Integrated AI Solutions

We put AI to work inside your business.

Integrated AI Solutions is a hands-on partner. We learn how your business runs, then set up AI to handle real work inside the tools you already use: your email, your CRM, your project boards, your phone system. Work that used to eat hours starts happening on its own.

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Illustrative chat example: an AI-run design contest with twelve concepts scored and ranked overnight
Illustrative example: an AI-run design contest: twelve concepts, scored and ranked overnight. Names and details are fictional.

Your team already knows how to use this

We don't teach your team a new platform: there isn't one. Your AI works inside Slack or Microsoft Teams, the place your team already talks. That's a deliberate choice, because adoption is where most AI projects die: new logins, new dashboards, new habits nobody keeps. We skip all of it. If you can send a message, you can put AI to work. And because every deployment lives in a channel, governance and cost control attach right there: different teams and projects can run different rules, models, budgets, and permissions.

  1. Zero training curve: no new software, no new habits

  2. Work happens in channels your team can see: visible, auditable, correctable in real time

  3. Requests, approvals, and results live in one searchable thread

  4. Works from a phone in a truck as well as it does at a desk

What that looks like

Every one of these runs from Slack or Microsoft Teams, no new platform required.

  1. One Slack message becomes a fully built, assigned task in your project board: client, budget, and instructions filled in

    See the use case

  2. Say "set up conversion tracking" and it gets deployed on your website, tested end to end

    See the use case

  3. Ask for design options and get a scored contact sheet of 12 concepts to pick from

    See the use case

  4. One assignment message spins up a team of AI agents that split the work, brief each other, and verify the result

    See the use case

  5. Every inbound lead is researched and scored before a human ever opens it

    See the use case

  6. Call notes file themselves into your CRM after every meeting

    See the use case

  7. A report that used to take an afternoon arrives in minutes

    See the use case

  8. Automate payment recovery and collections

    See the use case

  9. An agent notices its own operating cost climbing, restructures how it works, and cuts it

    See the use case
See real examples
Illustrative chat example: a website edit requested in plain English
Illustrative example: a website edit requested in plain English, deployed and verified. Names and details are fictional.
Illustrative chat example: a proactive morning check-in posted to a shared channel
Illustrative example: a proactive morning check-in posted to a shared channel. Names and details are fictional.

AI, deployed responsibly

- like an operation, not an experiment

The workflows are the shiny object. The bigger unlock, and the bigger risk, is cost and control. AI lets you get dramatically more done, which also means it can spend dramatically more. We manage both:

A structured rollout: every workflow starts as a Copilot (human drives)

earns its way to Coworker (works alongside you)

only becomes an Operator (runs on its own) once it's proven.

Nothing skips the line.

Governance built in: human approval gates on anything customer-facing, an audit trail in the channel, and each workflow limited to only the systems it actually needs.
The agent's own self-optimization report, blurred to protect client confidentiality
From the live workflow: an agent's own cost-optimization report.
Cost discipline: we measure what every workflow spends and put watchdogs on it. One of our live use cases is an agent that noticed its own operating cost climbing, restructured how it worked, and cut it.
See the use case

You're not just adopting AI. You're adopting a management system for it.

How an engagement works

  1. 01

    Discover

    Learn the business, its goals, economics, systems, workflows, and real bottlenecks.

  2. 02

    Design

    Prioritize opportunities by value and feasibility, then architect the operating environment.

  3. 03

    Build

    Connect systems and implement the workflows and agents that perform the work.

  4. 04

    Train

    Onboard employees and redesign how the work gets done around the new capability.

  5. 05

    Maintain

    Monitor, troubleshoot, update, support, and govern the environment in production.

  6. 06

    Expand

    Identify the next opportunity and build the next layer of capability.

Team working together

You don't need to know anything about AI. You point at the work; we make it happen.

Backed by our 90-Day Money-Back Guarantee.

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