Production software in days,
not months.
14 demos. Industries with no demos yet are on the roadmap.
The renter who wrote at 9 pm and never heard back
A leasing assistant on the manager's public site: search the listings, ask about pets and parking, book a tour at a real time, and get prequalified, at 9 pm, in the renter's own words.
Production ready in 15 daysInquiries waiting, tours to fill, applications stuck
An inbox by minutes waiting, with a drafted reply on every inquiry that names two units that fit and two tour slots; today's tours as a day; applications as a review deck with a recommendation on each card.
Production ready in 15 daysWork orders past SLA and the vendor nobody called
A triage queue by time to SLA, emergencies first, with the tech or vendor the agent suggests on every unassigned order and why: the trade, the load, the vendor's days and cost, whether their insurance is current.
Production ready in 12 daysLeases expiring in 90 days, priced by feel
A 30 / 60 / 90 timeline where every expiring lease is a card with current rent, the submarket median, the proposed offer inside the legal cap, and the odds of renewal at that price.
Production ready in 12 daysRent that is late and the sequence nobody follows
A delinquency ledger with the next step in the sequence on every balance and the window it belongs in: reminder on day 3, call on day 8, plan on day 14, notice on day 24. A policy can send the day-3 reminders on its own, under a ceiling.
Production ready in 15 daysUnits sitting vacant after move-out
A board of units in turn, columns for the steps (inspect, clean, paint, repairs, flooring, photos, list), days on every card, and the vendor on every step. Steps with nobody booked come first, because that is where the days go.
Production ready in 10 daysThe owner asking why the statement moved
A month-end desk: owner questions with the answer already assembled from the ledger lines that moved, distributions that swung 8%+ with the reason attached, and statements ready to send with the variance note inside.
What slipped this week, and what to decide
The founder's Monday page for a subscription grocer: acceptance, basket, forecast error, waste, contribution, payback and retention as one loop, the leak named, and the decision that fixes it one click away.
Deliver every box next week, at cost
Next week per fulfillment center, re-planned continuously: demand from the recommendation engine, receipts due, shortages, labor against the shift plan, packaging against the weather. Moves under a cost threshold run on their own.
Households about to leave
Five signals that a household is about to cancel (a bad box in flight, a cart they rejected, the promo cliff, a skip streak, an unanswered ticket), each with a policy that acts under a ceiling and the exceptions that go to a person.
Is growth paying back?
Contribution margin per box and per household, the waterfall from basket to contribution, cohorts by channel with payback, and the levers (substitutions, promo cadence, free-shipping threshold, channel budget) with promised versus realized effect.
Shaping the class under a tuition cap
The fall class against a headcount and net-tuition target: pipeline by income band, aid levers, territories, and the family questions with a drafted reply that computes the tuition cap from stated income.
Students slipping, and what we did about it
Engagement signals from four systems (LMS activity, missing work, card swipes, no-shows, holds) on every student, cases with an owner and an outcome, and what works: which interventions moved retention.
Seats short for spring, seniors without a capstone
The spring schedule draft by department against demand from last spring, seniors against capstone seats, faculty load and cost per seat, with the fix on each shortfall: open a section with the lightest-loaded instructor and a free room.
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Describe the workflow. We scope it in one session and put a working version on your data in days.