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Anthropic Agency: Claude integration, assistants and agents

ANTHROPIC CLAUDE IN THE ENTERPRISE

Anthropic Claude

Anthropic Claude is a family of powerful language models: large context windows, strong reasoning and a focus on safe, reliable output.

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Claude or OpenAI? Workshop as a first step

Anthropic Claude in figures

92
1.3.0
185M

What is Anthropic Claude?

Anthropic is a US company that builds the Claude family of language models. They come in several tiers: Haiku for fast, low-cost jobs such as classifying and routing, Sonnet as the balance of speed and quality, Opus for demanding work. According to Anthropic, the current models handle up to one million tokens per request.

As a decision-maker, access is what matters most: Claude runs through Anthropic's API, Amazon Bedrock, Google Cloud and Microsoft Foundry. By default, Anthropic doesn't use API inputs and outputs for training. For every model, Anthropic states an earliest retirement date, so switches can be planned. And with the Model Context Protocol (MCP), Anthropic published an open standard for connecting assistants to tools and data sources.

Whether Claude or OpenAI suits your task better is covered further down. If several models should stay interchangeable, we build the application with LangChain.

Hand writing with a pen in a notebook on a table

From email to CRM record

Pick one of three sample emails and process it: the model fills a fixed JSON schema, we check the answer and only then write to the CRM. One email fails the check – then you see the second attempt. The answers are prepared, the schema check runs in your browser.

From:
j.berger@example.com
Subject:
Request: equipping 40 workstations

Hello, we are moving offices in spring and need monitors and docking stations for 40 workstations. Could you send us a quote by the end of the month? Best regards Julia Berger Berger Logistik GmbH

  1. 1. Prompt
  2. 2. Model
  3. 3. Schema check
  4. 4. CRM fields
{
  "type": "object",
  "required": [
    "company",
    "contact",
    "email",
    "intent",
    "urgency",
    "summary"
  ],
  "additionalProperties": false,
  "properties": {
    "company": {
      "type": "string"
    },
    "contact": {
      "type": "string"
    },
    "email": {
      "type": "string",
      "format": "email"
    },
    "intent": {
      "enum": [
        "quote",
        "support",
        "complaint"
      ]
    },
    "urgency": {
      "enum": [
        "low",
        "normal",
        "high"
      ]
    },
    "summary": {
      "type": "string"
    }
  }
}

CRM record

Company
–
Contact
–
Email
–
Request type
–
Urgency
–
Summary
–

Prepared sample answers, no live model. Emails and companies are made up, the schema check runs in your browser.

What we build with Claude

Bookable individually or as a project. If another model – or no AI at all – fits better, we tell you up front.

  • Workshop: use case and model

    Together we find the tasks where Claude saves time and test Haiku, Sonnet and Opus on your real examples. Afterwards you know which model is enough and what it costs per request.

  • Analyzing long documents

    Contracts, tenders or technical specifications reviewed in one go: Claude summarizes, spots deviations and returns results in a fixed format for your ERP or CRM.

  • Assistant with your knowledge

    Claude answers from your manuals, data sheets and databases. Relevant sections are retrieved on purpose, and every answer names its source.

  • Agents with tool use and MCP

    Claude calls tools: looking up records, creating tickets, drafting replies. We connect your systems through the API or a dedicated MCP server, with limits and approvals.

  • Claude on AWS, Google Cloud or Azure

    If your infrastructure runs with one of these providers, we use Claude there – through Amazon Bedrock, Google Cloud or Microsoft Foundry, under your existing contracts and with regional endpoints where available.

  • Operations and model changes

    We measure quality and cost per request, use prompt caching for recurring context and re-run your tests before a model is retired.

How your Anthropic Claude project runs

Cost and duration depend on scope. Our project calculator gives you a first range; the binding figure comes with the offer after the workshop.

  1. First call

    You describe the goal, the users and the systems you already have. We tell you straight away whether Anthropic Claude fits or whether another route is better.

  2. Architecture workshop

    We define the data model, interfaces and hosting and cut the scope into packages. The offer is based on that.

  3. Delivery in iterations

    We ship in short steps to a test environment, so you see every stage. Tests and code review are part of each step.

  4. Go-live and operations

    We deploy to your infrastructure or run the application for you. After that we handle updates and monitoring if you want.

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Brands that work with us

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  • Kumho Tire logo
  • Cisco logo
  • Software AG logo
  • voicecon logo
  • HanseMerkur logo
  • Sixt logo

Pros and cons of Anthropic Claude

Pros

  • Large context windows: contracts, policies or entire manuals can be analyzed in one pass.
  • Tool use and structured outputs make Claude a solid base for assistants that take actions in your systems.
  • Anthropic focuses on predictable, rule-abiding behavior, which lowers the risk of unwanted output.
  • Besides its own API, Claude is available on major cloud platforms such as AWS Bedrock and Google Vertex AI.

Cons

  • Long contexts cost money: the more text you send per request, the more each call costs.
  • Claude is a language model; image or speech output needs additional services.
  • Anthropic is a US provider, so data flows and contracts need to be reviewed with your data protection officer.
  • Models get replaced regularly, and your prompts and tests have to be rechecked with every switch.

Is Anthropic Claude right for you?

A good fit if …

  • you want to analyze and summarize long documents such as contracts, tenders or technical specifications.
  • you need an assistant that reasons in several steps and uses tools like search or database lookups.
  • your infrastructure runs on AWS or Google Cloud and you want to use the model there under existing contracts.
  • you care about controllable, traceable output in production processes.

Probably not if …

  • you mainly want to generate images or spoken audio.
  • a simple rule or a form solves the task just as well.
  • you would send huge amounts of data with every request when retrieving the relevant sections would do.
  • you want to commit to one model without testing it on real cases first.

We build with Claude

Claude suits demanding language and reasoning tasks. We bring the models safely into your processes and systems.

  • Large context windows for long documents
  • Tool use for connected actions
  • Structured outputs for deterministic processes
  • Data-protection- and governance-aware integration
Image about: We build with Claude

Claude or OpenAI?

We use both and commit per task, not up front. Four questions about your project show which way it leans, and why – the decision is made in a test with your data. The weighting follows the decision table below.

Question 1 of 4

How much text goes into one request?

All trade-offs as a table

When Claude – and when OpenAI?

We use both and decide per task, not in advance. These are the questions we settle before testing with your data:

DecisionLean toward ClaudeLean toward the alternative
Amount of text per requestClaude, if a document has to be understood as a whole – say, a contract with annexes or a complete manual.OpenAI, if large numbers of short texts are processed. Then the price of the smallest model that works reliably matters most.
Existing cloudClaude, if you rely on AWS or Google Cloud. Through Bedrock or Google Cloud, the model runs in your existing environment.OpenAI, if you're with Microsoft and want Azure OpenAI with an EU data zone. Claude is available in Microsoft Foundry too; we then clarify the data protection questions for both routes.
Agents and toolsClaude, if the assistant should use many tools across several steps and you want to connect your systems via MCP.OpenAI, if your tools are already described for the OpenAI API. Other providers support MCP by now as well, so switching isn't a fresh start.
Images and speechClaude, if text and structured data are the result. Claude can read images but not generate them.OpenAI, if the project also needs to generate images or process spoken language and you want a single provider for it.

As of October 2026

Anthropic Claude compared

Anthropic Claude next to technologies of the same category, measured with the same public sources.

Anthropic Claude compared
FigureAnthropic (Claude)LangChainOpenAI
Releases in 12 months928590
Median between releases3 days4 days4 days
Latest version1.3.0 (23/10/2026)1.6.0 (28/10/2026)7.46.0 (31/10/2026)
Downloads per month185M (npm)12M (npm)168M (npm)
Security advisories (12 months)210

Sources: OSV.dev, npm · as of 31/10/2026. Figures are indicators, not a verdict on quality. Go to the pages: LangChain · OpenAI

Reasoning over long contexts

Claude processes extensive documents in one pass. Contracts, knowledge bases and reports can be analyzed as a whole.

Tool use and structured output

Through tools, Claude performs actions and, on request, returns structured output – the basis for reliable automation.

Illustration of Reasoning over long contexts and Tool use and structured output

A focus on safety

Anthropic emphasizes predictable, compliant behavior, lowering the risk of unwanted output in production systems.

Cleanly integrable

Via API and frameworks, Claude fits into existing stacks – with clear approvals, logging and cost control.

Illustration of A focus on safety and Cleanly integrable

Selected references

Document and knowledge work

Thanks to large context windows, Claude summarizes long documents, extracts data and answers questions from your own content.

Assistants that take action

With tool use, Claude supports support, research and internal workflows – with clear limits and approvals.

Illustration of Document and knowledge work and Assistants that take action

Anthropic Claude Data & Insights

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Frequently asked questions about Anthropic Claude

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When is Anthropic Claude worth it for our company?
Claude pays off for demanding language and reasoning tasks: analyzing long documents, summarizing complex matters or modeling multi-step logic. Its large context windows really shine when you need to process a lot of text at once, such as contracts, policies or entire knowledge bases. We assess the use case upfront and pick the right model, rather than using AI for its own sake.
How do you integrate Claude into our existing systems and data?
We connect Claude through the API and use tool use so the model can trigger connected actions in your systems rather than only producing text. For up-to-date domain knowledge we link Claude to your own knowledge sources via RAG, so its answers stay grounded in your content. Structured outputs make sure downstream processes can reliably work with the results.
What sets Claude apart from other language models like OpenAI?
Claude puts a clear focus on safe, reliable output and is strong on reasoning-heavy tasks as well as very long contexts. Which model ultimately fits depends on the specific use case, your data protection requirements and cost. We don't commit in advance but evaluate against your requirements whether Claude, another model or a combination is the best choice.
How do you keep data protection and governance under control?
We design the integration with data protection and governance in mind, which means we clarify early on which data the model is even allowed to see and how approvals are handled. Through structured outputs and guardrails we keep the output controllable and traceable. That way Claude stays auditable within your process landscape instead of turning into a black box.
What drives the cost and effort of a Claude project?
The biggest factors are the scope and complexity of the use case and how deeply it ties into your data and systems. The amount of context you use also feeds directly into ongoing API costs, which is why we deliberately tailor prompts and data volumes. We set up monitoring and cost control from the start so usage and quality stay transparent; we only quote concrete numbers after reviewing your case.

Sources

As of: October 2026

Free guide

Claude & Anthropic in the enterprise: the guide

Use cases, safety and integration of Claude – concise for decision-makers and tech teams. Download now.

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An AI project with Claude?

From use-case assessment to production integration: we bring Anthropic Claude safely into your processes.

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Ready for your Anthropic Claude project?

Let's talk about your requirements – we'll get back to you within one business day with concrete next steps.

What's it about?

Discuss your project +49 (0) 2161 539 71 60
Profile picture of Paul Kalisch, Executive Partner

Paul Kalisch

Executive Partner

  1. 30 minutes by video or phone
  2. You talk directly to a partner, not to sales
  3. You get the order of steps, risks and rough costs

+49 (0) 2161 539 71 60info@next-levels.de

Related services and technologies for Anthropic Claude

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* Sources: npm (31/10/2026) · Green: strong, orange: weaker, red: notably weak, each against usual values. A pointer, not a verdict.