Tailored
AI solutions.

When standard tools cover 70 % but the missing 30 % cost the most — we build the whole solution. Architecture, code, integration, handover. Vendor-independent, documented, in your ownership.

Applications Where custom solutions become necessary

Three typical intersections.

01

Hybrid tool landscapes

SAP + DATEV + own industry CRM + 4 Excel logics — no standard tool covers this. We build the connection layer with clear data schema, documented interfaces, and AI-powered workflow choreography.

Stack: n8n · Custom-API · Postgres · Claude/GPT
02

Industry-specific compliance

BaFin, MNB, IDD, MDR — if your sector is regulated, most SaaS is out. On-premise or EU hosting, audit trail, isolated data paths, model-swap capable. We deliver an architecture that passes internal compliance review.

Stack: On-Prem · Open-Source-Modelle · Audit-Log · AVV/DPA
03

Multi-agent systems

Multiple AI agents working together — e.g. mail classification → routing → response generation → CRM update → escalation to the right case worker. Tool use, memory, safeguards. Production-grade, not demo stage.

Stack: Claude/GPT Agents · Tool-Use · Vector-Memory · Human-in-Loop
Entry When it pays off

Three signals that you need a custom solution.

Method Four phases

How we build your complete solution.

P · 01

Discovery

Process mapping, data audit, ROI estimate per initiative.

Few days
P · 02

Architecture

Tech-stack selection, model strategy, risk matrix with roll-back.

2–3 weeks
P · 03

Build & integration

Sprint-based in 2-week cycles, early pilot with real data.

from 2 weeks, individual
P · 04

Handover & training

Team training, playbook, docs, 90-day bug-fix guarantee.

Few days
Answers Frequently asked questions

What mid-sized companies ask first.

What is a "custom AI solution" specifically?

A custom architecture instead of standard tool configuration: own data models, own integration layers, own workflow logic. Useful when the last 30 % between standard solution and your reality is decisive — e.g. industry compliance, own tool landscape, hybrid on-prem/cloud setups.

When does custom pay off vs. standard?

When the standard workaround costs more than the build. Heuristic: from 3 independent "unfortunately not possible" points in a standard tool, or when the integration between 2+ tools remains manual, custom typically pays off.

What is the difference from an agency that configures tools?

We deliver code and architecture that belongs to your company — not a tool configuration in a third-party system. You retain vendor independence, can expand the stack later or continue with other providers.

How long does a complete solution take?

Discovery few days, architecture 2–3 weeks, build from 2 weeks upwards depending on scope. We start with a clear phase plan and fixed price from Phase II.

Which tools / models do you use?

Model-agnostic: Claude, GPT, open-source depending on task. Stack: Python/TypeScript, n8n, Postgres/Supabase, vector stores (Pinecone, Qdrant), Vercel/Hetzner/AWS Frankfurt. Tools are selected per use case — not the other way around.

Discuss your own complete solution.

15 min, honest, no sales theater. We clarify whether a custom solution makes sense for your case — and in what order of magnitude.