Custom Software
Web apps, WeChat mini-programs, iOS / Android apps and admin consoles delivered as one system — one set of requirements, every platform.
See case studies
WebMini-program
AI-native engineering · every platformFrom idea to product,
From idea to product,
at AI-native speed and quality
Taylent Labs builds custom software and takes AI applications to production: web, mini-programs and mobile apps, with LLM / RAG / agent systems that go beyond the demo. Fast, transparent and built to maintain.
taylent-labs · workspace
// from requirements to launch, end to end
const product = await taylent.deliver({
idea: "your business idea",
platforms: ["web", "miniapp", "app"],
ai: { rag: true, agent: true },
});
// ✓ shipping in iterations · every build demoableRequirements parsed · drafting prototype
On-time launch · SLA support
- Projects Delivered
- 50+
- Projects Delivered
- Industries Served
- 10+
- Industries Served
- Service Uptime
- 99.9%
- Service Uptime
What we do
One team across the whole delivery chain
From custom builds to applied AI, from consulting to long-term operations — compose what you need, no over-promising.
Our Product
Taylent AI Gateway
One API key for every leading model
An AI API gateway compatible with both OpenAI and Anthropic formats, built for coding agents like Claude Code and Codex. Enterprise-grade nodes, pay-as-you-go billing, minutes to integrate.
- All the leading models: GPT, Claude, Gemini and more
- Low-latency enterprise nodes with stable high concurrency
- Pay-as-you-go with real-time, transparent usage and billing
- Works with official SDKs — just swap the base_url
terminal — set up Claude Code
# two env vars to wake up frontier models$ export ANTHROPIC_BASE_URL=https://ai.taylent.com$ export ANTHROPIC_AUTH_TOKEN=sk-tay-****✓ Claude Code connected to Taylent AIHow we work
A transparent five-step process
Every step has named deliverables and sign-off points. Progress stays visible — no black-box development.
- 01
Discovery
A free first conversation to map goals and scope — feasibility verdict the same day.
Deliverable: Requirements brief - 02
Proposal & Quote
A technical proposal with milestones and transparent pricing — costs clear at a glance.
Deliverable: Proposal · quote - 03
Kickoff
A dedicated squad forms after signing; prototypes and visual design lead the way.
Deliverable: Prototype · designs - 04
Agile Iterations
Short delivery cycles — every build is demoable, open to feedback and course-correction.
Deliverable: Working builds - 05
Launch & Support
Deployment, data migration and training, then long-term support and iteration.
Deliverable: Launch · SLA support
Ways to work together
Three engagement models
Different projects call for different arrangements — and you can switch models mid-way as needs change.
Fixed-Scope Delivery
Fixed scope, fixed quote, milestone payments — for well-defined, complete projects.
- Price locked once scope is set
- Pay on milestone acceptance
- Warranty period included
Agile Iterations
Pay per iteration with a rolling scope — for evolving products and new bets.
- Re-steer every iteration
- Pause or wrap up anytime
- Every build is demoable
Embedded Engineers
Senior engineers join your team on a monthly basis — to reinforce an existing squad.
- Deep in your workflow
- Knowledge stays with your team
- Scale headcount up or down
Why choose us
How we compare
No option wins everywhere — but for most small-to-mid projects, we hit the best balance of speed, cost and quality.
| Taylent Labs | Traditional Outsourcing | In-House Team | |
|---|---|---|---|
| Time to start | Team assembled in 1–2 weeks | Lengthy onboarding process | 1–3 months of hiring |
| AI engineering | AI-native workflow, built-in LLM experience | Depends on the vendor | Learned from scratch |
| Cost structure | Pay as needed, transparent quotes | Change orders add up | Fixed long-term payroll |
| Transparency | Demoable every iteration, visible progress | Often a black box | Fully in your control |
| Long-term upkeep | SLA support + full documentation handover | Hard to reach after contract | Depends on staff retention |
A general, experience-based comparison — happy to assess against your actual situation.
What we've built
Selected case studies
Delivery work across enterprise software, retail, healthcare and manufacturing (sample showcases, updated continuously).
EnterpriseSample
AI Knowledge-Base Assistant
RAG-powered internal Q&A: documents chunked and indexed automatically, answers cite their sources, accuracy tuned through dedicated evaluation.
LLMRAGNext.js
RetailSample
Mini-Program Store & Membership
A WeChat mini-program store with stored-value membership and referral growth, managed from one admin console for daily operations and campaigns.
Mini-programNode.jsMySQL
HealthcareSample
Clinic Management System
Appointments, electronic records and follow-up reminders in one flow, with multi-site data unified and separate doctor / patient experiences.
VueGoPostgreSQL
What we build with
A battle-tested stack
Neither chasing hype nor stuck in the past — chosen per use case, balancing velocity with long-term maintainability.
- React
- Vue
- Next.js
- TypeScript
- Flutter
- WeChat Mini-Program
- Electron
- Tailwind CSS
- iOS / Android
- Node.js
- Go
- Python
- PostgreSQL
- MySQL
- Redis
- Docker
- Kubernetes
- LLM / RAG
- Agent Workflows
- 50+
- Projects Delivered
- 10+
- Industries Served
- 99.9%
- Service Uptime
- 24h
- Response Time
Blog
Latest field notes
Hands-on lessons from LLM projects, software delivery and AI coding.
FAQ
Before we work together
How do you price a project?
We start with a free conversation, then deliver a technical proposal with pricing — a fixed quote for fixed scope, or a per-iteration rate. Work starts only after you confirm, and the quote holds as long as the scope does.
How long does a typical project take?
It depends on scope: small MVPs are measured in weeks; complex systems ship in milestone phases. The proposal includes a concrete milestone schedule, not one vague total.
Who owns the code and IP?
You do. On delivery we hand over the full source, documentation and deployment configuration, with IP ownership written into the contract.
What happens after launch?
Defects are fixed free during the warranty period; after that, an SLA support plan covers monitoring, security updates and continued iteration.
Can you add AI to an existing system?
Yes. We integrate LLMs, RAG knowledge bases or agent workflows incrementally into what you already run — no rewrite required.
You code with AI — how is quality assured?
AI accelerates the work, but architecture, code review, testing and final accountability always rest with senior engineers. AI is a force multiplier, not the responsible party.
Let's talk about your next project
A free 30-minute conversation to gauge feasibility, timeline and budget.
Book a Free Consultation