faktor400
Live8 engines for Amazon sellers: real-time finance, inventory and competition — forecasts, recommendations and fully-automatic optimization.
faktor400.com ↗You describe the product intent in prose. Our AI assembly line turns it into tested software — planned, built, cross-reviewed, merged.
A human describes what the product should do. That becomes a machine-readable contract — goals, bounds, acceptance criteria. The build runs in small steps through hard gates. Each critical step is reviewed by a different model before code is allowed to merge.
Even before building, a deterministic code gate checks the plan contract — every building block must resolve its inputs and outputs cleanly: no orphans, no forward references, no LLM discretion. Where it's about correctness rather than judgment, the hard gate beats probability.
Every build step passes through several roles with a widening view: a quality scan, then multiple adversarial rounds across deliberately diverse models — from sibling models in one family to foreign providers to external cloud bots — and finally an integration architect. Cross-layer changes get a second architect pass on top.
Then the tests run. Every change is classified by type and blast radius (surface class) and dynamically takes the matching route through the pipeline: a small text change the short path, a security-critical one the long path with additional, staged review rounds. That model diversity is load-bearing, not decorative: different systems see different bugs.
The factory runs several isolated production lines at once — unattended, but not uncontrolled: a compact status bus keeps the overview without a flood of logs, and a fail-closed reconcile lets only a real, reviewed result count as “done.” Failed runs are preserved and worked up — never silently discarded.
Every run leaves more than a product: friction becomes lessons, lessons become machine-readable operating rules that steer every following run. So the lead grows with each pass — compounding, not simply rebuildable with the same models.
When the orchestrator loses confidence on an architecture or tactics call, it doesn't guess — coupled to its own confidence, it convenes a panel of independent models that votes; on a tie it escalates on its own. The effort scales with the stakes — from a quick cross-check to a broad, diverse round. Uncertainty isn't hidden, it's played out.
Efficiency here isn't an after-the-fact savings drive — it's how the line is built. A good assembly line puts every resource exactly where it counts, and wastes no material.
We deliberately use different models — each where it's strongest, by fitness rather than price tag. Grounded not in assumption but in thorough model evaluation per role and task.
Every role works from a precisely scoped instruction — exactly for its task, without context ballast. Clear instruction instead of dragged-along noise.
Context and memory are refined continuously — quietly, in the background. Sometimes after hours, sometimes after days: cleaner handovers, less friction, more usable knowledge from the previous steps.
The human owns concept, priority and direction; the machine owns disciplined execution.
Product intent is translated into machine-readable specs — build and review share the same ground truth.
Plan, build, audit and merge don't happen on a hunch, but through hard checkpoints with a clear verdict.
No model reviews its own work: critical cross-checks run deliberately across providers and models.
BeyondWega builds and operates its own software products in clear markets — they are the proof that the assembly line delivers, not just a promise.
8 engines for Amazon sellers: real-time finance, inventory and competition — forecasts, recommendations and fully-automatic optimization.
faktor400.com ↗Gantt, a Kanban board and the critical path, wired into one — lean instead of bloated. GDPR-compliant, servers in Germany.
gantt400.com ↗Rankings, live scores and club management for the table-tennis scene.
Repair a chaotic flow network until the parts run into the collectors on their own.
Aerodynamic riding position from photo and video — CdA score and verifiable adjustments.
Status currently: 2 live, the rest in early lanes or validation. We show the real state — what's running and what's taking shape.
Hype-weary buyers spot exaggeration instantly. So we say where the factory stops.
The factory runs the build through its gates on its own — but it does not decide what is valuable. A human owns the concept.
Exactly one thing is still young: the automatic self-grade “does the product meet its vision?” — we measure that against real pilots instead of claiming maturity. The rest — throughput, zero heavy bad merges, checked contracts, hard gates — is evidence, not a promise.
Individual runs get slowed by AI-provider behaviour — rate limits, hiccups, context limits. Not fatal, but part of the honest picture.
On the measured effort we put one fixed, openly stated factor — and nothing else: no management fees, no orchestration costs. The price sits on a measurable basis, before we start.
Your price comes from your project's verified build effort — the actually measured token consumption. The tokens consumed per model are valued at current API prices and multiplied by a fixed factor: verified build effort × 3.5.
Including tax and VAT logic, from the integration through to checked billing.
~€780 · delivered in ~1 day
Reworking authentication — the long path through every gate, because the blast radius demands it.
~€1,700 · ~2 days
A clearly bounded fix with test coverage — fast, but through the same checkpoints.
~€320 · same day
Small projects are explicitly welcome. For new engagements the sensible minimum scope is ~€1,000, so analysis, build, review and handover are cleanly covered.
The same mechanism carries from a contained fix up to a complete product — what grows is the scope, not the way it's calculated.
You say what should be made — the factory delivers it. From a clearly scoped job through a complete product to an ongoing product partnership — with industrial delivery logic.