Solutions
AI-Powered Products
AI product agency for German teams building copilots, automations, and data-grounded features—safety-first by design.
Who It's For
Perfect for
Products needing intelligent automation
Platforms requiring natural language understanding
Applications with predictive analytics needs
Businesses wanting to leverage AI for competitive advantage
Products requiring personalization at scale
Use Cases
Built for these scenarios
Deliverables
Everything you receive
Timeline
Typical timeline
Discovery
AI use case definition, model selection, and architecture planning
Build
AI integration, model fine-tuning, inference pipelines, and testing
Launch & Stabilize
Performance optimization, cost monitoring, and production deployment
Metrics
Success metrics
AI accuracy: Model performance meets business requirements
Response time: Sub-2 second AI inference
Cost efficiency: Optimized API usage and caching
Scalability: Handles 1,000+ requests per minute
Reliability: 99.9% uptime for AI services
Considerations
Risks & assumptions
AI model performance may require iteration
API costs can scale with usage
Hallucinations in LLMs need mitigation
Regulatory compliance for AI varies by region
Related
You might also need
AI Capability Layer
Add AI to this solution
Common AI modules teams add to accelerate support, ops, and internal workflows—without rebuilding the core product.
Start with a fixed-scope gig
If you want a quick pilot, these gigs ship fast with clear scope, deliverables, and handoff.
FAQ
Frequently asked questions
We use OpenAI GPT-4, Claude, and other leading models based on your needs. For custom requirements, we can fine-tune models or use open-source alternatives. We choose models based on accuracy, cost, and latency requirements.
We use Retrieval-Augmented Generation (RAG) to ground responses in your data, implement prompt engineering, add fact-checking layers, and provide source citations. We also set confidence thresholds.
Yes. For specialized use cases, we can fine-tune existing models or train custom models. However, most use cases work well with pre-trained models and fine-tuning, which is faster and more cost-effective.
We implement caching, batch processing, model selection based on use case, and usage monitoring. We optimize prompts to reduce token usage and choose cost-effective models when appropriate.
We implement bias detection, fairness testing, and ethical AI practices. We ensure AI systems are transparent, explainable, and fair. We follow AI ethics guidelines and best practices.
Regional
Delivery considerations for your region
Compliance & Data (EU)
For Germany/EU delivery, we keep GDPR-first patterns: data minimisation, purpose-limited storage, and explicit access boundaries.
We can work under a DPA (template available on request) and implement pragmatic retention/deletion flows when needed.
- GDPR-first architecture patterns (generic, no legal claims)
- DPA template available on request
- Retention/deletion and export flows where required
- Least-privilege access and safe logging defaults
- Documented data flows and access boundaries
Timezone & Collaboration (EU)
We align to EU working hours with CET-friendly collaboration windows and async progress updates.
We keep delivery predictable: weekly milestones, documented decisions, and clear scope control.
- EU overlap with CET-friendly windows
- Async-first delivery with written decisions
- Weekly milestone demos and progress checkpoints
- Clear change control to avoid surprises
- Escalation path for blockers and risks
Engagement & Procurement (EU)
We support procurement-friendly engagements with clear scopes, milestone plans, and documentation that stakeholders can review.
For EU teams, we can structure invoices and milestones for EUR-based engagements where appropriate.
- EUR-based engagements and invoicing options
- Discovery-first option to reduce delivery risk
- Milestone-based billing and scope sign-offs
- Vendor onboarding documentation on request
- Transparent change control and approvals
Security & Quality (EU)
We prioritise reliability: reviewable PRs, predictable releases, and tests that protect critical paths.
Performance budgets and clear release discipline keep the product stable as it grows.
- CI-friendly testing: unit + integration + smoke tests
- Performance budgets + bundle checks
- Release checklist + rollback-safe deployments
- Security checklist for auth and sensitive data flows
- Observability hooks (logs + error tracking) ready for production
Want to scope this properly?
Tell us the workflow + data sources and we’ll propose an AI roadmap with guardrails and clear next steps. EUR-based engagements.
Reply within 2 hours. No-pressure consultation.