AI Consulting for Enterprises

Costs depend on scope and complexity. An AI strategy workshop starts at approximately €15,

000 (2–

3 days, including use case prioritization and roadmap). A proof of concept typically ranges between €30,

000 and €80,

000 depending on data effort and model complexity. For an initial non-binding estimate, contact us — we calculate based on your specific requirements and provide a transparent proposal within

48 hours.

A typical timeline: Use case workshop (1–

2 days) → PoC development (4–

8 weeks) → Pilot with real users (4–

8 weeks) → Production rollout (4–

12 weeks). Overall, you can expect 3–

6 months from the initial idea to a production-ready AI system. For standardized use cases on Synthara AI Studio, it can be faster — some document processing solutions go live in 6–

8 weeks.

Our strongest industry expertise lies in financial services (banking: fraud detection, credit risk, KYC/AML automation; insurance: claims processing, underwriting support, loss prevention), energy (predictive maintenance, grid optimization, smart metering), and the upper mid-market (document automation, process optimization, customer intelligence). We also advise across industries — wherever data exists and processes can be improved.

The answer is almost always: both. For standard tasks (text analysis, document processing, chatbots), we recommend using proven foundation models via Synthara AI Studio — faster time-to-value, lower costs. For competitively critical differentiation (proprietary data, industry-specific models), fine-tuning or custom model development may be appropriate. We help you make the right decision for each use case and avoid vendor lock-in through vendor-independent architecture.

Data protection is not an afterthought for us — it is an architectural principle. Specifically: Data Protection Impact Assessment (DPIA) before every AI project, privacy-by-design in system architecture, GDPR-compliant data processing (including anonymization/pseudonymization), EU AI Act compliance (risk classification, documentation obligations, transparency requirements). Synthara AI Studio supports on-premise deployment — your data never leaves your infrastructure. As an ISO 27001-certified company, we guarantee adherence to the highest security standards.

Before the project starts, we jointly define KPIs tied to your business objectives — e.g., process cost reduction (typically 30–60% for document processing), throughput time reduction, error rate reduction, or revenue growth through better personalization. In the PoC, we already measure these KPIs with real data and extrapolate the business case for scaling. Typical ROI factors for our clients: 3–10x within

12 months of going live.

Traditional AI solutions use a single model for a single task (e.g., sentiment analysis or image classification). Multi-agent systems orchestrate multiple specialized AI agents that work together to handle complex workflows — similar to a team of specialists. Example: One agent extracts data from documents, a second validates it against rules, a third generates a report, a fourth monitors quality. Synthara AI Studio is built precisely for this: it orchestrates these agents, monitors their interactions, and ensures governance. Multi-agent systems are the next evolutionary step beyond generative AI.

The biggest obstacle in AI projects is rarely the technology — it is the people. Our approach: early involvement of business units (not just IT), transparent communication about the goals and limitations of AI, hands-on training instead of PowerPoint presentations, quick wins as motivation drivers (first visible results in weeks, not months), and clear human-AI role definition (augmentation rather than replacement). Experience shows that acceptance increases dramatically when employees directly experience how AI makes their daily work easier.