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Implement Claude AI.
We bring AI into your company.

Connected to your systems. GDPR-compliant. From pilot to live operation.

Anthropic Logo - BI2run

Why does Claude AI implementation so often get stuck in the pilot phase?

Anyone introducing Claude AI in a company knows these four hurdles. There’s a clear answer for each.

Problem
AI doesn’t know your data
Solution
First data preparation and sourcing. Then connection to ERP, BI, and CRM via MCP
Problem
No use case with measurable benefit
Solution
Use case with ROI defined up front in the workshop
Problem
Data protection and governance unresolved
Solution
Roles, permissions, and the EU AI Act built into the solution
Problem
The team doesn’t use it
Solution
Training and champions during rollout

Why Claude?

Four qualities that matter in enterprise use. Backed by independent benchmarks.

82.7%

Precise with financial data

Accuracy in the FinanceBench test: finding the right figure in annual reports hundreds of pages long.

FinanceBench, Opus 4.7
64.4%

Agent-ready

Leading the Finance Agent benchmark for multi-step analyses with tool use. Accesses real systems via MCP.

Finance Agent v1.1, top score
Safety

Secure

Anthropic develops Claude with a focus on traceable behavior. Important for regulated industries.

Constitutional AI
1M

Large context

Up to one million tokens in a single pass. Entire reports, contracts, or datasets at once.

Opus, 1M context window

Where does Claude AI create value in a company?

Six areas where Claude takes the load off in everyday work after rollout.

Knowledge access

Questions to internal documents in natural language, with sources.

Reports & analyses

Analyses from BI systems, commented and prepared.

Customer communication

Quotes and follow-ups straight from the CRM context.

Document processing

Read, review, and pass on contracts and invoices in a structured way.

Process agents

Multi-step workflows that Claude runs on its own.

Controlling & finance

Reporting and forecasts directly in TM1 and Power BI.

IBM Planning Analytics x Claude Logo

Focus on finance & controlling?

We implemented the integration for IBM Planning Analytics (TM1) in detail: read, comment, write values back, calculate forecasts.

View Claude × TM1 →

How does Claude AI implementation work?

Four steps from idea to live operation.

01

Workshop

Identify use cases, review systems and data situation

Week 1
02

Pilot

Data preparation, integration, one case on real data

Weeks 2 to 6
03

Rollout

Training, governance, champions in the team

Weeks 7 to 12
04

Operation

Support, updates, further development

Ongoing

Most AI projects don’t fail because of the technology.

The first test goes well, then nothing follows. Most of the time it’s not the model, but three points nobody clarified beforehand.

95%

of AI projects fall short of expectations, mostly without integration into processes.

MIT, State of AI in Business Report 2025
19%

of large companies truly integrate AI agents into their core processes.

Civey / Hochschule der Medien, 2026
82%

of companies in Germany report productivity gains from generative AI.

IW Köln

Frequently asked questions about Claude AI implementation

No. We’ll work that out in the workshop and find the use case with the clearest benefit.

Yes. We clarify rights, data flows, and the EU AI Act up front. Access stays role-based and logged.

Claude is strong at precise work with documents and numbers and can be connected deeply to real systems. We’ll work out honestly in the intro call which model fits.

A first pilot is usually up in a few weeks. The rollout depends on scope and systems.

It depends on the use case and system integration. After the workshop you’ll get a concrete quote.

Your Claude AI implementation
starts with a conversation.

Free and non-binding.

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