AI implementation, embedded with operating teams

Ship the AI tooling your operating team needs in weeks, not quarters.

We embed alongside your team to turn manual, multi-system workflows into AI-native internal tooling.

See the work → Start a conversation

Where we sit Inside the operating team

Time to POC ~2 weeks from kickoff

How we operate PM + engineer in one

I / What we fix

The AI roadmap is the easy part. Shipping it is where it stalls.

Workflows live across multiple systems that don't speak

Operators tab-switch between ERPs, CRMs, spreadsheets, Slack threads, and emails to complete a single workflow. The cost is invisible until you measure it.

Prototypes never ship

Vibe-coded internal apps either die at the demo or consume scarce engineering capacity to harden. Auth, deploy, LLM calls all get rebuilt from scratch every time.

III

Finding the right AI talent is slow

Hiring an experienced AI builder takes months and the market is thin. We drop in top, production-ready talent in days so the work starts without waiting on a search.

Where we sit

AI Engineers embedded with the operators who run the business.

Consultants

Deliver a strategy, walk away. Strong on slides, light on what ships.

Dev shops

Build to spec, exit at handoff. Production-grade code, but no embedded knowledge of how the workflow actually runs.

Stuhi Grand

Discover, build, ship, iterate, all alongside your team. An extension of your team that leaves a working system and codified institutional logic behind.

2 weeks

From kickoff to POC

PM + Eng

Sitting with your team

Weekly

Live demo cadence with leadership

II / Services

What we build for operating teams.

AI Strategy & Roadmap

Executive workshops, operating-model diagnostics, and a prioritized plan that ties AI to margin, throughput, or revenue — not slideware.

AI Platform & Infrastructure

The substrate that makes AI repeatable: model evaluations, retrieval pipelines, agent frameworks, observability, and governance. So the next use case ships in weeks, not quarters.

III

Custom AI Workflows

AI-native tools and agents purpose-built for the workflows your team actually runs. Integrated with your existing systems, evaluated for safety and quality, and shipped to production.

Adoption & Enablement

Internal playbooks, hands-on training, and operator-led rollout that turn pilots into daily defaults. We codify the institutional logic so your team owns the lift after we leave.

III / Our work

A snapshot of recent work.

Project

The problem

What we built

Business outcome

OPERATIONS

Automated a manual operating process driving client errors and churn.

A manual operating process spanning multiple systems was producing client-impacting errors. Errors were turning into churn.

An internal AI app that consolidates the workflow into a single guided interface, flags exceptions inline, and learns from operator feedback each week.

−70%

Error rate, within 3 weeks of going live

PRODUCT VELOCITY

Closed the loop between user feedback and the next deploy.

Vague user feedback was bottlenecking every internal app. A translation layer sat between operators and engineers, and iteration crawled.

An in-app widget that captures screenshots, asks structured clarifying questions, and auto-tickets feedback straight into the build cycle.

Days

From user feedback to next deploy

PLATFORM

Non-engineers shipping production-grade internal apps.

Internal apps from non-engineers stalled in prototype or consumed scarce engineering capacity to harden. The same plumbing got rebuilt every time.

A hosted dev harness with auth, deploy, LLM calls, observability, and a feedback widget. Purpose-built for non-technical builders to ship to production.

0 → prod

Without an internal engineering team

IV / FAQ

Common questions.

How quickly can you ship a working POC?

About two weeks from kickoff to a working proof of concept your operating team can actually click through. We work as a PM-plus-engineer pair embedded with your team, with weekly live demos to leadership so the build stays grounded in real workflows, not a wishlist.

Who do you typically work with?

Operating teams at mature businesses — COOs, heads of ops, and AI / automation function leads — that have moved beyond pilots and need AI tools running in production. We are not the right fit for early-stage product R&D or pure-research engagements.

How is this different from a strategy consultancy or a dev shop?

A strategy consultancy delivers a plan and walks away. A dev shop builds to spec and exits at handoff. We sit between the two: production-grade engineering, embedded with the operators who run the workflow, so the institutional knowledge stays after we leave.

What does an engagement look like?

Either a fixed-scope project or a monthly retainer, scoped together on the intro call. We embed with your team, ship to production, and hand off working systems your team owns — not slides, not a dependency on us.