DE Contact Discuss your project
02AI & Agentic Engineering

AI in your product.
Agents in our process.

We build AI applications that fit your systems – and use agents to build software faster. Engineers stay accountable.

Discuss your AI project Who does what?
For
Companies with a concrete use case
Start
Use case workshop
Outcome
AI running in production
Models
Cloud, EU or on-premises
Data protection
GDPR, covered by contract
Two perspectives

What we build. How we build.

ABuilt for you

AI in your product.

Applications that understand your data and take the load off your processes.

  • 01AI agents for business processes
  • 02LLM integrations
  • 03Knowledge systems with RAG
  • 04Intelligent data processing
  • 05Internal AI tools
  • 06AI features in products
BHow we work

Agents in our process.

Develop faster without giving up control.

  • 01AI-assisted development
  • 02Agentic workflows
  • 03Automated code reviews
  • 04Agentic testing
  • 05AI-supported architecture
  • QHuman in the loop
Human + agent

Who does what.

Agents do the groundwork. Humans decide.

RequirementsAI agent: Structure notesEngineer: Clarify goals with youQQ-Gate: Scope sign-off
ArchitectureAI agent: Compare optionsEngineer: Decide on the architectureQQ-Gate: Architecture review
ImplementationAI agent: Draft codeEngineer: Own the codeQQ-Gate: Code review
QualityAI agent: Generate testsEngineer: Define acceptance criteriaQQ-Gate: Pipeline green
ReleaseAI agent: Prepare deploymentEngineer: Approve the releaseQQ-Gate: Sign-off on staging
OperationsAI agent: Monitor metricsEngineer: Respond & improveQQ-Gate: Incident review
Example scenarios

What it looks like in practice.

Always the same pattern: the agent does the groundwork, a human signs off.

Document review

A
Incoming invoice Agent extracts the data and checks it against the ERP QA human reviews any discrepancies Posted in the ERP

Knowledge assistant

B
Question from the team Agent answers from your documents QEvery answer cites its source Traceable answer

Product advice

Our own product
Online shop visitor Agent advises in the chat QRules and limits set by the retailer The right product
Live at qart.chat
Approach

Into production in four steps.

1

Use case workshop

Clarify benefits, data and risks.

Fact sheet
2

Prototype

Built on your real data.

Working prototype
3

Evaluation & hardening

Measure quality, set limits.

Evals & guardrails
4

Operations

Quality and costs kept in check.

Live in production
Honest about AI

What we don't promise.

  • ✕Fully autonomous developmentAgents do the groundwork. Engineers decide.
  • ✕Black boxAnswers come with sources, decisions can be traced.
  • ✕Data without consentYou decide what a model is allowed to see.
Questions about AI

Good to know.

Whichever suit your case: large cloud models, models hosted in the EU or models on your own infrastructure.

With test cases from your day-to-day work, automated evaluations and spot checks by domain experts.

Not completely. We limit them through source grounding, validation and approvals – and make uncertainty visible.

→Next step

Let's start with your use case.

One workshop, and you'll know what AI can do for you.

Request a workshop
Your contactNikolaos KostopoulosManaging Director, shiftQ UG (haftungsbeschränkt)