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Vietnam-based AI and data delivery partner

We design, ship, and harden agent workflows, reporting systems, data pipelines, and automation for teams that need senior execution without a bloated agency layer.

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SeaSure
Graspr AI
Zeno
Ahrvo
ClarifyIQ
FinanceScaler
OpenAI
BigQuery
Airflow
AWS
OpenAI / LangGraph / BigQuery / Airflow / AWS / Docker
Workflow preview

Watch the full-service workflow in motion

See how research, build, automate, harden, and handoff can stay inside one senior delivery loop instead of scattering across tools and vendors.

Founder-led delivery loop

Founder-led delivery from workflow audit to production hardening

Tran Tien Van leads the work from the first workflow audit through architecture, implementation, and hardening, so business context and technical decisions stay aligned all the way into production.

01

Founder-led Audit

Business goals and bottlenecks stay in one conversation.

02

System Ownership

Architecture decisions stay with the person shipping the work.

03

Hands-on Delivery

The same lead stays close to implementation and rollout.

04

Hardening + Support

Monitoring, docs, and post-launch support stay connected.

Tran Tien Van, founder of Van Data Team

Tran Tien Van

Founder-led AI agent and data engineering delivery from Ho Chi Minh City, Vietnam.

This section is built to answer the buyer question behind every founder-led service business: who is actually behind the work, and can that person be verified before the first call?

Here, the same person handles workflow audit, architecture direction, implementation, and hardening, so decision quality and execution speed stay in the same loop.

5.0

Upwork rating

71 public reviews

Founder-led

Decision chain

Scope, architecture, and delivery stay aligned.

Vietnam

Operating base

Ho Chi Minh City, Vietnam

AI + data

Execution lens

Agent workflows, reporting systems, and pipelines.

Service lanes

Services built around the bottleneck

Choose the lane that matches the workflow, reporting, automation, or data problem your team needs to scope, ship, and harden.

  1. Autonomous execution

    AI Agent Development

    Design AI agents that reason, call tools, and complete production workflows with clear guardrails and human review.

    Multi-step agent workflows for support, research, and operations
    Tool-connected execution across APIs, documents, and internal systems
    Human review, audit trails, and fallback handling for sensitive actions
    CrewAILangGraphOpenAIClaude
  2. Reliable data movement

    Data Pipelines

    Build resilient batch and streaming pipelines that move data cleanly from source systems into warehouses, reports, and AI-ready products.

    Batch and streaming ingestion designed around real freshness needs
    Warehouse-ready transformation models for reporting and AI consumers
    Monitoring, alerting, and replay-aware operational controls
    AirflowKafkaBigQuerydbt
  3. Insight on autopilot

    Agentic BI & Reporting

    Build governed LangGraph reporting agents that query your semantic layer, validate SQL, explain KPI movement, and deliver Slack-native narratives.

    Six-agent LangGraph workflows for planner, SQL, validation, execution, visualization, and narration
    BigQuery, Snowflake, or Postgres integration through MCP with auditable tool calls
    80-150 question eval suites and validation gates for CFO-grade reporting
    LangGraphMCPBigQuerySnowflake
  4. Hard-to-get data

    Web Scraping & Automation

    Collect structured data from dynamic and protected sources with browser automation, proxy strategy, and production-grade delivery.

    Playwright and Selenium workflows for dynamic and protected targets
    Proxy-aware routing, retry orchestration, and anti-detection handling
    Structured parsing and validation for usable downstream data
    PlaywrightSeleniumScrapyProxy
  5. Scale without waste

    Cloud Cost Optimization

    Reduce cloud waste while protecting delivery speed through workload analysis, right-sizing, scheduling, and targeted re-architecture.

    Spend visibility tied to workloads, teams, and business pressure
    Right-sizing, scheduling, and storage changes that create durable savings
    Architecture recommendations that protect reliability while lowering waste
    AWSGCPAzureDocker
  6. Legacy to leverage

    Platform Modernization

    Modernize brittle data and integration stacks into platforms that support reporting, automation, and AI delivery with less operational drag.

    Warehouse and integration contracts that are easier to extend safely
    Migration sequencing that protects live reporting and operations
    Deployment, rollback, and support patterns teams can sustain
    FastAPIPostgreSQLS3Cloud Run
  7. Website operations

    Managed Web Infrastructure

    Launch and operate business websites with a clear technical owner for deployment, maintenance, and improvement.

    Domain and DNS configuration
    Hosting deployment, SSL, and business email setup
    Backups, maintenance, upgrades, and performance optimization
    CloudflareVercelAWSGCP

Verified review signal

5.0 · 71 reviews on Upwork

Chod S.

5.00 / 5

Data Extraction & Automation Engineer for Large Document Repository

Chris K.

5.00 / 5

FT Platform Phase #2

"Great backend developer, highly recommend!"

Gilad B.

5.00 / 5

Phase 0: Design a granular data schema and structure, and full tool flow

"Very knowledgeable and professional. Good communication"

Engagement models

Ways to work with Van Data Team

Choose the engagement shape that fits your team, then start with a free call.

Strategy Sprint

Scope and de-risk

Validate the workflow before a bigger build.

Typical outputs

Discovery
Workflow audit
Architecture direction
Quick-win backlog
Delivery estimate
Book Free Call

Production Build

Ship the system

Recommended

Best for business-ready AI, automation, or data delivery.

Typical delivery

End-to-end delivery
Testing and deployment
Docs and handoff
30-day optimization
Weekly reporting
Talk Through Build

Embedded Partner

Senior support

Ongoing support inside complex AI or data roadmaps.

Typical support

Priority response
Architecture support
Performance tuning
Ops improvements
Flexible sprint execution
Book Partner Call
FAQ

Questions teams ask before they reach out

Straight answers on what Van Data Team builds, who it fits, and how projects start.

What does Van Data Team build?

Van Data Team builds AI agents, reporting workflows, data pipelines, automation systems, and modernization work for teams that need production-ready delivery.

Who is the best fit for Van Data Team?

The strongest fit is a team with a real workflow bottleneck, a delivery owner on the client side, and a need for senior implementation rather than slideware.

Can you work inside an existing stack?

Yes. Many engagements start from an existing stack that needs stabilization, better observability, or a new AI and data layer added on top.

How do projects usually start?

Projects usually start with a scoped conversation, a workflow review, or a short strategy sprint that clarifies the bottleneck, risks, and recommended next step.

Why work with a Vietnam-based delivery partner?

A Vietnam-based delivery model can keep overhead lean while still giving global teams senior ownership, strong communication, and timezone overlap that supports steady delivery.

Free strategy session

Get a 30-minute AI and data consultation

Bring the current process, blockers, and decision pressure. The output is a practical next-step plan, not a vague sales call.

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