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HOW IT WORKS

How Cognitive Hive Works

From regulatory requirements to production-ready AI systems

From Data to Intelligent Decisions

1
Your Data
BPMN · Standards · Rules
2
Graph
Context Cells
Knowledge Graph · Connected · Semantic
3
AI Agents
Specialized · Coordinated · Learning
4
Human Review
Control · Correction · Approval
5
Result
Decision · Reasoning · Audit
Minutes instead of Weeks
Automated preparation
100% Traceable
Every step documented
Human decides
AI only supports
Legally secure
Audit-ready & compliant

Generation Pipeline & Context Packages

From regulatory requirements to deployable case-system components.
Build/Eval/Deploy — automated, quality-assured, production-ready.

Understand Knowledge Graphs → Intelligent Building Blocks →

Supported Process Standards (BPMN, FIM, KGSt, ...)

Supported Process Standards

Cognitive Hive understands and processes established public administration standards – for seamless integration into existing process landscapes.

BPMN 2.0

Business Process Model & Notation

Import your BPMN diagrams directly. Our AI agents understand activities, gateways and sequence flows – and generate executable applications from them.

Process Models Workflows DMN

FIM

Federal Information Management

Leverage the federal repository for administrative services. Master data on services, processes and data fields is automatically integrated.

Service Catalog Process Library Data Fields

KGSt

Municipal Community Center

KGSt process models and product plans as foundation. Best practices from over 2,000 municipalities flow directly into your applications.

Product Plan Process Registry KPIs

XÖV Standards

XML-based data exchange formats for e-government

OZG Services

Online Access Act compliant administrative services

SAGA

Standards and architectures for e-government

Custom Processes

Your individual workflows and procedures

Import Standard
AI understands Context
Generate App
Deploy to Production

The Pipeline in 3 Steps

1 Ingest & Structure

Regulations, process standards, and laws are ingested and organized into versioned Context Cells — traceable and with clear accountability.

2 Build & Evaluate

AI agents assemble Context Cells into deployable Composables (PBCs) — including process logic, UI, and automated quality assurance.

3 Deploy & Operate

Production release with complete audit trail. Ongoing monitoring, rule updates and continuous improvement included.


Specialized AI Agents in Detail

Specialized AI Agents

No generic chatbots — specialized agents that work together in coordination. Each agent receives its own context package and is governed by clear policies.

Analysis & Compliance

Understand documents, extract requirements, check rules and identify risks.

Build & Integration

Model processes, generate components and connect systems.

Quality & Operations

Validate results, test artifacts and monitor production quality.

Coordinated Collaboration: The agents communicate, share context and orchestrate complex tasks together — governed by Hive policies.


Agentic Factory (End-to-End)

From knowledge ingestion to citizen application — the complete transformation pipeline.

1. Knowledge Ingestion

Normalization, structuring & interactive refinement

2. Eval & Build

Shadow mode tests, IT specs & UX generation

3. Deploy & Operate

Production release with monitoring & maintenance


The AI Assistant for Your Authority

The AI Assistant for your authority

Employees receive traceable answers from all authority knowledge – structured, source-based and always current.

Precise Answers

Questions about regulations, processes or responsibilities are answered directly from the Knowledge Graph – not guessed.

With Source References

Every answer contains references to underlying documents – paragraphs, guidelines, process descriptions.

Structured & Clear

Complex matters are clearly presented – with steps, checklists and recommendations.

Typical Use Cases

Regulation Info
"What deadlines apply to this application?"
Process Help
"What is the process for objections?"
Responsibilities
"Who is responsible for this case?"
Phrasing Help
"How do I formulate this justification?"
NOT LIKE CHATGPT
No hallucinations
TRACEABLE
Every statement verifiable
DATA SOVEREIGN
Your knowledge stays with you
ALWAYS CURRENT
Automatically synchronized

Quality Criteria

Tests & Validation

  • Shadow mode (parallel test run without impact) against real cases
  • KPI framework: Quality / Bias / Speed
  • Routing & fallback per skill/cell (Model Router)
  • Automated regression tests

Action Gates

  • Tool calls only via Hive roles & policies
  • Forbidden actions automatically blocked
  • Autonomy level 0–3 per cell
  • Complete audit trail for every action

Context-Flow Overview

Context-Flow: Unstructured Data → AI Agents → Context Cells → Composable → Case Cell Context-Flow: Unstructured Data → AI Agents → Context Cells → Composable → Case Cell
Enlarge
From unstructured data to executable Composables
Context-Flow: Unstructured data → AI Agents → Context Cells → Composable → Case Cell Context-Flow: Unstructured data → AI Agents → Context Cells → Composable → Case Cell

Production Operations for AI Solutions
OPERATE

Production Operations for AI Solutions

On-Premise or Cloud · OSS Ecosystem · Production-Ready

Monitoring & KPIs

  • Real-time dashboards
  • Quality/Bias/Speed metrics
  • Automatic alerts
  • Performance tracking

CI/CD Pipeline

  • Automatic deployment
  • Shadow mode testing
  • Rollback capability
  • Blue/Green deployments

Registry & Versioning

  • Agent registry
  • Skill catalog
  • Version management
  • Dependency tracking

Deployment Options

On-Premise
Full control
Private Cloud
EU providers
Hybrid
Flexibly combined

Frequently Asked Questions

Why not just use rule mapping (Law-as-Code)?

Rule mapping is excellent for clear, static decision logic. Cognitive Hive targets dynamic rule application with connected knowledge: norm references, context retrieval, deep audit chains, automatic updates — especially valuable with high norm density and complex dependencies.

How long does pipeline setup take?

Initial setup for a pilot use case typically takes 4–8 weeks, including knowledge ingestion, context cell modeling and shadow mode evaluation. Production rollout follows after successful validation.

What happens when an agent makes a mistake?

Every action is logged with full provenance. Errors trigger automatic escalation based on autonomy levels. The Why-Graph enables root cause analysis, and Replay allows re-executing decisions with corrected rules.


The Intelligent Process — Citizens, AI and Case Workers

The Intelligent Process

Citizens, AI and case workers collaborate seamlessly

Citizen starts
Portal · Chat · App
Application captured
Documents & Data
AI analyzes
Rules & Context
Follow-up
Citizen adds info
Subsumption
Rule → Result
Case worker
Reviews & approves
Decision
Notice issued
Citizen receives
Decision + explanation
CITIZEN PORTAL
Submit applications, track status, ask questions – all digital
INTERACTIVE DIALOG
AI asks follow-ups, citizen responds – no waiting
TRANSPARENT REASONING
Citizens understand why – every step explained
PROACTIVE UPDATES
Citizens are automatically informed about progress
HUMAN DECIDES
Case worker reviews, corrects and approves
FEEDBACK LOOP
Citizens rate service – system learns continuously

From Idea to Productive Building Block in Weeks

See in 30 minutes how your processes can be transformed with Cognitive Hive — with full transparency and Human-in-the-Loop.

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