Ho Chi Minh City · Singapore · Working worldwide

AI-Native Engineering and Product-Led Growth Team who ship outcomes, not tickets.

We deploy elite AI engineers and product leaders — fluent in state-of-the-art AI — to build and ship your production-ready product in weeks, not months. Trusted by high-growth companies and leaders globally, we architect and deploy mission-critical AI systems that deliver production scale and measurable business impact.

See our work

30 minutes, with an engineer — not a salesperson.

Working coverage 
United States
Europe
Singapore
Japan
Vietnam
00061218
Overlaps our working dayTheir business hoursUTC axis · live
80+
Client projects delivered
5
Client markets — US, EU, SG, JP, VN
92.5%
Manual workload removed, best result
100+
Engineers (external in network)

Working across

TypeScriptReactNext.jsNode.jsPythonGoPostgreSQLRedisSupabaseDockerKubernetesExpoTypeScriptReactNext.jsNode.jsPythonGoPostgreSQLRedisSupabaseDockerKubernetesExpo
01 — Services

Enterprise-Grade Cognitive Systems. Engineered for Scale, Governance, and Speed.

AI-native engineering teams and product leaders. Senior-led architecture. Zero agency middlemen. Zero brittle wrappers.

01

Engineering Squads

High-velocity engineering squads embedded directly within your engineering organization, GitHub/GitLab repositories, CI/CD pipelines, and sprint rituals. We deploy machine learning engineers, systems architects, and full-stack distributed systems engineers to accelerate your core roadmap with production-tested rigor. From custom foundational model fine-tuning (LoRA/QLoRA) to high-throughput data pipelines, we operate as a direct force-multiplier for your technical leadership.

Dedicated technical squads · Contractual 4-hour synchronous overlap · Quarterly roadmap commitment

Most popular02

AI-Native Product Pods

Autonomous, cross-functional product organizations led by seasoned Product Managers, Machine Learning Engineers, Cloud Architects, and QA Automation Specialists. We assume complete operational and architectural ownership of your AI product domain — from technical discovery and systems design to continuous post-launch optimization, automated evaluation benchmarking, and compute efficiency scaling. We partner multi-year to continuously scale production throughput and maximize enterprise ROI.

Senior-led multidisciplinary squads · End-to-end product development, latency SLA & delivery ownership · 100% IP assignment

03

Production AI Sprints

A mission-critical AI capability, multi-agent orchestration, or cognitive pipeline taken from initial systems architecture to live enterprise production in 4 to 8 weeks. Every deployment includes customized automated evaluation harnesses, deterministic input/output guardrails, low-latency model routing tiers, and complete enterprise compliance validation.

Fixed scope · Guaranteed production acceptance criteria · SOC 2 / HIPAA / GDPR verified

02 — Why Rockship

Production velocity, proven in your codebase.

Validate our architectural rigor with a two-week paid discovery sprint. Walk away with full IP ownership if we aren't an exceptional fit.

Production-tested by default

Every system is architected, governed, and shipped by proven product and engineering leaders. Zero unvetted talent, zero outsourced staffing.

We scale what we ship

A large percentage of our production deployments evolve into multi-year product partnerships, continuously optimizing inference latency, cost-per-query, and model accuracy as your traffic scales.

Contractual timezone overlap

A guaranteed 4-hour daily synchronous working window with your core engineering team, written directly into our master services agreement.

Complete asset sovereignty

Your repositories, your cloud infrastructure. All source code, fine-tuned model weights, proprietary datasets, and agentic workflows assign to you immediately upon delivery.

03 — Team

The people you'll work with.

You meet the engineers before you commit.

Executive Team

Son Vo

Son Vo

Chief Operating Officer
Quan Do

Quan Do

Chief Technology Officer
Mimi Nguyen

Mimi Nguyen

Chief People Officer

Management Team

Huy Dang

Huy Dang

Managing Partner
Hung Tran

Hung Tran

VP of Engineering
An Nguyen

An Nguyen

Head of Product

Advisory Board

Dr. Wray Buntine

Dr. Wray Buntine

Chief AI Advisor
Full Professor of Data Science and AI at Monash University, top 0.75% most-cited AI researchers globally
04 — Selection

Empirical rigor. Deterministic execution. An uncompromising engineering bar.

We evaluate technical talent by production systems reliability, not resume claims. Here is our four-stage vetting protocol.

01

Architectural & Algorithmic Screening

Direct application or peer referral. Every candidate is evaluated by our technical directors — never non-technical recruiters. We filter for foundational computer science mastery, memory optimization, concurrency patterns, and production Git history.

02

Distributed Systems & Cognitive Architecture

A live architectural defense under enterprise production constraints. Candidates design resilient, distributed systems: dynamic multi-model routing, low-latency execution, agentic workflows — not memorized LeetCode puzzles.

03

Production-Grade Work Trial

A compensated, high-intensity technical sprint inside an isolated sandbox. Candidates architect a production capability, build automated evaluation harnesses (LLM-as-a-judge), implement strict schema guardrails (Pydantic/Zod), and submit pull requests reviewed against our highest code standards.

04

Two-Week Production Discovery Sprint

Embedded directly within your engineering repositories, CI/CD pipelines, and daily sprint cadence. Continued partnership is governed entirely by your technical leadership's evaluation of velocity, code maintainability, and delivery excellence.

05 — Case studies

What we've put into production.

80+ client projects across various industries. Please contact us for specific use cases for your needs. Client names withheld under NDA. Metrics measured by the client.

Resident support automation
Property management

Resident support automation

92.5%Manual workload removed
Read the case study →
Finance automation for a clinic group
Singapore · Healthcare

Finance automation for a clinic group

95%Time saved on close
Read the case study →
Conversational commerce
Vietnam · B2B distribution

Conversational commerce

+35%Revenue growth
Read the case study →
Loan origination automation
Indonesia · Microfinance

Loan origination automation

2.5×Applications per officer
Read the case study →
06 — AI R&D Lab

Our innovation engine.

A proprietary Agentic AI & Data Platform that closes the gap between static enterprise data and proactive, goal-driven autonomy.

Rather than simple chatbots or isolated models, the platform deploys coordinated multi-agent workflows that safely query data silos, reason through high-stakes constraints, and execute mission-critical tasks in real time.

We are rolling out structured access and early-adopter deployments for global enterprise partners who want to automate domain-specific operations without compromising security or data sovereignty.

The AI R&D Lab platform: agentic workflows, data silo integration, goal-driven autonomy, security and data sovereignty, and enterprise operations arranged around the Rockship innovation engine.

Agentic workflows

Coordinated multi-agent runs with hand-offs and guardrails, not single-shot prompts.

Data silo integration

Governed queries across systems that were never built to talk to each other.

Goal-driven autonomy

Agents work towards a stated outcome and reason through the constraints on the way.

Security & data sovereignty

Deployed inside your boundary, so the data stays where your regulator expects it.

Enterprise operations

Built for the domain-specific, mission-critical work that runs the business.

Dr. Wray Buntine

Dr. Wray Buntine

Chief AI Advisor

Long before large language models captured global attention, Dr. Buntine's research at NASA Ames, UC Berkeley and Monash University established the frameworks for machine learning, nonparametric topic modelling and Bayesian inference that foundational models rely on today. With over 17,000 citations and a place in the top 0.75% of the most-cited scientists in AI, his ongoing work on reasoning calibration, reward modelling and explainability keeps our agentic systems out of black-box territory — grounded in provable safety and explainable logic.

07 — A career, redefined

We forge the product engineers who own the outcome.

In the era of automated code generation, syntax is commoditized. What remains exceptionally scarce is the engineer who owns systems architecture, domain constraints, and commercial ROI.

01

Forward-deployed by default

Our engineers and product leads embed directly with your executive stakeholders, analyze regulatory and business constraints in real time, and ship production code. Zero account-manager dilution, zero requirements lost in translation.

02

AI-native engineering discipline

Automated evaluation harnesses, deterministic guardrails, and inference cost governance are foundational engineering standards here — not post-launch afterthoughts.

03

Institutional mentorship, proven ownership

Building high-impact software demands equal rigor across product discovery and systems engineering. Emerging product managers and engineers hone their craft embedded within senior cross-functional pods — proving their execution across live production milestones before directing client roadmaps.

Engineers: see our next open session.

08 — Questions

The architectural, security, and operational standards enterprise leaders ask first.

Engagement, Commercial Terms & Team Collaboration

For evaluating partnership models, IP ownership, and cross-border velocity.

How do we engage, and how do we exit?

We structure partnerships around validated technical outcomes and production velocity, never commoditized headcount rental. Depending on your operational roadmap, we deploy under two primary engagement models:

Every engagement begins with a two-week paid discovery sprint embedded directly within your code repositories and communication channels. If we do not demonstrate exceptional technical velocity, architectural rigor, and cultural alignment during this period, you may terminate the engagement immediately with zero ongoing financial commitment and 100% exclusive ownership of all delivered architecture, configurations, and code.

  • Fixed-Scope AI Delivery Sprints: Concentrated 4- to 8-week production milestones designed to take an AI system from initial architecture to staging and live production deployment under contractually guaranteed acceptance criteria, latency thresholds, and evaluation benchmarks.
  • Dedicated AI Product Pods: Integrated, cross-functional squads — comprising a dedicated Product Lead, Senior Machine Learning Engineers, Full-Stack Developers, and QA Engineers — deployed on quarterly roadmap commitments to own technical domains end-to-end.
Who owns the intellectual property, model weights, and custom datasets?

You retain 100% exclusive ownership of all intellectual property from day one. Because our engineers develop directly within your cloud infrastructure and GitHub/GitLab organizations, IP never resides on Rockship systems:

  • Complete Asset Scope: Your ownership encompasses all source code, fine-tuned model weights (e.g., LoRA and QLoRA adapters), proprietary vector embeddings, synthetic training datasets, custom data pipelines, and architectural system diagrams.
  • Immediate Legal Assignment: All intellectual property rights are assigned to your entity automatically upon creation under bilateral contract. We never retain, claim lien over, or reuse your proprietary domain logic.
  • Clean Decommissioning: On the exact date an engagement concludes, all access credentials, cryptographic tokens, and repository permissions are formally revoked and audited.
How do you eliminate timezone friction across global teams?

We eliminate asynchronous communication bottlenecks by contractually guaranteeing a 4-hour daily synchronous working overlap with your core engineering and product leadership, regardless of your geography:

  • Seamless Team Integration: Our engineers and product leads integrate directly into your daily sprint rituals — participating in live standups, collaborating in Slack/Teams channels, and conducting real-time GitHub code reviews.
  • Multi-Market Coverage: We actively support enterprise partners across Silicon Valley (PST), New York (EST), London (GMT/CET), Singapore (SGT), and Tokyo (JST). Our overlapping sprint schedules ensure that technical blockers, pull requests, and architectural decisions are resolved synchronously within hours, preserving rapid continuous deployment velocity.
How do you ensure our internal engineering team can own and maintain the system after handoff?

We reject consultant dependency. Our goal is to institutionalize permanent AI capabilities inside your organization so your team can maintain, debug, and extend the system independently:

  • Paired Engineering & Architectural Reviews: Throughout the engagement, our engineers and product leads conduct weekly architectural syncs, paired programming sessions, and collaborative pull request reviews with your internal technical staff.
  • Living Specifications: We deliver comprehensive system documentation, architecture decision records (ADRs), interactive API documentation, and automated evaluation suites that serve as executable specifications for future model updates.
  • Turnkey Operational Runbooks: Every handoff includes documented incident-response playbooks, token cost alerting dashboards, and step-by-step procedures for updating retrieval embeddings, re-indexing vector stores, and retraining custom adapters.

Tell us what you're trying to ship.

Thirty minutes with an engineer. You'll leave with a written view on the team we'd recommend — either way.

info@rockship.co