// Project brief
Slop isn't just AI, it can also be human. Unslop will input a website and cut out all the ineffective fluff/slop with context decisions and browserbase lookup centered around jev decision making.
Projecthackathon
Built at JEVATHON (w/ The AI Collective)
UnSlop
Slop isn't just AI, it can also be human. Unslop will input a website and cut out all the ineffective fluff/slop with context decisions and browserbase lookup centered around jev decision making.
// latest_project_recording.mp4
// More from this event
Keep exploring what builders shipped.
Gustave
Gustave, the voice shopping assistance
Online shopping means typing, filtering, scrolling and comparing across tabs. And most "shopping assistants" just swap the search bar for a chat box: type, wait, see three products, type again, wait again. In a store, you just talk, and someone starts pulling things off the rack while you're still talking. Every reaction you give sharpens what they bring next. Meet Gustave: a voice shopping assistant that recreates that natural, iterative experience.
TypeSafe AI
Worth Your Saturday
Worth Your Saturday
Worth Your Saturday is a decision-intelligence prototype that helps people discover what they actually won’t compromise on before spending their time. Using apartment hunting as the demo, Jev speculatively evaluates 1,872 evidence-level distinctions across five apartments; as a conversation clarifies the user’s priorities, the same evidence fields are re-projected with zero additional Jev evaluations to surface meaningful matches, tradeoffs, and unresolved questions. The result isn’t another ranked list—it’s a realistic Saturday of tours worth taking, delivered through an agent connected to iMessage with Photon Spectrum. The broader primitive is intent-conditioned salience: evaluate evidence broadly, discover what matters to the person, preserve consequential uncertainty, and allocate scarce human attention accordingly. Https://worth-your-saturday.vercel.app
TypeSafe AIPhoton
KYC-Sentinel
KYC Sentinel
KYC Sentinel: adverse-media screening for AML/KYC analysts. Jev judges, code decides, the LLM only writes. Compliance analysts waste hours clearing irrelevant news hits: same-name strangers, victims, passing mentions. KYC Sentinel pulls news for every client in a portfolio. Jev (TypeSafe AI) judges each client–article pair: same person? the perpetrator? what risk? how severe? A pure, unit-tested router then sorts every client into CLEAR / REVIEW / FLAGGED / NO_COVERAGE. • Fails closed: any uncertainty or model error means REVIEW, never CLEAR. • Autonomy Dial: a compliance manager drags strictness and the whole portfolio re-routes instantly from stored Jev probabilities, with zero new model calls. • Thresholds live in code, not prompts. The LLM only writes analyst memos, on demand, for flagged/review clients, citing sources. It never decides. • Full audit log of every decision, plus a live receipts meter. Results on a 26-client portfolio: 37 Jev calls, 0 errors, 0.9s, $0.0011, about 145× cheaper than the same job on a frontier LLM (est. $0.16). Famous-name collisions (Michael Jordan, Michael Cohen) are cleared as "different person" even when the other person's news is damning. Victims and identity-theft targets are cleared as "not the subject". Vague common-name mentions go to REVIEW. Documented fraud cases and a Tulsa accountant who shares Taylor Swift's name are surfaced, while the pop star's news is ignored. Stack: Jev (TypeSafe AI), FastAPI, GDELT, Gemini for memos, vanilla JS. 77 tests. Data note: GDELT rate-limited our network, so several clients use clearly labelled synthetic articles (domain synthetic-demo.local). Everything downstream runs identically.
TypeSafe AI