These are the products and systems inside our R&D lab—Stackit, Navo, and NeedsMatch—where we run AI and agent experiments before turning the winners into an AI Growth Engine for agencies.
Future agency case studies
Verified creative, digital, and tech agency outcomes will be added above the internal products, with niche, starting point, timeline, booked-call or revenue outcome, and claim sources.
We will not publish a placeholder logo, projected result, or anonymous claim as proof.
Leak attackedRestricted paid acquisition and a product serving only human treasury owners
ExperimentBuilt an owned education-to-product funnel, automated treasury workflows, and agent-ready interfaces
Early result / learningLive since February 2023 · Hundreds of customers through the cycle · ≈$40K historical peak MRR
Stackit.ai grew from a manually incubated treasury strategy into an application used by hundreds of customers throughout a market cycle. Live since February 2023, Stack is now applying those product, customer, and operating lessons as it expands from human treasury owners to AI agents.
Leak attackedVideo creation, publishing, performance review, and iteration lived in separate tools
ExperimentBuilt an agent loop that creates, posts, reads performance, and changes the next video
Early result / learningCreate–post–learn workflow in active development · No completed client outcome claimed
A standalone AI video platform, also used inside the AI Growth Engine, where an agent creates and posts videos, learns from their performance, and improves future versions with the goal of finding a video that can become an ad.
Before Mass Ideation became a growth R&D lab, we spent more than a decade as the “try the new thing” partner for agencies and brands: early video banner ads for Disney, AR and interactive work for fashion houses, and mobile and web games for entertainment and global brands like Google and Johnson & Johnson.
That wave-spotting experience is why our AI and agent experiments stay early and useful, not gimmicky.