What does AI feature integration cost?

Costs depend on the scope. A scoping workshop takes 1-2 days and serves as the basis for a realistic effort estimate. Sprint-based implementation typically starts in the low five-figure range. Since AI features are integrated as add-ons to existing engagements, separate project overhead is eliminated.

Do I need my own AI infrastructure?

No. We use your existing infrastructure and extend it strategically. Cloud APIs (Azure AI, OpenAI) are suitable for many use cases. For sensitive data, we deploy local LLMs — hosted on your own or EU-based infrastructure.

How do you protect our company data?

Data protection is part of every solution. We implement access controls, audit trails, and GDPR-compliant data processing. For particularly sensitive data, we work exclusively with local models and European infrastructure. Your data never leaves your control.

Does this work with our existing systems?

Yes. We have experience integrating with ERP systems, CRM platforms, ticketing systems, and custom software. Through APIs, webhooks, and middleware, we connect AI capabilities with your existing workflows.

How long until we see initial results?

After the scoping workshop (1-2 days), we start implementation immediately. First working AI features are typically in use after 2-4 weeks. Through the sprint-based approach, you see concrete progress after each cycle.

Can I add AI features later to an ongoing Krafteq engagement?

Yes. That is exactly what this service is designed for. AI features are an optional add-on you can activate at any time — regardless of whether you already have a Managed Squad, a project, or staff augmentation with Krafteq.

What happens when the AI makes mistakes?

Every AI solution has limitations. That's why we build in feedback loops, human review steps, and monitoring. The automation doesn't replace decisions — it prepares them. The models improve through continuous learning from corrections.

Which AI models do you use?

We select the appropriate model for each use case. For text understanding and generation, we use OpenAI, Azure AI, or local open-source LLMs. For classification and search, we rely on proven ML frameworks with Python. The decision is based on data privacy, cost, and performance — not trends.

Isometric illustration of an AI automation system with interconnected workflow modules and data streams

Hyperautomation & AI Features

AI-Powered Automation for Businesses

Pragmatic AI integration with measurable ROI

Your employees spend hours on tasks a machine can handle in seconds. At the same time, you lack a clear plan for where AI truly adds value. We integrate pragmatic AI capabilities into your existing systems — with measurable ROI instead of hype.

60 % Support Tickets Automatically Categorized

35 % Shorter Processing Time

Request a Free Scoping Workshop

Result at a service company (200 employees): 60 % of support tickets automatically categorized, 35 % shorter processing time.

ChallengesWhy AI automation is critical right now

Repetitive tasks cost time, money, and motivation. Yet many AI projects fail because they are planned as major initiatives. The market is moving fast — companies that don't automate now lose efficiency and competitiveness.

Manual processes are slowing your growth

Support tickets are sorted by hand. Documents go through approval loops via email. Knowledge lives in people's heads and scattered files. These manual workflows don't scale. Your operating costs rise while quality drops.

AI hype without substance

Many providers promise an AI revolution. But the concrete connection to your business processes is missing. You don't need a 50-page AI strategy. You need working automation that delivers results next week.

Lack of governance slows adoption

Data privacy, access controls, and traceability are critical for German businesses. Without clear governance, nobody dares to deploy AI in production. Many initiatives get stuck at the pilot stage.

BenefitsBenefits at a glance

Krafteq combines AI engineering with pragmatic craftsmanship. Our AI features deliver measurable results instead of endless evaluations.

Immediately measurable relief

Less manual work from the first sprint. Your teams focus on value-adding tasks instead of routine activities.

Pragmatic integration instead of rebuilding

We extend your existing systems with AI capabilities. No platform switch, no risk. The AI works where your data already lives.

Governance from the start

Access controls, data privacy, and audit trails are a permanent part of every solution. Especially important for GDPR-compliant organizations and regulated industries.

Works as an add-on to any Krafteq service

Whether enterprise platform or SME software — AI features can be integrated into any engagement. As an optional building block, not a separate project.

Transparent ROI

Before we start, we define KPIs together. After each sprint, we measure progress. You always see what the automation delivers.

Experienced engineers instead of experimentation

Senior engineers with production experience implement your AI features. No interns, no experiments. Speed with discipline.

ProcessHow the collaboration works

This process works regardless of the engagement model. Whether as part of a Managed Squad, within a project, or as an extension of a staff augmentation — the AI features adapt to your collaboration with Krafteq.

Scoping workshop

Together, we identify the processes with the highest automation potential. We assess data quality, technical feasibility, and expected ROI. The result is a prioritized implementation plan with concrete sprint goals.

Clear plan with 2-3 quick wins and a realistic effort estimate.

Sprint-based implementation

We implement AI features in 2-week sprints. Each sprint delivers a working enhancement: a workflow assistant, document automation, or knowledge search system. You test immediately with real data.

Working AI features after every sprint — directly in the production system.

Measurement and optimization

After rollout, we jointly measure the actual impact. Automation rate, processing times, error rates — all transparent and traceable. Based on the data, we continue to optimize iteratively.

Documented ROI and continuous improvement.

ServicesWhat we concretely implement

From workflow assistants to data-driven decision support — every solution is pragmatically integrated into your existing systems.

Assistants for internal workflows

AI assistants that support your employees with daily tasks. Accelerate proposal creation, pre-draft customer communications, automate reporting. The assistants work context-aware within your existing tools.

Intelligent document and ticket automation

Automatic classification, routing, and processing of documents, emails, or support tickets. The system learns from your historical data and improves with every interaction.

LLM-powered search and knowledge systems

Enterprise-wide search across internal documents, wikis, and databases — using natural language. Your employees find answers in seconds instead of hours. Including governance: access controls are inherited from existing systems.

Data-driven decision support

Automated reports, anomaly detection, and forecasts based on existing data. No complex data science initiative — but pragmatic analytics that help decision-makers act faster and more informed.