About Us
AI implementation consulting for teams that build products, not ML platforms. We design and build AI systems that ship to production — hybrid architectures, the right models for your use case, developer tooling, and the infrastructure to run it reliably.
Why We Exist
Most small and mid-size engineering teams are great at building their product. But running AI in production — choosing the right models, building reliable inference, integrating developer tooling, 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 open-source models like Llama and Qwen running on your own infrastructure. You get senior-level AI implementation expertise at a fraction of a full-time hire — with documentation and handoff so your team can maintain it going forward.
We've built production AI systems, designed hybrid architectures, boosted developer productivity with AI tooling, and shipped features that stay reliable at scale. We know what good AI implementation looks like — and we know what it takes to get from a working demo to something that runs in production.
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
AI implementation built on production-grade foundations — all hands-on experience shipping real systems.
[ AI Infrastructure ]
Hybrid architectures, frontier and open-source model integration, self-hosted LLM inference, agent orchestration, RAG, developer productivity tooling, and production observability. We build AI into your product so it ships to production and keeps working.
Hybrid AI & Inference
Hybrid Model Routing
Frontier APIs (Claude, GPT) for reasoning, open-source models (Qwen, Llama) for volume and privacy — matched to your workloads and constraints.
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, RAG pipelines, and task-queue control planes — the right model for each step, in the right architecture.
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
Prometheus, Grafana, OpenTelemetry, Langfuse — tracking quality, latency, token usage, and cost per request.
Let's Talk About Your AI Implementation
Book a free 30-minute call. We'll discuss your AI goals, where you are today, and what it takes to get something reliable into production.
Book a Free Call