אבחון ← בנייה ← ניהול. אתם מאשרים כל שלב.
מודל אספקה המעוצב כך שה-AI מבצע את עיקר העבודה האוטומטית ובן אדם אחראי על התוצאה. מחיר קבוע, ללא קופסאות שחורות, ושלב בקרת איכות אנושית לפני שמשהו מגיע אליכם.
Paid diagnostic
A short, paid engagement on your real data. We show where you lose, under-price or over-invest senior time — with a live demo run on one of your real opportunities. The diagnostic credit applies against the build.
Fixed-price build
We stand up the workflow as a system, tuned to your templates, stack and commercial logic. Fixed scope, fixed price — no surprise invoices.
Monthly managed plan
We run it on live work, keep it current as your business changes, and review the outcomes that matter — win rate, margin, time-to-value — with you each month. Optional, and cancellable.
AI does the volume
The system handles the heavy lifting — structuring discovery, drafting scope and estimates, surfacing risk — so a person spends their time on judgement, not typing.
A human owns the result
A named Pro scopes the work, QAs every output and signs off before anything reaches you. The name on the work is a person, not a model.
You approve everything
No black box. You see and approve the scope, the estimate and the draft at every gate. Nothing goes out without your sign-off.
כל מעורבות הופכת את הבאה אחריה לזולה וחדה יותר.
כל פרויקט מפקיד במערכת נכסים רב-פעמיים: היקפים, מודלים של הערכה, לוגיקת תמחור וכללי סיכון. במקום להתחיל מדף חלק, המערכת מייצרת סטנדרטיזציה — אחריות ברמת שירות עם מרווחים ברמת תוכנה. שיקול הדעת המובנה והמצטבר הזה הוא החומה המגנה שלכם (the moat).
אודות הגישה
Why a paid diagnostic instead of a free pilot?+
A paid diagnostic earns real data and real attention from both sides. It runs on one of your actual opportunities, so you see the artifact — not a generic demo — before committing to a build. The fee credits against the build if you proceed.
What does "fixed price" really mean?+
Fixed scope, fixed price. We agree the workflow and the deliverable up front, and that is the price. No hourly meter, no surprise invoices. If scope changes materially, we agree a new fixed price before any work — you are never billed for a moving target.
How do you keep AI output trustworthy?+
Two ways. First, evaluation: we build graded eval sets from real past cases and gate every release against them. Second, a human QA step: a Pro reviews and signs off before anything reaches you. Accuracy is measured, not assumed.
What is the standardisation / data-moat story?+
Every engagement deposits reusable assets — structured scopes, estimate models, pricing logic and risk rules. The system gets cheaper and sharper each time instead of starting from a blank page. That compounding standardisation is the moat: service-like accountability, software-like margins.
Do we have to take the managed plan?+
No. The managed plan is optional and cancellable. Many clients run the built system themselves; the plan exists for those who want us to keep it current and review outcomes with them each month.