Before / After

Three reports from our studio.

No feature list. No tech pyramid. Three stories. Drag the slider to see how before becomes after.

01 / SaaS & Web Development

An idea.

A product. Paying customers.

◉ https://app.deinstartup.io/dashboard
App
Dashboard
Customers
Billing
Settings
du@startup.io
MRR
€12,840+18%
● live
Acme GmbHEnterprise€2,400
NorthwindPro€890
Helios LabsStarter€340
Notebook · Seite 47
My SaaS Idea
v1 — bearbeitet
TODO: Auth? Clerk? NextAuth?
TODO: Billing — Stripe eingerichtet??
TODO: Multi-Tenant Logik überlegen
TODO: Dashboard-Design (Figma offen)
TODO: Domain kaufen
TODO: Mit Entwickler sprechen
Angebot Entwickler: 6 Monate Wartezeit · frühestens Q3
Before
After
Drag

A founder in Wiesbaden, January 2025. Pitch deck done. Figma mockups beautiful. Developers contacted. The answers: six-month waitlist, unclear scope, no price until a workshop.

She comes to us. We look at the mockup, cut half, prioritize what makes money.

Six weeks later the product goes live. Auth, billing, dashboard. Her first ten customers pay. By Friday of week seven she has product-market-fit evidence.

from kickoff to launch
6 weeks
Deep-dive
02 / AI Engineering

A demo. An investor.

Real traffic. Real numbers.

Production · p99 latency
780ms
target: <800ms · stable across 40k req/day
cost_per_request$0.03 · predictable
accuracy94%
fallbackClaude → GPT-4 → cache
evals● 42/42 passing
investor update
Series B · pipeline warm
classification · live● stable
Production · p99 latency
14.2s
expected: 800ms · actual: 14,200ms
cost_per_request$0.42 · 14× over
hallucination_rate5.1% · SLA fail
fallback_strategynone configured
evals— not implemented
investor ETA
Montag 09:00 · kommen
streaming classification…37%
Before
After
Drag

A Berlin startup, March 2024. The AI demo on stage works. Investors are impressed. The money arrives.

Then comes the traffic. The same AI answers 40 times slower, costs fourteen times more than expected, hallucinates on every twentieth request.

We come in, write evals, build fallback routing, cap cost budgets, migrate to a mixed model stack. After six weeks: p99 under 800 ms, costs predictable, accuracy at 94 percent. The investor calls again. This time about Series B.

accuracy in production
94%
Deep-dive
03 / BI & Data Analytics

Forty-seven Excel files.

One dashboard. Monday. 8:47 AM.

Live · Montag 08:47

Dispatch Dashboard

Quelle: SAP · Postgres · Refresh: 30s
Liefertreue · diese Woche
94.2%+3.1% WoW
Delivery · last 14 daysSLA target: 92%
Ø Marge / Auftrag
€127+€12
Offene SLAs
23−8
Fahrer aktiv
41 / 45ok
📊 Monatsreport_2024_v7_FINAL_final_v3_KORRIGIERT.xlsxAutosave: off · Last edit: Fr 21:47 — Müller
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Before
After
Drag

A mid-market logistics firm near Fulda, December 2024. The controller opens Excel Monday morning. She opens forty-seven files. She doesn't know which one is still current. Friday's numbers were right. Tuesday's weren't.

The meeting starts at nine. The managing director asks about on-time delivery this week. She says: "I’ll send it to you." That means afternoon.

Three weeks later. Monday 8:47. She opens the browser. A dashboard loads. On-time delivery 94.2 percent. Delta to last week plus 3.1. She sees the number before being asked. The meeting takes eighteen minutes instead of forty.

from kickoff to launch
3 weeks
Deep-dive

Also in-house

Three further capabilities, usually delivered as part of the projects above — not their own landing pages, but real skills in the house.

Cloud & DevOps

AWS, Kubernetes, Terraform. Boring deployments — exactly what you want.

Backend & APIs

REST, GraphQL, event-driven architectures. APIs your team will enjoy using.

Technical Consulting

Architecture reviews, code audits, team scaling. Honest assessment of where it hurts.

Your before also eventually becomes an after.

That only happens once you start. Discovery call is 30 minutes, free, NDA-first.

Book discovery call