From Prototype to Production —
AI Systems That Actually Ship
We build bespoke AI pipelines for startups and scaleups. GPU compute orchestration, LLM integration, agent architecture, and synthetic media — engineered for production, not demos.
What We Build
Across every layer of the AI stack — compute, model, pipeline, and deployment.
GPU Pipeline Engineering
End-to-end GPU compute pipelines — from cloud provisioning and orchestration to inference serving. We design for cost efficiency and throughput, not just proof-of-concept.
LLM Integration & Agent Architecture
Production-grade LLM integration with structured outputs, tool use, and memory. We build reliable agent systems — not chatbot demos — grounded in real business workflows.
Custom AI Pipeline Development
Multi-stage AI pipelines connecting data ingestion, model inference, post-processing, and delivery. Built to be repeatable, observable, and swap-friendly as models evolve.
Synthetic Media Systems
AI-generated image, video, and audio pipelines for advertising, content, and product teams. We deliver the compute architecture and workflow tooling to run these in production.
Cloud AI Infrastructure
AI workloads on AWS, GCP, or Azure — model hosting, auto-scaling, cost monitoring, and IAM. We design for the growth curve, not just the launch date.
MLOps & Model Deployment
CI/CD for models: versioning, canary rollouts, drift monitoring, and rollback. We bring software engineering discipline to the model lifecycle.
Technologies & Tools
Why Cipher Projects
We work like an embedded engineering team — not a vendor handing over a slide deck.
Forward-Deployed in Asia-Pacific
Our engineers are embedded in Vietnam, Singapore, and Australia — working in your timezone, syncing daily, and moving at startup pace. No handoffs across 12 time zones.
Production-First Engineering
We care about reliability, observability, and cost — not just whether the demo worked once. Every pipeline we build is designed to run unattended at scale.
Startup-Paced Execution
We scope MVPs tightly, ship fast, and iterate. Most applied AI engagements go from brief to working pipeline in 2–4 weeks, not 6-month waterfall projects.
Model-Agnostic Architecture
Models change fast. We architect pipelines so swapping the underlying model is a config change, not a rewrite — protecting your engineering investment as the landscape evolves.
Ready to Build?
Tell us what you're trying to make. We'll scope it, ship an MVP, and iterate from there.
Get in Touch