Multi-tenant infrastructure for AI agent products.
If you've launched an AI agent product and now need to make it work for many
customers instead of one, I build the multi-tenant infrastructure underneath.
Fractional or project-based.
Most teams ship single-tenant agent demos quickly. The gap between that demo and a
multi-customer product is where I work.
// architecture · simplified
What you get
What changes after we work together.
The technical work has a purpose: removing the engineering friction between
your tenth customer and your hundredth. Here's what that looks like in
practice.
✗ Before
One customer works. The second one breaks something subtle in production.
Every new tenant takes a senior engineer half a day to onboard.
Your GitHub App is wired for your dev account, not your customers'.
Sandbox isolation is "we hope nothing escapes."
You're three months from needing to hire a senior platform engineer FT.
→
✓ After
New tenants come online without engineering involvement.
Each customer's code, secrets, and runtime stay strictly isolated.
GitHub App installation is a customer-driven flow you don't think about.
The orchestration layer has real visibility per tenant.
You're 3–6 months ahead of the infra hire, or never need it.
~6mo
Deferred the senior platform-engineer FT hire, saving the equivalent of $90k+ in fully-loaded cost while still shipping.
Typical target · estimate
0 eng hrs
To onboard a new tenant. Goes from a half-day engineering task to a customer-driven flow with no human in the loop.
Target outcome · post-engagement
1–2 wks
To working multi-tenant isolation. First engagements deliver a deployed boundary, not a slideware architecture document.
First-engagement scope
Selected work
What I've built, and what it proves.
Three projects, each with its own arc. I lead with the one most relevant to
what you'd hire me for.
Active project · 2026
Multi-tenant background agents
Fork of a popular open-source background-agents repo · in progress
The problem
The most popular open-source background-agents codebase explicitly punts on multi-tenant deployment. The README lists the gaps: per-tenant GitHub Apps, access validation at session creation, tenant isolation in the data model. Real product teams need exactly those pieces.
What I'm building
A fork that closes the gaps. Per-tenant GitHub App installation flows. Access validation enforced at session creation. Tenant-isolated data model. Sandbox orchestration on Cloudflare Durable Objects + Modal + OpenCode runtime.
Where it stands
Architecture decided, foundation built, milestones tracked publicly on GitHub. Demo and architecture writeup coming in the next few weeks.
→ What this means for you
I'm solving the exact problem this site sells, in public. Available to apply this work to your product as a contract engagement, usually starting with the highest-friction piece in your stack.
GitHub (coming soon)
Writeup (coming soon)
Shipped · open-source · 2024–2025
OmoiOS
Autonomous agent platform · Apache 2.0 · 60★ on GitHub
Spec-driven workflowCode assistant
The idea
A self-hostable platform where you write a feature spec, agents execute it overnight in cloud sandboxes, and you wake up to a PR. Built before "background agents" was a named category.
What I built
Multi-agent DAG executor on Daytona sandboxes. Spec-to-PR pipeline. Self-hostable so teams could run it on their own infrastructure. Designed for parallel agent execution with proper isolation between tasks.
What happened
60 stars on GitHub, working demo, real users. I couldn't find product-market fit as a managed service and stopped pursuing it commercially. The orchestration patterns I developed are the foundation of the multi-tenant work I do now.
→ What this proves
I've shipped autonomous agent infrastructure end-to-end before "background agents" became a named category. I know what the right abstractions look like, and what they cost when you build them in a vacuum. I bring that to your product.
Regional ML infrastructure for Paraguay · with collaborator Fran
The problem
Paraguay's meteorological infrastructure has real gaps. High-resolution regional weather modeling needs serious GPU orchestration and data pipelines most teams can't stand up.
What we built
Data pipelines for regional meteorological inputs. Inference orchestration on GPU infrastructure. NVIDIA Earth-2 framework integration for high-resolution forecasting.
→ What this proves
I work with serious ML infrastructure beyond LLM agents. The same orchestration patterns transfer across domains, and I can ship with research collaborators on time-bounded work.
No long discovery process, no slideware. Most engagements move from first
call to working infrastructure inside two weeks.
01
A 30-minute call
You describe what you've shipped, what's breaking, and where the multi-tenant gap lives. I tell you whether I think I can help, and what the first week would actually look like. If we're not a fit, you'll know on this call.
No-cost · usually within 48 hrs
02
A focused first engagement
Usually 1–2 weeks. An architecture review plus a build of your highest-friction piece, often the per-tenant GitHub App flow or the session isolation boundary. Fixed scope, fixed price. You walk away with working infrastructure either way.
Typical scope · 1–2 weeks
03
Continue, or don't
If the first engagement lands, we continue on retainer or project basis until you've got the multi-tenant layer you need. If it doesn't, you've still walked away with working infrastructure and a clear architecture review.
Optional · retainer or project-based
About
Engineer · Paraguay.
I'm Kevin Hill, an American engineer who moved to South
America. I'm now based in Asunción, Paraguay. I've spent the last several
years building agent infrastructure, multi-tenant SaaS, and data systems,
most recently on Cloudflare Workers, Modal, OpenCode, and Daytona. I've
also supported and run production mobile apps in Flutter for both iOS and
Android. I co-run a workforce development company as a separate venture;
this site is for my independent engineering work.
I work US-business-hours-friendly from UTC−3. Engagements are fractional or
project-based, not full-time. Invoiced through Wise or Stripe.
Building an AI agent product? Let's talk about the layer underneath.
Tell me what you've shipped, where the multi-tenant gap is, and what you'd
want different in 30 days. I'll reply within 48 hours with whether I think
I can help.
