ARTIFICIAL INTELLIGENCE

Future

Agent-Based Enterprises (BAM, MCP, AI Gateways)

BAM — the agent platform by HO2

BAM is our platform for developing, operating, and monitoring AI agents centrally. Each agent runs in its own environment, separated per customer and with controlled access, and is connected through a lightweight interface — without you having to build your own AI infrastructure or operate models yourself.

An agent works on a defined knowledge base, answers questions in natural language, and captures requests in a structured way. The AI assistant on this website runs on BAM — what you experience here is the platform in production, not a prototype.

What BAM can do for your organization

Relieve customer contact — an agent on your website or customer portal answers recurring questions instantly, around the clock, and hands complex cases to your team in a structured form instead of letting them pile up in an inbox.

Make knowledge accessible — employees ask for documentation, process descriptions, or policies in natural language instead of searching through folders and drives. Particularly effective where knowledge sits with just a few people.

Trigger processes — the next step is connecting agents to your business systems: pre-qualifying requests, capturing document data, triggering SAP workflows. Standards such as MCP and AI Gateways keep this integration controlled and traceable — exactly where our core competence from over two decades of SAP integration lies.

How we proceed

We do not start with the technology but with the process: together we identify the use case with the greatest leverage, bring a first agent into production there, and expand from that point. This keeps the effort manageable and the benefit measurable from day one.

Available as a ready-made SaaS building block: cAItering — our AI solution for hospitality, events, and festivals →

AI Types

Analytical & Integrative AI

Definition

Analytical AI processes data, detects patterns, and generates forecasts to support data-driven business decisions. Integrative AI, on the other hand, connects different systems, data sources, and business processes, enabling information to be exchanged and processed automatically across enterprise applications. Together, these two AI approaches provide the foundation for efficient, intelligent, and fully digital business operations.

Typical Use Cases

Common applications of Analytical AI include revenue forecasting, trend analysis, anomaly detection, and automated reporting. Integrative AI is used to connect invoices, ERP systems, POS data, CRM platforms, and accounting solutions while automating cross-system business processes. Industries such as hospitality, retail, and event management particularly benefit from increased transparency, streamlined workflows, and data-driven operations.

Benefits

The combination of Analytical AI and Integrative AI reduces manual effort, minimizes errors, and provides real-time visibility into key business metrics. Organizations benefit from faster decision-making, automated workflows, improved data quality, and seamless integration across business systems. At the same time, operational costs, administrative effort, and processing times are significantly reduced.

Custom Models

Custom Models

Where standard models reach their limits, we train models on your own data — precisely tailored to your domain and your quality requirements.