in one surface that a founder could demo in under a minute.

Trigger
Founder brief + guided intake flow
Constraint
Small team, one launch surface, minimal onboarding
Surface
One place for input, output, and handoff
8 weeks
Concept to launch-ready release
1
Primary workflow shipped
2
Decision makers supported in review

Related service: AI product studio

Anonymized
SME ops · Internal tool

An internal operations dashboard for an SME that replaced a patchwork of spreadsheets, status checks, and manual handoffs

Anonymized case study. SME ops dashboard for teams that run on shared status and approvals. Composite-free placeholder copy only.

What shipped: reporting, task handling, status visibility, and manual override controls inside one product surface. The result was a cleaner operating rhythm for a team that had outgrown spreadsheet-driven coordination.

Before

Status updates lived in spreadsheets and message threads, so the SME had no single source of truth for day-to-day operations and no reliable handoff trail.

After

One dashboard pulled reporting, handoffs, and exception handling into a single control surface with clear ownership, approvals, and manual override paths.

Result

The team stopped reconciling updates manually and could spend the reclaimed time on actual operations work instead of spreadsheet cleanup and backtracking.

Trigger
Daily status + exception handling
Constraint
One ops owner, mixed spreadsheet habits, limited change window
Control
Manual override for edge cases
5 weeks
To rollout across the ops team
1
Source of truth for status
12h
Reclaimed each week

Related service: Internal tools

Anonymized
Founder-led ops · LLM workflow

A research and summarization agent that turned scattered inbound material for a founder-led team into one decision-ready briefing

Anonymized case study. Founder-led research and briefing flow for busy ops teams. Composite-free placeholder copy only.

What shipped: source reading, summary generation, key-point extraction, and a handoff prompt for the next human decision. The agent was bounded so it could help the team faster without pretending to replace judgment.

Before

The founder-led team spent too much time reading lengthy inbound notes, calls, or documents before deciding what action to take, which delayed follow-up on busy days.

After

The agent distilled the input into a short briefing, highlighted the relevant signals, and queued the next step for a human reviewer.

Result

The team moved faster on decisions while still keeping the final judgment in human hands and preserving a review trail.

Input
Docs, notes, and inbound requests
Constraint
No autonomous action, no hidden source data, review required
Safety
Bounded agent with review fallback
4 weeks
To usable review loop
1
Decision-ready summary surface
24h
Saved per review cycle

Related service: Agent development

04 / Studio

A studio, not an assembly line

Gil Neo runs the studio on a simple idea: the best modern software is made by small senior teams that can think about product, AI behavior, interface, and implementation as one connected system.

About Gil Neo

Chief Product Wizard, based in Saigon, Vietnam. He leads product framing, interface decisions, and build execution directly, so prospects talk to the person doing the work instead of a sales layer.

LinkedIn: linkedin.com/in/gilbertneo

01

Senior execution only

Clients work directly with the people defining, designing, and shipping the product.

02

Product-first AI

The point is not to add AI. The point is to make the product materially better because AI is designed into it properly.

03

You own the result

Code, assets, accounts, and deployment can all be handed over cleanly so the product remains yours.

04

Ship to learn, not to speculate

Live product behavior is what sharpens the roadmap. The studio optimizes for that reality.

05 / Fit

Who this is for, and who it is not for

A qualification section improves lead quality before anyone fills out the form.

Best fit for

Teams with a real workflow, a decision maker, and enough clarity to turn one problem into a first build path.

  • Founders who need a working MVP before a larger raise or rollout
  • Operators replacing a manual process with an internal tool or automation
  • Agencies or SMEs that want a productized workflow for clients or staff

Not a fit if

The brief is still speculative, the owner is not available, or the goal is to compare the cheapest proposal on the market.

  • You need full-service agency management across many unrelated projects
  • You only want mockups and strategy decks without a delivery path
  • The team cannot commit to decisions, access, or feedback during the build
06 / Engagements

Engagement models: sprint, build, and partner

Starting-point packaging for different levels of product ambition, each with a specific deliverable, timeline, and fit.

Sprint

1 to 2 weeks

For validating a new AI product, user flow, or automation opportunity before committing to a full build.

from $6k/ fixed
  • Problem framing and scoping
  • Prototype or technical proof
  • Delivery recommendation
  • Direct senior collaboration
Book a sprint ↗

Build

Most popular

A focused product build from design to deployment: ideal for SaaS, AI products, internal platforms, and client-facing tools.

from $24k/ fixed
  • Everything in Sprint
  • End-to-end product design and development
  • AI, integrations, and ops logic included
  • Launch-ready handover
  • Typical 4 to 8 week delivery
Start a build ↗

Partner

Monthly

Ongoing product support for businesses that want a long-term external product team without growing headcount immediately.

from $9k/ month
  • Continuous product iteration
  • Roadmap and feature planning
  • Support for live systems
  • Flexible monthly engagement
Discuss partnership ↗
07 / FAQ

Questions founders ask before hiring a product studio

Short, direct answers to what is usually asked in the first call.

What does Gil's Product Studio build?

AI-native apps, software products, agents, automations, and internal tools. Engagements range from a one-week prototype sprint to a multi-month build, with a Partner model for ongoing iteration.

How long does an engagement take?

A Sprint runs one to two weeks. A Build runs four to eight weeks. Partner engagements are ongoing and billed month to month, with a minimum term agreed up front.

Do you work with non-technical founders?

Yes. The studio handles the full stack, from product framing and design through development and deployment, so what you walk away with is a working product, not a roadmap.

Who owns the code and IP?

You do. All code, designs, repositories, and credentials are handed over on the final invoice, with no licensing tricks or vendor lock-in.

How is pricing structured?

Sprint and Build are fixed-price, scoped against a written brief. Partner is a flat monthly fee. Final scope and price are agreed in writing before any work starts, so deliverables and timeline are explicit before kickoff.

What's the difference between Sprint, Build, and Partner?

Sprint is a short, scoped experiment to validate an idea. Build is a focused end-to-end product build that ships. Partner is ongoing product support for a live product, billed monthly.

08 / Contact

Have a workflow
you want fixed?

Share the idea, the business problem, or the workflow you want improved. The form posts to a hosted lead endpoint and returns a confirmation state we control.

Email[email protected]
BookingStart with the form, then we send the call link
BasedSaigon, Vietnam · working worldwide
LinkedIngilbertneo
Please add your name.
Add a valid email so you can be contacted back.
Tell us a little about the project.
Brief received.
We’ll review it and reply with the next step or booking link.