About Us
AI infrastructure consulting for teams that build products, not ML platforms. We design hybrid cloud+local model architecture that ships AI features to production — and cuts the bill that comes with them.
Why We Exist
Most small and mid-size engineering teams are great at building their product. But running AI in production — choosing models, self-hosting inference, controlling token spend, keeping it observable — isn't their core skill. And it shouldn't have to be.
The problem is that hiring a senior infrastructure or ML platform engineer costs $180K-$250K/year. For a 10-person team, that's a huge commitment for someone who might only be fully utilized for a few months of setup work.
Entuit fills that gap. We bring deep experience across the modern AI stack — from frontier APIs like Claude and GPT to self-hosted open models like Llama and Qwen running on Kubernetes. You get senior-level AI infrastructure at a fraction of a full-time hire — with documentation and handoff so your team can maintain it going forward.
We've built and operated production platforms, designed cloud architectures, and shipped AI systems that stay cost-efficient at scale — hybrid routing, self-hosted inference, agent orchestration, and cost-per-request observability. We know what good AI infrastructure looks like because we've built it — and we know what runaway AI costs because we've cut them.
How We Work
Straightforward consulting. No fluff, no upsells.
Fixed Prices
Every project has a clear price before we start. No hourly billing, no surprise invoices, no scope creep. You know what you're paying and what you're getting.
We Ship, Not Just Advise
We don't hand you a slide deck and walk away. We configure Vercel, set up Supabase, write the Terraform, integrate AI features, and hand you working infrastructure with documentation.
Your Team Owns It
Every engagement includes documentation and a walkthrough so your engineers understand and can maintain everything. We want you to be self-sufficient, not dependent on us.
No Lock-In
We use industry-standard tools and platforms — Vercel, Supabase, GitHub Actions, Terraform. Nothing proprietary. If you stop working with us, everything keeps running.
What We Know
Cost-efficient AI infrastructure, built on production-grade foundations — all hands-on production experience.
[ AI Infrastructure ]
Hybrid cloud+local model architecture, self-hosted LLM inference, agent orchestration, RAG, and cost-per-request observability. We build AI into your product so it ships to production and stays affordable as it scales.
Hybrid AI & Inference
Hybrid Model Routing
Frontier APIs (Claude, GPT) for reasoning, local models (Qwen, Llama) for volume — cutting LLM spend 60–80%.
Self-Hosted LLMs
vLLM and Ollama on Kubernetes, GPU scheduling, and KEDA autoscaling — own your inference end to end.
AI Agents & Orchestration
Multi-agent systems and task-queue control planes that route each step to the cheapest capable model.
Production Foundations
Kubernetes & AWS
EKS clusters, Terraform, GPU infrastructure, cost optimization, networking, and security hardening.
CI/CD & GitOps
Dagger, GitHub Actions, ArgoCD, GitOps workflows, container builds, and multi-environment deployments.
Observability & FinOps
Prometheus, Grafana, OpenTelemetry, Langfuse — tracking tokens, latency, and cost per request.
Let's Talk About Your AI Stack
Book a free 30-minute call. We'll discuss what you're spending on AI today, where a hybrid stack could cut it, and how we can help you get there.
Book a Free Call