Resources and Sitemap
Browse the canonical public pages for Van Data Team services, delivery examples, and implementation notes.
Core pages
Main routes
Start with the primary pages Google should understand as the site structure.
Services
All service pages
Canonical service pages for AI agents, data engineering, reporting, automation, cloud cost, and platform modernization.
- AI Agent DevelopmentVan Data Team builds production ready AI agents with LangGraph, CrewAI, and Python, from workflow audit to deployment. Book a free 30 minute consultation.
- Data Pipeline DevelopmentVan Data Team delivers expert data pipeline development services, engineering scalable, production grade ETL and ELT pipelines with Airflow, dbt, and Kafka. Ship in 2 to 6 weeks with total ownership.
- Agentic BI ReportingVan Data Team builds governed agentic BI reporting systems with LangGraph, MCP, semantic layers, validation agents, eval suites, and native Slack delivery.
- Web Scraping AutomationProduction grade Web Scraping & Automation services for mid market teams. Founder led Playwright runtimes, proxy strategy, validators, and warehouse delivery.
- Cloud Cost OptimizationFounder led cloud cost optimization services for AWS, GCP, and Azure teams that need 20 to 60% waste reduction without breaking delivery. Van Data Team ships workload mapped spend audits, right sizing, savings plan strategy, query optimization, and durable FinOps guardrails.
- Data Platform ModernizationFounder led data platform modernization services for teams stuck on legacy ETL, brittle Airflow, warehouse rewrites, or AI readiness gaps. Van Data Team ships workflow mapped audits, staged migration slices, dbt modeling, orchestration upgrades, and durable data contracts in 8 to 16 weeks.
Case studies
All portfolio pages
Canonical portfolio entries covering production delivery examples across the service lines.
- Enterprise Data Warehouse & Analytics PlatformData Engineering - Fortune 500 company
- Enterprise Web Automation & Scraping PlatformWeb Scraping - Market research firm
- Cloud-Native Data Orchestration PlatformCloud Platform - Enterprise financial services firm
- Autonomous Research Agent StackAI Agents - VC-backed SaaS team
- Revenue Operations Automation Command CenterWorkflow Automation - B2B SaaS revenue team
- AI Support Triage & Escalation SystemAI Agents - Global software support team
- Multi-Region Airflow Modernization ProgramCloud Platform - Regional logistics enterprise
- dbt Finance Reporting Acceleration StackData Engineering - Private equity portfolio team
Blog
All articles
Canonical blog posts sorted by publication date for crawler discovery and reader navigation.
- Google DeepMind Launches $10M Multi-Agent AI Safety Initiative: What Production Teams Should LearnJune 12, 2026 - Google DeepMind Launches $10M Multi-Agent AI Safety Initiative is a June 2026 funding call for research into risks that emerge when many AI agents interact, delegate, negotiate, use tools, and transact online.
- Claude Fable 5 vs GPT 5.5 vs Gemini 3.5 Flash ThinkingJune 11, 2026 - Claude Fable 5 vs GPT 5.5 vs Gemini 3.5 Flash Thinking should be compared with real numbers first: token price, context window, output limits, benchmark signals, latency profile, and the production risk of each workload.
- Claude Fable 5: A Practical Guide for Production AI WorkflowsJune 11, 2026 - Claude Fable 5 is a practical fit for teams that want AI agents to handle longer coding, reporting, and operations workflows, but only when the work is scoped, observable, and reviewable.
- Database Query Plan Regression Review for Production TeamsJune 6, 2026 - A database query plan regression review is the safest way to decide whether a changed execution plan is a harmless optimizer choice or a production risk.
- Optimizing Docker Image Build Times: A Practical Guide for Production TeamsJune 3, 2026 - Optimizing Docker image build times means reducing how long it takes to produce a reliable container image without breaking runtime behavior, reproducibility, or deployment safety.
- Event-driven Architecture With Message Queues: A Practical GuideJune 3, 2026 - Event-driven architecture with message queues is a production pattern where services publish events or tasks to a broker, and independent consumers process them asynchronously.
- Building AI agents with Model Context Protocol (MCP): A Practical Guide for Production TeamsMay 27, 2026 - Building AI agents with Model Context Protocol (MCP) means designing an agent that can connect to external tools, services, and data sources through a standard protocol.
- Customer onboarding journey for B2B SaaS FrameworkMay 27, 2026 - Customer onboarding journey for B2B SaaS examples Customer onboarding journey for B2B SaaS framework Customer onboarding journey for B2B SaaS workflow Customer onboarding journey for B2B SaaS best practices how to use Customer onboarding journey for B2B SaaS what is Customer...
- AI Agent Incident Response Playbook: A Practical Guide for Production TeamsMay 24, 2026 - An AI agent incident response playbook is an operating guide for handling failures in agent workflows. It defines how teams detect incidents, classify severity, contain unsafe behavior, escalate to humans, review logs, fix root causes, and improve the agent before returning...
- GPT 5.5 vs Claude Opus 4.7: practical comparison for production teamsMay 18, 2026 - Teams comparing GPT 5.5 vs Claude Opus 4.7 should start with the workflow, not the model name. A useful comparison tests both models against real tasks, scores the outputs, tracks review effort, and identifies where guardrails or human escalation are required before...
- ReAct agent: a practical guide for production teamsMay 18, 2026 - Internal Links: AI agent development Agentic BI and reporting Autonomous research agent case study AI agents with human review AI agent ops playbook External Links: Original ReAct paper Google Research ReAct overview OpenAI function calling documentation OpenTelemetry GenAI...
- GPT-5.4 vs Claude Opus 4.7: Which Model for Production AI Agents?April 16, 2026 - Neither GPT-5.4 nor Claude Opus 4.7 wins in every situation. The production decision is not which model to pick -- it's which tasks go where.
- Claude Opus 4.7: What Changed and When to Use It for Production AI AgentsApril 16, 2026 - Opus 4.7 is a production upgrade, not just a benchmark chase. Here is what adaptive thinking, cross-session memory, and a 13% coding lift mean for teams running AI agents today.
- AI Agent Development Services: What Changes Between a Prototype and ProductionApril 10, 2026 - Production AI agent work is not only about prompt quality. It is about tool permissions, review checkpoints, failure handling, and operational ownership after launch.
- Human Review Loops for Production AI AgentsApril 7, 2026 - The strongest human-in-the-loop design does not ask people to review everything. It places review at the moments where risk, confidence, and customer impact actually change the decision.
- Production AI Agent Ops and Human Escalation PlaybookApril 7, 2026 - The difference between an impressive agent demo and a production workflow is rarely the model alone. It is the operating system around escalation, review, tooling, and runtime visibility.
- Choosing Batch vs Streaming for Modern Data PipelinesApril 6, 2026 - Teams rarely need streaming because it sounds modern. They need it when the downstream workflow truly breaks without low-latency data.
- Data Engineering Partner vs In-House Team: How Buyers Should Think About the TradeoffApril 5, 2026 - The real decision is rarely partner or in-house forever. It is about who can create momentum fastest without leaving the business with a fragile handoff later.
- Resilient Web Scraping Pipelines with Monitoring and FallbacksApril 5, 2026 - Most scraping failures do not come from the parser alone. They come from weak runtime design around browser behavior, retry policy, proxy health, and downstream validation.
- Tutorial: Turning an Ops Brief into an Executable Automation ScopeApril 3, 2026 - Most automation requests start as a symptom, not a scope. The job is to translate that symptom into a workflow contract a team can actually build, test, and launch.
- Agentic BI for Operations Teams: When Dashboards Need to Trigger DecisionsApril 2, 2026 - Operations teams rarely need more charts alone. They need reporting that points to the next action, highlights exceptions, and fits the pace of the workflow.
- Web Scraping Automation for Protected Sites: What Actually Keeps Collection StableMarch 30, 2026 - Reliable scraping is less about one clever script and more about a monitored collection system with browser strategy, retries, proxies, and failure visibility built in.
- Cloud Cost Optimization for Data Platforms: The Guardrails That Actually Reduce SpendMarch 26, 2026 - The fastest cost wins usually come from operating discipline, not heroic re-platforming. Good guardrails make waste visible before the monthly bill does.
- Data Platform Modernization for AI Readiness: What to Fix Before You Add LLM WorkloadsMarch 22, 2026 - AI readiness rarely starts with the model. It starts with whether the platform can move clean data, trace decisions, and support new workloads without breaking old ones.
- Why US Companies Are Moving Data Engineering to VietnamFebruary 18, 2026 - US teams are moving more data engineering work to Vietnam because they want senior execution, not agency overhead.
- Designing AI Agents with Human Review Loops That Actually WorkFebruary 12, 2026 - The best human-in-the-loop design does not ask people to review everything. It asks them to review the moments where confidence, risk, and business impact matter.
- Building Real-Time Data Pipelines with Apache KafkaFebruary 6, 2026 - Real-time pipelines only create value when they are observable, replayable, and designed for the downstream decisions they serve.
- A dbt + BigQuery Playbook for Faster Warehouse DeliveryJanuary 30, 2026 - Fast warehouse delivery comes from clearer contracts, leaner models, and deployment habits that keep transformation logic easy to reason about.
- How Data Teams Reduce AWS Costs by 60% Without Slowing DeliveryJanuary 24, 2026 - The best AWS cost optimization work removes waste while improving clarity, reliability, and architecture discipline.
- Scaling Playwright Scraping with Proxies, Retries, and Fewer Nightly FailuresJanuary 16, 2026 - Stable scraping systems are built around fallback paths, retry logic, and operational visibility, not only around browser automation scripts.
- When to Modernize a Legacy Data Platform for AI ReadinessJanuary 8, 2026 - AI readiness rarely starts with a new model. It usually starts with fixing the data platform issues that make retrieval, reporting, and workflow automation unreliable.