Huh, what does that mean?
Fine-Tuned AI Models
What it is
Custom AI models trained on your own emails, docs, chats, and SOPs so they speak your language, follow your rules, and handle specific jobs inside your business.
Some examples
Draft replies to leads and customers in your tone
Act as an always-available knowledge guide that helps users navigate educational materials, onboarding content, or internal documentation
Classify/route tickets, deals, or tasks based on your logic that helps your clients draft and negotiate contracts relating to recording, publishing, licensing and distribution, sponsorship and merchandising.
Why its worth doing
You get consistent, on-brand decisions and responses without burning your team’s mental energy on repeat work. Instead of a generic chatbot, you’re building a reusable “second brain” that actually reflects how your business thinks.
What it is
Custom AI-powered platforms, interfaces, and applications that turn AI capability into a visual, software-native experience. Instead of interacting through a text-first chat window, these are purpose-built programs such as web apps, dashboards, and tools where intelligence is embedded into layouts, screens, controls, and flows.
What it can do
Present AI-driven logic through visual components like dashboards, forms, decision trees, and step-by-step screens rather than long text exchanges
Give teams and customers clear, structured interfaces where context, options, and next actions are visible at a glance
Turn complex reasoning into interactive experiences people can click through, explore, and understand without reading or prompting
Why it’s worth doing
Text-based AI is powerful, but visual systems reduce friction. When intelligence is expressed through interfaces instead of conversations, users move faster, make fewer mistakes, and need less explanation. The underlying AI does not change. The experience does, and that difference is what turns capability into something people actually adopt and rely on.
AI-Powered Applications
What it is
A CRM set up as the operating system for your revenue: clean data, clear pipelines, and automations that move leads, trigger follow-ups, and keep everyone on the same page.
Some examples
Auto-create and tag leads from forms, calls, and chats
Send timed follow-ups and reminders based on pipeline stage
Surface simple reports: where deals stall, response times, conversion by source
Why its worth doing
Instead of guessing where revenue is leaking, you can see it and fix it. Fewer dropped balls, less “what’s going on?”, and a sales/ops engine that feels controlled instead of reactive.
CRM & Revenue Systems (with Automations Built In)
Prototyping & Experiments (The Lab)
What it is
A structured sandbox for trying ideas fast: small AI/automation builds that are designed to answer “Is this actually worth scaling?” instead of living forever in a notion doc.
What it can do
Test a micro-automation on one painful task
Spin up an internal tool or assistant for a single team
Trial a new data source or model for a week and see real impact