A small team that takes on the hard problems other shops won't. Fraud intelligence, automation that runs the work, generative engines. We scope it, ship it, and run it.
Every system is custom-engineered, shipped to production, and run as a live operation. We don't hand over a tool and disappear.
OSINT pipelines, network mapping, and card-misuse detection that surface what keyword monitoring can't see. Running around the clock, re-tuned as the actors change their methods.
Dashboards and agent workflows that take the busywork off your team's plate. Intake, triage, reporting, the repetitive decisions, with a person put back only where one's actually needed.
Systems that learn a brand's voice from its best work, then produce posts, video, and ads at volume. Grounded, scored, scheduled, and tuned by what actually performs.
Browser and multi-agent systems that operate across real platforms at scale, reliably, without tripping detection or falling over the moment something changes.
A few of the things we've built. Clients kept anonymous; the numbers are real.
A real-time platform that runs intelligence gathering, content generation, comment ops, and ad analytics from a single console. The team stopped switching between ten tools and started running the whole operation from one screen, with the AI handling the repetitive work underneath.
A card issuer needed to find where its cards were being resold and misused. The system now tracks 6,400+ sources, has surfaced 130 sites carrying its card BINs, including 16 the in-house fraud team had never found, and runs continuously, flagging new exposure as it appears.
An engine that pulls in winning content, builds the brand's own corpus, and writes a full QA-scored weekly calendar. Listings, market commentary, recruiting, each piece grounded and on-voice, the whole workflow assembling itself while the operator just talks through what they want.
A platform that continuously finds, scores, and recombines top-performing organic and paid creative into campaigns a team can run, replacing a slow manual research habit with a pipeline that never stops looking.
No packages, no off-the-shelf drops. We scope each engagement to what you actually need, then own it through to operating it.
We map the real problem and design the system that solves it. Fixed scope, priced to the project.
We engineer it to production. The pipelines, the models, the interface, the guardrails around all of it.
It ships onto infrastructure you own, wired into the tools your team already works in.
We run it. Watching it, tuning it, and improving it as the ground underneath keeps moving.
The experimental side. Where we push the generative stack past what clients have asked for yet.
Custom-character UGC at scale, text-to-track music, video synthesis. The cutting-edge work that becomes next year's client systems. A look at the edge of what we build.
Step into the Lab →If it involves AI doing something real, and running once it's built, it's the kind of work we take on.
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