Private AI & Enterprise LLM Guides

Enterprise Data Fragmentation: The Scale of the Challenge

Enterprise data environments are fragmented across hundreds of systems, making access, trust and orchestration difficult. Scalytics Federated unifies Kafka, Flink and Apache Wayang to provide real time execution, federated access and an assistive data concierge for faster insights. This architecture reduces integration effort and enables immediate value without centralizing data.

Author:

Dr. Mirko Kämpf

Strategic Proposal Assistant: Governed, Data-Local AI for Enterprise Bid Management

This article explains how the Strategic Proposal Assistant uses ACP governance and data-local execution in Scalytics Federated to analyze project briefs securely and accurately. It shows how the system verifies claims, evaluates capabilities, and produces defensible recommendations grounded in distributed internal knowledge.

Author:

Dr. Mirko Kämpf

Deep Search AI: Grounded, Trustworthy Enterprise Search

Enterprise search needs more than semantic similarity. Our Deep Search Optimization (DSO) Agent delivers grounded results with source citations, trust scores based on source authority, and relevance ranking tuned to your domain—eliminating hallucinations in high-stakes knowledge retrieval.

Author:

Alexander Alten

SynthLink Benchmark: Testing Enterprise AI Accuracy

How accurate is your enterprise AI on complex queries? SynthLink benchmark tests multi-hop reasoning, evidence chain construction, and fact verification across 60 carefully designed questions. Evaluate Llama, Mistral, GPT-4, and Claude on real enterprise knowledge tasks.

Author:

Alexander Alten

Enterprise LLM Runtime: Deploy Open Source Models Securely

Deploying Llama or Mistral in production requires more than a GPU. Enterprise LLM runtime needs request queuing, prompt injection protection, context window management, token budgeting, and audit logging. Scalytics Connect provides the missing operational layer for self-hosted AI.

Author:

Alexander Alten

AI Agent Framework: Build Agentic RAG with Data Control

This article explains why AI agents must operate at the edge and why enterprises need a control layer to govern their workflows. It introduces the Agent Context Protocol as the foundation for secure, auditable multi agent systems that work on real time data without centralization.

Author:

Alexander Alten

Building Governed Multi Agent Systems with MCP and the Agent Context Protocol

This article explains how Scalytics Federated extends the Model Context Protocol with the Agent Context Protocol to govern multi agent systems. It shows how ACP adds policy based access control, auditability, and secure communication, enabling agents to collaborate across environments without losing compliance or control.

Author:

Dr. Mirko Kämpf

Multi-Agent LLM Systems: Collaborative AI Architecture

Single AI agents hit capability limits. Multi-agent systems combine specialized agents—researchers, analysts, critics, executors—that collaborate through structured communication. Learn architecture patterns powering autonomous research, code generation, and complex enterprise workflows.

Author:

Dr. Tristan Behrens

Private AI: Enterprise LLM Deployment Guides

Enterprise Data Fragmentation: The Scale of the Challenge

Strategic Proposal Assistant: Governed, Data-Local AI for Enterprise Bid Management

Deep Search AI: Grounded, Trustworthy Enterprise Search

SynthLink Benchmark: Testing Enterprise AI Accuracy

Enterprise LLM Runtime: Deploy Open Source Models Securely

AI Agent Framework: Build Agentic RAG with Data Control

Building Governed Multi Agent Systems with MCP and the Agent Context Protocol

Multi-Agent LLM Systems: Collaborative AI Architecture