Build and Ship Modern Web Products.
We help teams build websites, web apps, and AI-powered features faster — using modern tools and the right platform for your needs. Services such as Vercel and Cloudflare for speed, EKS when you need more control. No big agency, no full-time hire.
The right platform for your team — not ours.
Not every team needs Kubernetes. A 10-person SaaS product often ships better and faster on services such as Vercel and Cloudflare. We start with your constraints — team size, traffic shape, data requirements, budget — and recommend the platform that actually fits. When you do need EKS, GPU infrastructure, or self-hosted models, we've built that too.
Sound Familiar?
Good ideas stall for the same reasons: not enough bandwidth, unclear tooling choices, and the gap between “working” and “shipped” being wider than expected.
“We need a new site or app but our team is heads-down on the product”
The work is real — a marketing site, an internal tool, a new customer-facing feature — but your engineers are already stretched. Bringing in a big agency means months and a large budget. Hiring takes even longer.
“Our prototype never made it to production”
The demo works. But deploying it reliably, handling real traffic, and keeping it observable — that's a different problem. The gap between prototype and production is wider than it looks.
“We should be moving faster than this”
Modern tools — AI-assisted development, managed platforms, better CI/CD — should be multiplying your team's output. If they aren't yet, setup and integration is the bottleneck.
Fixed-Price Packages
No hourly billing surprises. Pick a package, get a clear scope, and know exactly what you're paying before we start.
Strategy & Technical Audit
1 week
$2,500
A focused review of where you are and what to do next — your tech stack, deployment platform, development workflow, and where AI tooling or infrastructure changes would have the most impact. Includes a clear, prioritized action plan.
- ✓Tech stack & architecture review
- ✓Platform assessment (services such as Vercel and Cloudflare vs. EKS vs. self-hosted)
- ✓AI tooling & productivity opportunities
- ✓Infrastructure & observability gaps
- ✓Quick wins vs. longer-term investments
CI/CD & Deployment Pipeline
1-2 weeks
$5,000
A production-grade pipeline for your application — from code push to live across dev, staging, and production. We deploy to whatever platform fits: services such as Vercel and Cloudflare, or Kubernetes when you need more control. Self-hosted model rollout included if you run inference.
- ✓Automated build & test pipeline
- ✓Multi-environment deployments (dev/staging/prod)
- ✓Platform setup (services such as Vercel and Cloudflare, or EKS)
- ✓Self-hosted model rollout (vLLM / Ollama) where needed
- ✓Monitoring, alerting & performance tracking
Build Sprint
2 weeks
$7,500
A focused two-week build — a new website, web app, or AI-powered feature, shipped to production and handed off with documentation. We scope it together, we build it fast using modern tools, and you own it.
- ✓Requirements scoping & architecture design
- ✓Website, web app, or AI feature development
- ✓AI model integration (frontier + open-source as needed)
- ✓Platform deployment (services such as Vercel and Cloudflare, or EKS)
- ✓Monitoring, observability & production handoff
Monthly Retainer
Ongoing
$3,000/mo
Ongoing development and platform support — new features, site updates, AI integration, infrastructure improvements, and developer tooling — like having a senior engineer on your team without the full-time commitment.
- ✓15 hours/month of development & platform work
- ✓Feature development & iteration (web, app, or AI)
- ✓Architecture guidance & tech stack decisions
- ✓Developer tooling & productivity improvements
- ✓Platform & deployment improvements
- ✓Security updates & patching
Build Fast. Ship to the Right Platform. Keep It Running.
We combine AI-accelerated development with solid engineering fundamentals — so you ship faster and land on infrastructure that fits your team, not just whatever we happen to know best.
[ AI-Accelerated Dev ]
Ship faster with AI in the loop
We use AI throughout our development process — Claude Code, Cursor, AI-assisted code review and testing — so we build websites, web apps, and AI features faster than a traditional team would. We also help your team adopt the same tools: coding assistants, developer tooling, and agent workflows that multiply output.
[ Right-Sized Platform ]
Fits your team, not just our résumé
Services such as Vercel and Cloudflare for fast, low-overhead deploys. EKS and Kubernetes when you genuinely need GPU scheduling, self-hosted models, or enterprise-scale traffic. We recommend what fits — and we've built on all of them.
[ AI Observability & Production Foundations ]
Measure what matters
Every request traced: quality, latency, token usage, and cost per feature. CI/CD pipelines that actually work, infrastructure as code you can maintain, and the monitoring to know when something breaks — regardless of which platform you're running on.
How It Works
Book a Call
Tell us what’s broken, expensive, or missing. 30 minutes, no obligation, no sales pitch.
Get a Proposal
We scope the work, pick the right package, and send you a clear proposal with a fixed price. No surprises.
We Ship It
We do the work, keep you informed, and hand off with documentation so your team can maintain it.
Latest from the Blog
Practical insights on building AI in production — hybrid architectures, model selection, self-hosting, developer tooling, and the infrastructure that keeps it running.
Want a deep technical dive? Read our 8-part series on building a hybrid LLM platform →
The Cost-Efficient AI Stack: Ship AI Features Without the Runaway Bill
Most teams overpay for AI by routing every request to a frontier model. This is the architecture we build instead — hybrid cloud+local routing, self-hosted inference, agent orchestration, and cost-per-request observability — and the single principle that ties it together: send each unit of work to the cheapest model that can do it well.
Building a Hybrid LLM Platform on EKS, Part 5: Serving Local Models with vLLM and KEDA
Part 5 of our hands-on EKS series. We deploy vLLM model servers on the GPU pool from Part 4, load Qwen2.5-7B model weights from Amazon S3 via an init container, and wire KEDA autoscaling that scales replicas with live queue depth and drives GPU nodes to zero overnight.
Building a Hybrid LLM Platform on EKS, Part 7: Observability and Cost Telemetry
Part 7 of our hands-on EKS series. We instrument the TypeScript router with OpenTelemetry, upgrade Prometheus to kube-prometheus-stack for GPU and vLLM metrics, add Grafana Tempo for distributed traces, and wire Langfuse so every request shows its backend, token count, and dollar cost.
Let's Ship Your AI Feature
Book a free 30-minute call. We'll discuss where you are, what you're trying to build, and what it takes to get AI working reliably in production.
Book a Free Call