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Belden Studio LLC

We help you decide where AI is worth the investment, and then make it work.

How an engagement runs

  1. Trace the work

    I follow one job end to end with the person who does it, and understand the time sinks and pain points.

  2. Scope one workflow

    We pick a single workflow, name who owns it, and agree what success looks like.

  3. Build it

    Something working early enough to try on real work. Then the version that runs unattended, with a person checking the output before it counts.

  4. Train the team

    Training for the people who will use it, with named champions and a route to get help.

  5. Review what changed

    We look at whether those time sinks actually went away, and decide together: continue, adjust, expand, or stop.

An example engagement

01

AI workspace setup

A shared workspace on the tools you already own, whether that is Microsoft 365 and Copilot, Google Workspace, or ChatGPT Business.

  • Data boundaries agreed in writing before anything is connected
  • Instructions written for each role separately
  • A library of your recurring tasks, named the way you name them
  • Your files, your database, and your calendar connected, read-only to start
02

Workflow build

One recurring job running end to end. Say the quote that takes an hour to assemble from a price list, a spec, and last year's version.

  • One workflow running on work that actually counts
  • Pulling from the systems that job already touches
  • A person reviews the output before it counts
  • Checks that catch a wrong answer before someone has to
03

Training and handover

Your team running it without me, and knowing what to do when it misbehaves.

  • Training built around what each role does all day
  • A named owner inside your team
  • A thirty-day plan with a real decision point in it
  • A recurring check-in with a date on it

What we have worked on

Start a project conversation

Headwaters

Context

a regulated food distributor with perishable stock, a sales floor, a warehouse, and data spread across too many places

Shipped

the system the business runs on: inventory dashboards, live customer menus, sales orders, invoicing into QuickBooks, ordering over Telegram and WhatsApp, and AI built into the screens people use all day

Why it matters

The closest match to any organization where the hard part is getting people, data, and software to agree.

SuperCarl.ai

Context

AI relationship intelligence and outreach product

Shipped

a campaign builder, a live dashboard, outreach across LinkedIn, email, phone and text, and voice agents that hold a conversation

Why it matters

Production work with real users, saved state, and consequences when it goes wrong.

CookingBuddy.ai

Context

voice-first AI assistant for multi-step cooking

Shipped

a voice assistant for when your hands are busy: live progress, substitutions, timers, and step-by-step guidance

Why it matters

Proof that AI can walk someone through a messy real-world task without losing the thread.

1Password / Caffeine / mmhmm

Context

larger software teams

Shipped

high-traffic interfaces, live video clients, machine learning running in the browser, and enterprise video workflows

Why it matters

Work like this holds up under real traffic or it does not ship.