Ship AI Features That Work in Production.
We help engineering teams go from AI prototype to production-ready system — the right models for your use case, hybrid architectures, developer tooling, and the infrastructure to run it reliably at scale. No ML platform hire needed.
Sound Familiar?
AI works in the demo — then hits a wall in production. The models, the infrastructure, the team workflows: there's a lot to get right between a working prototype and something that ships.
“Our AI demo never made it to production”
The proof of concept works on a laptop. But nobody knows how to deploy it reliably, scale the inference, handle failures, or keep quality consistent once real traffic hits. The gap between demo and production is wider than it looks.
“We don't know which models to use”
Frontier APIs, open-source models, self-hosted inference, fine-tuning — the choices multiply. Without clear criteria, teams default to whatever worked in the demo and never revisit it.
“AI should be speeding us up, but it isn't”
Developer tooling, coding assistants, internal agents — the value is obvious, but integrating them into real workflows takes time your team doesn't have.
Fixed-Price Packages
No hourly billing surprises. Pick a package, get a clear scope, and know exactly what you're paying before we start.
AI Infrastructure & Strategy Audit
1 week
$2,500
A focused review of your AI stack and how it can better serve your goals — model selection, architecture patterns, infrastructure gaps, and where to invest next. Includes a clear, prioritized action plan.
- ✓AI stack & model selection review
- ✓Architecture assessment (hybrid routing, self-hosted vs. API)
- ✓Developer AI tooling & productivity opportunities
- ✓Inference infrastructure & observability gaps
- ✓Security posture check
CI/CD & Model Deployment Pipeline
1-2 weeks
$5,000
A production-grade pipeline for your application — and your models. From code push to live across dev, staging, and production, including rolling out self-hosted inference if you run it. We use the right tool for your stack.
- ✓Automated build & test pipeline
- ✓Multi-environment deployments (dev/staging/prod)
- ✓Self-hosted model rollout (vLLM / Ollama) where needed
- ✓Infrastructure as Code (Terraform, Helm)
- ✓Monitoring, alerting & performance tracking
AI Feature Sprint
2 weeks
$7,500
Add production-ready AI capabilities to your product — using the right mix of frontier and open-source models for your use case — shipped, deployed, and instrumented so you can see how it's performing.
- ✓Requirements scoping & model selection
- ✓Architecture design (frontier + open-source as needed)
- ✓Inference infrastructure setup (vLLM / Ollama / API)
- ✓RAG / LLM / agent integration development
- ✓Observability & production deployment
Monthly Retainer
Ongoing
$3,000/mo
Ongoing AI implementation support — model selection, infrastructure improvements, new feature development, and developer tooling — like having a senior AI engineer on your team without the full-time commitment.
- ✓15 hours/month of AI & infrastructure work
- ✓AI feature development & iteration
- ✓Model selection & architecture guidance
- ✓Developer tooling & productivity improvements
- ✓CI/CD, deployment, and infrastructure improvements
- ✓Security updates & patching
AI Implementation, End to End
Every team's AI needs are different. We build hybrid architectures, integrate frontier and open-source models, and create the infrastructure and tooling that makes AI work in your specific product.
[ Hybrid Routing ]
Right model for each task
Frontier APIs for complex reasoning and judgment; open-source models for high-volume, well-defined tasks — or wherever data privacy or latency requirements make self-hosting the right call. Matched to your workloads, not a one-size-fits-all default.
[ Self-Hosted Inference ]
Own your models, own your data
Run open-source models on your own hardware or cloud GPUs. Predictable inference costs, full control of your stack, and your proprietary data stays within your infrastructure. Production-grade with autoscaling, monitoring, and zero vendor dependency.
[ AI Observability & Production Foundations ]
Measure what matters
Every request traced: quality, latency, token usage, and cost per feature. It all runs on the production infrastructure we've always built — Kubernetes, CI/CD, Terraform — so your AI stack stays reliable, observable, documented, and yours to own.
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.
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