We're developing an AI-powered marketing workspace that connects campaign data, helps teams understand performance, and turns insights into reviewable actions. Designed for human oversight, not black-box automation.
Our AI Marketing Platform is currently in development. We're building practical tools for businesses and agencies to understand what's working, coordinate campaigns, and reduce repetitive tasks without losing control over budgets or approvals.
Campaign performance varies by channel. Review creative and audience-level results before adjusting budgets.
Bring campaign metrics from platforms such as Meta Ads and Google Ads into one consistent view.
Ask questions in plain language, investigate performance changes, and surface opportunities worth reviewing.
Draft and iterate campaign copy, creative briefs, and test ideas with AI support.
Coordinate repetitive marketing tasks with explicit review and approval before impactful actions.
Zero-to-one builds for founders. We define the spine of the product, ship a working v1, and stay on to scale what works.
Next.js, SwiftUI, Flutter, React Native. Load time, gesture feel, and the small details that make software feel fast.
Boring, observable, well-documented infrastructure. AWS, Cloudflare, Postgres. CI that actually tells you when it's broken.
Evals first. We wire LLMs into workflows where they earn their keep — agents, search, structured extraction, ops copilots.
Real-time rates for every global currency. Built because existing converters were stuffed with ads.
Curated, editorially-calm wallpaper library. No gacha, no crypto. Good gradients and good stills.
Searchable keyboard-shortcut cheat-sheet for the tools devs actually use. Syncs across devices.
Paper-style planner that turns into a weekly review. Built for people who journal with pens.
One-screen focus timer with a small grain of intention at the start of every block.
Small log book for the daily gestures of shipping software: commits, notes, deploys, decisions.
┌─────────────────────────────────────┐ │ scope → spine → ship │ │ 1w 3–4w 4–6w │ └─────────────┬───────────────────────┘ │ ▼ ┌─────────────────────────────────┐ │ operate · on-call · iterate │ │ ongoing · monthly qbr │ └─────────────────────────────────┘ // or handoff to your team, cleanly. handoff() → runbooks + eval suite + video walk
We read the doc, talk to users, and write a short brief with the shape of v1 and the sharp edges we see.
End-to-end with real data, then wrap the rest of the product around what actually held up.
Instrumented for the three numbers that matter. We iterate daily until the numbers move.
On-call rotation, quarterly reviews. Or we hand it off cleanly — runbooks, eval suite, a video walkthrough.
Llama shipped a product we'd been stuck on for a year — in eight weeks, and with less code than we had before.