Build the Future
with AI Precision
Strategic AI & Software Partner
Based in Hangzhou, China and operated by Hangzhou Xingzhoudu Technology Co., Ltd., DevStudio AI is a senior engineering team — many ex-Alibaba — building production-grade AI for cross-border startups and AI-transitioning enterprises. We have delivered 20+ projects for 10+ clients, targeting a first production milestone within 45 days of confirmed scope. We reply in writing within one business day and work async-first across time zones. We deliver project-based engagements at $14k–$85k over 4–10 weeks, every project shipping with three engineering commitments: Eval Week 1, a 6-month QA window, and a quarterly Token Audit. Entry product: Paid Scoping at $700–$2,800 over 1–2 weeks — about one in four scopings recommends not building, which is the value. Last updated: 2026-06-18.
Why DevStudio
Hangzhou-based, ex-Alibaba senior engineering team. Project rate $14k–$85k over 4–10 weeks, with a written reply within one business day and async-first delivery. Three engineering commitments make us cleanly different from generic outsourcing shops — written into every contract before any code is shipped.
Eval Week 1
At least 200 reference cases with expected outputs and a CI-gated scoring rubric land in the first sprint. Accuracy is measured from day one, not promised. No production code merges until Eval pass-rate clears the agreed threshold.
6-Month QA Window
Every project includes a six-month warranty period for production fixes. Customer keeps the source code, deployment docs, and runbook on day one of handover — we are paid to keep it healthy, not to keep you locked in.
Quarterly Token Audit
Token routing, caching, and model selection are re-evaluated every 90 days against the eval set. Monthly run-rate stays predictable as corpus and traffic grow — no silent margin erosion when the model market shifts.
Paid Scoping — $700–$2,800, 1–2 weeks
A fixed-price feasibility engagement. Written go/no-go, 50-item readiness checklist, Eval plan, and unit-cost model — before any build engagement is signed. About one in four Scopings recommends not building. The fee credits 100% toward a build engagement if you proceed.
Industries we have shipped against
Anonymized industry patterns, not named clients. We ship production AI for these eight verticals from our Hangzhou engineering team.
- Tech
- Fintech
- Healthtech
- E-commerce
- SaaS
- Manufacturing
- Logistics
- Education
How We Deliver
Five sequential phases from kickoff to handover. Each phase ends with a written deliverable and a working demo, so you always know exactly where the engagement stands.
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Paid Scoping
Week 0 — 1–2 weeksDiscovery, data readiness, architecture sketch, eval plan, cost model, written go/no-go. Either side can walk away after this phase with all four artifacts.
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Eval Set Construction
Week 1 — 1 week200+ reference cases co-built with your domain owner. Eval pipeline runs in CI on every change so accuracy regressions surface within minutes, not weeks.
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Build & Integrate
Week 2 — 7 (typical)Two-week increments, each ending with a demo against agreed acceptance criteria and a written changelog. Tools, retrieval, model routing, and observability wired together.
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Hardening & Pilot
Week 7 — 9 (typical)Performance profiling, security review, alerting tuned to the SLO, runbook drafted. Shadow-mode pilot under human review until eval pass-rate clears the production threshold.
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Handover & Operate
Week 9 — 10 + 6-month warrantyFull source code, infrastructure-as-code, runbook, and on-call escalation path delivered. 6-month QA window with quarterly Token Audit so unit cost stays predictable as traffic grows.
Industries We Serve
Patterns we have shipped across pragmatic, outcome-focused engagements.
E-commerce & Retail
AI customer support, recommendation engines, content automation.
SaaS & Platforms
MVP-to-Series-A delivery, multi-tenant infrastructure, agentic workflows.
Manufacturing & Supply Chain
Workflow automation, document intelligence, ERP integrations.
Professional Services
RAG-based knowledge bases, internal copilots, audit-grade compliance.
Education & EdTech
AI tutors, content generation, assessment automation.
Logistics & Operations
Multi-agent orchestration, dispatch automation, anomaly detection.
Anonymized industry patterns from our delivery history. Specific case studies are published with client permission only.
Full-Stack, AI-Enhanced
From MVP to enterprise-scale systems, every project benefits from our AI-powered workflow.
Web & App Development
Responsive websites, enterprise web applications, and cross-platform mobile apps with AI-assisted development.
AI Agent & Workflow
Custom AI agents, RAG knowledge bases, and automated workflows that become your productivity engine.
SaaS & Custom Systems
CRM, ERP, OA systems with AI-powered automation, analytics, and intelligent workflows.
Stay ahead with AI Trends
How Much Does AI Agent Development Cost in 2026?
AI agent development cost in 2026 typically ranges from $15,000–$40,000 for a simple workflow agent , $40,000–$120,000 for a production multi step agent with integrations , and $120,000–$400,000+ for an enterprise multi agent system with advanced orchestration, compliance, SSO, monitoring, and service level expectations.
How Much Does RAG Knowledge Base Development Cost?
RAG knowledge base development cost in 2026 typically ranges from $15,000–$40,000 for a basic single source RAG system , $40,000–$120,000 for a production multi source knowledge assistant , and $120,000–$300,000+ for an enterprise RAG platform with access control, real time sync, evaluation, monitoring, and compliance requirements.
SaaS MVP Development: Process, Cost, and Timeline
A focused SaaS MVP usually costs $15,000–$80,000 and takes 8–16 weeks when it includes authentication, one core workflow, a dashboard, basic admin, billing or payment setup, deployment, and QA.
Top 5 Questions Before You Reach Out
Quick answers to the things prospects ask us most. See the full list on the FAQ page.
What makes AI agent development different from traditional development?
How is data security ensured in AI projects?
How are AI project prices evaluated?
What AI tech stacks do you support?
What post-delivery support do you provide?
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