AI advisory & strategy
Choose where AI earns its place. We assess workflows, data, and constraints, then shape a roadmap your team can act on.
You keep: a focused roadmap.
Your people. Your systems. What comes next.
Clear directionWorking softwareLasting capability
AI consulting & embedded engineering
Working AI.
Built with you.
Left with you.
We help mid-market companies and nonprofits turn AI plans into working software.
Our engineers embed with your team to build agents, automate workflows, and teach your people to run what we ship.
Twelve weeks. Software shipping weekly.
The code and capability stay with you.
The Nagomi practice
A clear decision.
A working system.
A team that owns it.
Embedded engineering
Build on your systems and data. We ship internal assistants, agents, and workflow automations with the review steps your people need.
You keep: working software and code.
Teaching & enablement
Make the capability part of your team. We work through real examples, document the system, and practice running it together.
You keep: playbooks and practical skills.
From the work to the working system
Start with something
your team does every week.
The report someone rebuilds by hand. The policy nobody can find. The request that crosses three systems before anyone can act. These are the kinds of problems we help your team work through.
We start inside the workflow, choose a focused scope, and build with the people who will use the result. Here is how that work becomes a system your team can own.
Go straight to the engagement plan ↓Inside an engagement · 01
First, we find the work worth improving
We map the reports, requests, and handoffs your team handles every day. Together, we choose a workflow where AI can make a useful, measurable difference.
Inside an engagement · 02
We work alongside the people doing it
Our engineers sit with your team, understand your systems, and trace the workflow on your data. The starting point is a workflow map your people recognize.
Inside an engagement · 03
Some work should stay with people
Judgment, relationships, and responsibility belong with your team. Choosing where AI should not act is part of designing a useful system.
Inside an engagement · 04
We build assistants around your knowledge
An assistant can find an internal policy, prepare a report, or draft a response with the relevant source material. We design the review step with the people responsible for the result.
Inside an engagement · 05
We connect the steps between your systems
An agent can classify a request, collect the right information, and prepare the next action. We build the integrations, approval points, and exception handling that make the workflow usable.
Inside an engagement · 06
New capabilities take practice
Your team learns to review outputs, handle exceptions, and improve the system. The playbooks and practice are part of the engagement.
Inside an engagement · 07
The pieces become a working system
Useful changes connect. Working software ships weekly, inside your environment. We observe what happens, learn from it, and build the next small improvement.
Inside an engagement · 08
And the capability stays with you
Your repos. Your tools. Your data. Your team owns the code, the models, and the playbooks. We plan our exit from the first day.
A fixed-scope engagement
Small, working steps.
Something you can keep.
We work inside your environment, from the first workflow map to the final handover.
Explore the deliverables ↓- Engagement length
- 12 weeks
- First working software
- Week 05
- Ownership
- Your team.
The code, the models, the playbooks.
How the engagement unfolds
AdvisoryBuildingEnablement
Weeks 1–2
Start with the work.
We begin inside your workflows. We watch, ask, and measure before recommending anything.
Weeks 3–4
Choose fewer things.
We cut the roadmap to what matters: what to build, in what order, and what to leave alone.
Weeks 5–10
Working software, weekly.
Agents, automations, and copilots on your data. Small, working improvements, measured against the outcomes we promised.
Weeks 11–12
The capability stays.
You own everything we build. Your people have the code, the models, and the playbooks to run and improve it.
Your first twelve weeks
with Nagomi.
Move through the twelve weeks. See what we work on,
and what stays with your team.
Observe1 / 4
Start with the work.
We begin inside your workflows. We watch, ask, and measure before recommending anything.
Yours to keep
Workflow map
How the work moves through your people, data, and systems.
Drag across the illustration to move through the weeks.
ObserveFocusBuildTransfer
Built with you.
Left with you.
The code, the models, and the playbooks belong to your organization. We work inside your environment from the beginning, so the handover is something we build toward every week.
We start inside your workflows, alongside your people.
The people and tools behind the work
Human judgment.
More hands for the work.
AI helps with the work. People set the direction, review the results, and stay responsible.
01 / HumanGabriel Rojas
FounderTwenty years running technology for demanding institutions. Experience brought directly into the work, alongside your people.
Meet GabrielAI assistants
Research & draftingFinding relevant knowledge, preparing a first draft, and exploring options. Your people review the result before it becomes a decision.
Explore the practiceWorkflow agents
Integration & automationConnecting steps across your systems. Collecting information and preparing actions, with human approval where it matters.
See how we build“Calm is not slow. Calm is what speed feels like when it’s under control.”Gabriel Rojas · New York / Austin
▍ Filed from production
Production Notes
A working publication from inside a real agentic stack. Filed from production by Gabriel Rojas.
Read the latest dispatches ↗Let’s talk about your workflow
What is your team
ready to make work?
Bring a recurring bottleneck, an AI pilot, or a workflow you want to improve. We’ll talk through the problem and tell you honestly whether Nagomi is a fit.
Book a call ↗hello@nagomistudio.ai