AI / LLM Agents · Full-Cycle Delivery

Architecting, Building, and Deploying Enterprise-Grade AI and Agentic Systems.

From architecture to deployment, we integrate LLMs, RAG, and agentic workflows directly into your production environments.

Built for teams ready to execute. We write robust code, configure resilient infrastructure, and deliver scalable solutions. You work directly with a compact team of senior engineers — no sales layer, no junior pyramid.

Request a SolutionClient Cases
Core Engines

Three engines, proven in production.

Knowledge, voice and agents — the underlying machinery we adapt to each client's domain, taking AI from a demo to a dependable system.

01

Knowledge Engine

Makes your private data AI-ready

Enterprise knowledge sits buried in reports, wikis, manuals and databases that LLMs cannot reliably use. The Knowledge Engine turns that raw corpus into a structured, retrieval-ready knowledge base — deployed on-premises or in your private cloud, so sensitive data never leaves.

On-prem / private cloudSource-cited answersDomain concept modelingTables · PDFs · legacy exports
600 GB+of industrial biotech data structured into one production knowledge base
Proven in production — leading genomics company, Greater China
  1. 1

    Ingest & Parse

    Documents, tables, images and legacy exports are parsed into clean, structured elements.

  2. 2

    Structure & Model

    Domain concepts, terminology and scenarios are distilled into an organised knowledge model.

  3. 3

    Index for Retrieval

    Content is chunked, embedded and indexed so every answer is grounded in the right source.

  4. 4

    Serve to Agents

    A retrieval layer any LLM or agent can query — with citations back to the original document.

02

Voice Engine

Real-time voice, an agentic engine underneath

Real time is what makes voice work: the user hears a reply beginning, not a spinner. The Voice Engine streams recognition and synthesis both ways and stays interruptible at every moment — while underneath, the agentic engine does the real work: calling tools, tracking device state, retrieving knowledge. Voice is the interface; the agent is the application.

WebRTC transportStreaming ASR 300–400 msFirst audio ≈250 msCode-switched recognitionMillisecond telemetry
< 1 secondfrom end of speech to the agent's first word in direct interaction — 300–400 ms recognition, ~250 ms to first audio, interruptible throughout
Proven in production — global prosumer audio brand
  1. 1

    Full-Duplex Streaming

    Recognition and synthesis stream both ways over WebRTC — no stage waits for another to finish.

  2. 2

    Barge-In & Recovery

    Interrupt mid-answer and audio halts instantly, context trimmed to what you actually heard — while a cough or filler word won't derail the reply.

  3. 3

    Code-Switched Hearing

    Recognition carries your industry's vocabulary — "compressor threshold" inside a Chinese sentence, heard correctly the first time.

  4. 4

    Agentic Engine Underneath

    Beneath the voice runs the agent engine — tool calls, live device state, knowledge retrieval. Talking to the product is operating the product.

03

Agent Engine

Decomposes complex requests, executes accountably

Real business requests are rarely a single question, and an agent that can operate enterprise systems has to be trustworthy. The Agent Engine pairs intent decomposition with a disciplined execution harness: typed tools, live state awareness, propose-before-execute, and a full audit trail for every decision.

Typed tool schemasPropose-before-execute guardrailsBounded reasoning loopsLive decision tracing
Fortune 500container shipping group using it in production for live fleet queries
Proven in production — Fortune Global 500 container shipping group
  1. 1

    Intent Classification

    A single request is decomposed into the multiple intents it actually contains.

  2. 2

    Plan & Propose

    A reason-act loop determines the tools each intent needs; non-routine actions are proposed for confirmation before execution.

  3. 3

    Validated Execution

    Every tool call is checked against a typed schema and scope validation, combined with live system state, inside a bounded loop.

  4. 4

    Traceable Synthesis

    Results are composed into one grounded answer; every step's parameters, results and latency are on record.

Delivery Models
  • Fully Custom BuildBuilt from scratch around your business process
  • Framework ImplementationFaster delivery on proven stacks like Dify and LangGraph
  • Rapid Proof of ConceptTwo-week feasibility sprint, fixed fee, clear go / no-go

A live demo beats any deck.

20 minutes online, running on real systems. Bring your hardest question.

Book a live demo
Client Cases

Production Deployments

Real-world AI agent implementations across logistics, biotech, and hardware — all running in production.

Client names shared in reference calls, under NDA.

Global Shipping EnterpriseLogisticsIn Production

Global Shipping Enterprise

Fortune Global 500 container shipping group

CHALLENGE

Container fleet information was scattered across multiple legacy systems, making it difficult to answer customer queries promptly.

SOLUTION

An AI agent that interprets user queries, orchestrates internal search tools and databases, and retrieves real-time vessel data — displaying geographic locations directly on an interactive map.

Biotech Emerging UnicornBiotechIn Production

Biotech Emerging Unicorn

Leading genomics company in Greater China

CHALLENGE

Pre-sales teams were spending countless hours answering repetitive questions about sequencing processes, sampling guidelines, and product details.

SOLUTION

A specialized agent trained on all internal workflow documents and sales collateral. It responds instantly and accurately to common client inquiries, reducing turnaround times drastically.

Pro Audio ManufacturerAI HardwareIn Production

Pro Audio Manufacturer

Global prosumer audio brand headquartered in Shenzhen

CHALLENGE

Pro-grade audio equipment involves complex parameters, creating a high barrier to entry and forcing creators to spend hours on tedious post-processing.

SOLUTION

We upgraded their hardware with an agent-powered assistant. Users can now configure scenes via natural language and use smart tools to streamline their entire creative workflow.

Technical Capabilities

Full-Stack Coverage, From Dev to Prod

From agentic loops and long-term memory to evals, guardrails and deployment — production-grade engineering across the modern AI stack.

Agent Engineering

Agentic Loop DesignAgent HarnessesMulti-Agent OrchestrationLangGraph / LangChain

Context & Memory

Long-Term MemoryContext EngineeringAgentic RAG / GraphRAGMCP Tool Integration

Reliability & Deployment

Agent Evals & ObservabilityGuardrails & Human-in-the-LoopDocker / KubernetesCI/CD

Models & App Stack

Mainstream LLMsDomestic & Self-Hosted ModelsFastAPI · Next.jsPostgreSQL + pgvector
How We Work

We write production code, not just prototypes.

We prioritize code quality, test coverage, documentation, and system maintainability. We build enterprise-grade implementations, not mere proofs of concept.

  • Business fit first; no assumed technical silver bullets.
  • Emphasis on answer quality, responsibility boundaries, and traceability.
  • Retaining human judgment to ensure automation has appropriate guardrails.
  • Human review, logging, permissions and rollback retained on critical paths.
01

Discovery

Align on goals, constraints, decision frameworks and risk requirements; map processes, roles and data as they stand.

02

Architecture

Define the use case, data flow, tech stack, system architecture and integration points.

03

Development

Write code, establish testing protocols, configure infrastructure, integrate systems and optimize performance.

04

Validation

Deploy to production, run stability tests, and facilitate user acceptance testing.

05

Operations

Continuous monitoring, issue resolution, feature expansion, and team training.

Getting Started

A low-risk first step.

Our Team

Engineering-Driven Veterans

With over a decade of industry experience, we are a collective of tech veterans dedicated to eliminating the friction of enterprise digitalization and AI automation.

01

Exquisite Service

We don't just deliver software; we deliver an experience. Our commitment to service excellence is woven into every interaction.

02

Co-Creation

We work alongside our clients as one unified team, aligning our engineering culture with your business objectives.

03

Long-Term Partnership

Transformation is a journey, not a destination. We provide enduring support as your trusted long-term technical partner.

Founder — Charles Lei · B.S. & M.S. in Computer Science, Zhejiang University (QS Top 50) · MBA, Boston University · 10+ years delivering enterprise solutions

Global Presence: Hangzhou • Hong Kong • Singapore
Contact

Bring one pain point to a 30-minute call — we'll bring a sketch of the solution.

We'll look at your existing workflows, data readiness and deployment requirements together, then judge whether AI belongs there, what phase one should be, and how to measure the result.

contact@keyzen.com.cn

We reply during business hours. English and Chinese are both welcome.