Know Your LLM Series: Claude

Anthropic's Claude has gained traction among teams looking to integrate AI into their data workflows. It offers solid reasoning capabilities, strong coding performance, and works well with the Model Context Protocol (MCP), Anthropic's open standard for connecting AI to external systems. Security and compliance have been priorities in its design, which matters for organizations in regulated industries.

In this article, we will walk through how Claude fits into modern data platforms, with a focus on using it alongside CData Connect AI. We will cover the model family, platform capabilities, and practical considerations like security and governance. We will also explore how Claude and CData Connect AI can work together to provide natural-language access to enterprise data.

Overview of the Claude model family

Claude is a family of large language models built by Anthropic. It's designed with enterprise use cases in mind, prioritizing reliable outputs over experimental features.

Claude processes every request using its full model rather than routing queries to specialized components, which can help produce more consistent results when working with structured data. Anthropic has also built safety guidelines directly into the training process, an approach called Constitutional AI, which shapes how the model handles requests.

Anthropic doesn't publish parameter counts. Instead, they organize Claude into three tiers based on what you need:

• Claude Haiku – Built for speed and lower costs. Works well for lightweight tasks and high-volume scenarios.
• Claude Sonnet – A middle-ground option that balances capability and cost. This is what most enterprise teams start with.
• Claude Opus – The most capable tier, suited for deep analysis, complex reasoning, and longer tasks.

This setup lets you pick a model based on your workload rather than getting lost in technical specs.

Current Claude model variants

All current Claude models support 200K token context windows. That's enough room to include full documents, database schemas, codebases, and metadata in a single request which is useful for analytics and multi-step workflows.

Let's look at how the current models compare:

Claude model family (Generation 4.5)

Here's a closer look at the latest 4.5 generation:

Claude performance on the LLM Leaderboard 2025

The Vellum LLM Leaderboard 2025 provides independent benchmark data across leading AI models. Claude ranks among the top performers, with strength in coding, visual reasoning, and multilingual tasks.

Benchmark leadership

Claude leads several key benchmarks relevant to enterprise data and development workflows. Here's where Claude currently ranks highly:

Claude Sonnet 4.5 and Opus 4.5 hold the top two positions on SWE Bench, outperforming GPT 5.2 and Gemini 3 Pro at resolving real GitHub issues.

Model selection guidance

If you are not sure which model to pick, this table can help:

If you are using CData Connect AI, these results translate into more accurate SQL generation, better schema comprehension, and more reliable agentic workflows across enterprise data sources.

Multimodal understanding and computer use

Claude isn't limited to text. It can process images, PDFs, charts, diagrams, code, and structured documents. This comes in handy for enterprise analytics where data arrives in different formats.

Specifically, Claude can interpret:

• Charts and graphs
• Tables and forms
• Technical diagrams
• Scanned documents and PDFs

Claude also offers a computer use mode, currently in beta, that allows it to interact with desktop environments. In this mode, Claude can move the cursor and click through interfaces, navigate applications and internal tools, and perform step-by-step actions inside a desktop environment.

API, authentication, security and rate limits

Claude is accessed through a simple and secure API designed to be easy to integrate while meeting enterprise reliability requirements. Working with Claude's API is straightforward. Let's break down the key pieces.

Authentication

Each request to the Claude API is authenticated using an API key, which is passed in the request headers. This ensures that only authorized applications can access the service.

Along with the API key, requests include an API version header. This ensures consistent behavior over time, even as the platform evolves, and new capabilities are introduced.

Making an API request

A typical request includes:

• Your API key (x-api-key)
• The API version (anthropic-version)
• A JSON payload with the model name, response length, and messages

Security considerations

Claude's API is built for enterprise use:

• Requests are encrypted in transit
• API keys should be stored securely and never exposed in client-side code
• Versioned APIs help prevent unexpected changes in production systems

Together, these practices make Claude suitable for secure, production-grade deployments.

Rate limits scale with usage tiers

Let's now see how the rate limits work across different tiers:

Core platform capability

One of Claude's strengths is its ability to work as an AI agent that not just answers questions, but also reasons through problems and use tools to complete tasks. This matters for data workflows where you need the AI to interact with databases, APIs, and other systems.

Foundational tools

Claude comes with several built-in tools that handle common agent tasks without requiring complex setup.

• Code Execution Tool (Beta) – Runs Python and Bash in a sandboxed Linux container with 5 GB of memory and disk space. Internet access is disabled for security. Common libraries like pandas, NumPy, and matplotlib are included.
• Bash Tool – Runs command-line instructions in a persistent session. The environment remembers your working directory and variables throughout the conversation.
• Text Editor Tool – Reads and edits files, creates new ones, and can replace or insert text at specific locations.
• Memory Tool (Beta) – Stores information across conversations in a dedicated directory, making interactions feel more consistent over time.

Advanced tool orchestration

Beyond basic tool usage, Claude provides advanced orchestration features that allow agents to handle larger, more complex workflows efficiently.

• Programmatic Tool Calling (Beta) – Instead of calling tools one at a time, Claude can write Python scripts that chain multiple tools together. This speeds things up and reduces token usage.
• Tool Search Tool (Beta) – When you have hundreds of available tools, this feature lets Claude search the catalog and load only what it needs. This can save 10,000–20,000 tokens per request.

Agent SDK

The Claude Agent SDK is a developer library that simplifies building and running AI agents. It is available in TypeScript and Python and handles tool execution, context management, and error handling and retries. The SDK lets developers focus on using the agent's output rather than managing the complexity of how the agent works behind the scenes.

Claude's MCP

MCP (Model Context Protocol) is Anthropic's open standard for connecting Claude to external systems. It uses JSON-RPC 2.0 and provides a consistent way for the model to use tools, access resources, and run workflows.

With MCP, Claude can:

• Query databases
• Fetch documents
• Call APIs
• Transform data
• Execute scripts in controlled environments

Enhanced reasoning and output control

Claude includes features that give you more insight into how it thinks and more control over its responses.

Extended thinking

Extended Thinking lets Claude work through complex problems step by step before responding. When enabled, the API response includes "thinking" sections that show the reasoning process. This is helpful for debugging and understanding why Claude reached a particular conclusion.

Structured outputs (Beta)

Sometimes you need responses in a specific format. Structured Outputs let you define a JSON Schema, and Claude will match it exactly. This eliminates parsing headaches and makes it easier to integrate Claude into automated pipelines.

Prompting, reliability, and long-context behavior

Claude handles structured data tasks well and has a solid understanding of SQL. Hallucination rates tend to be lower than some alternatives, especially when working with well-defined schemas. The large context window means you can include full schema definitions, governance rules, documentation, and sample queries; all in one request. This helps Claude produce more accurate outputs.

A few prompting tips:

• Define the model's role clearly
• Use natural language for tool descriptions
• Include examples when possible
• Be explicit about output formats
• Handle ambiguous cases with clear instructions

For repeated tasks, prompt caching can reduce costs and latency.

Security, compliance, and data governance

Claude is built with enterprise requirements in mind. The platform holds several certifications:

• SOC 2 Type II
• ISO 27001
• ISO 42001
• HIPAA-ready
• GDPR-compliant practices
• CSA STAR Level 2

Data is encrypted at rest and in transit. For API customers, inputs and outputs are deleted within 30 days by default. You can also enable Zero Data Retention (ZDR) if you need it. Customer data isn't used for training unless you explicitly agree.

Using Claude with CData Connect AI for intelligent data workflows

Claude and CData Connect AI work together naturally. Claude understands schemas and can generate SQL. CData provides secure, real-time connectivity to enterprise data sources. Combined, they form the basis for agentic data systems that can discover, query, summarize, and orchestrate large amounts of information.

Typical workflow

• Expose schemas and metadata to Claude through system prompts or MCP resources
• Allow users to ask natural language queries
• Claude generates SQL
• CData Connect AI executes the query, using governed, role-aware access controls
• Claude interprets and summarizes the results for users

CData as an official connector inside the Claude interface

CData is now an officially supported connector inside Claude's interface. You can connect directly to live enterprise data sources, enabling natural language queries with proper governance and security controls.

This integration offers direct exploration of business data inside the Claude experience, live natural language to SQL with governance and source-level security, secure, policy-aligned access powered by CData's connectivity engine, and a consistent data layer for multi-source analytics and agentic workflows.

Claude Projects

If you find yourself repeating the same setup instructions in every conversation, Projects can help. A Project acts as a persistent workspace where you store context that Claude references automatically, and schemas, rules, and background information stay available across conversations.

Here is what you can store in a Project:

• Documents – PDFs, text files, or reference material
• Instructions – Guidelines for behavior, tone, or rules to follow
• Code and schemas – Database schemas, API specs, or code samples
• Examples – Sample queries, expected outputs, or templates

For teams using CData Connect AI, Projects let you store connection context, schema definitions, SQL conventions, governance rules, and example queries in one place. With this context available, Claude generates more accurate SQL from the start and no clarifying questions about table names or guessing at your schema.

Projects also pair well with Claude Code, letting you store coding standards and project-specific patterns that carry across development sessions.

Development automation with Claude Code

Claude Code extends the model's capabilities directly into the software development workflow. It transforms Claude from a passive assistant into an active development partner that can maintain context, follow rules, and apply engineering patterns consistently.

Key components include:

• A claude.md rules file that defines how the model behaves inside the project
• Custom Slash Commands that codify multi-step workflows
• Sub-agents that specialize in tasks like testing, documentation, or analysis
• Hooks that let you attach automated actions after agent operations
• Integration with GitHub CLI for full end-to-end workflows, from issue to PR
• Safe fully autonomous modes using dev containers
• Parallel agent execution using git work-trees

When combined, CData Connect AI + Claude Code can generate ETL scripts, build integration code, create SQL migrations, and document data pipelines.

When Claude is the right choice

Claude works well when you need:

• Deep reasoning – Working through large documents and complex calculations
• Data privacy – Enterprise-grade compliance and governance
• Long-context handling – Analyzing extensive documentation or codebases
• Consistent outputs – Predictable responses across similar requests

It's particularly strong for coding tasks, schema comprehension, structured outputs, and document understanding.

How enterprises are using Claude today

• Financial Services: Bridgewater Associates uses Claude for investment analysis, reporting 50–70% faster time-to-insight on complex financial reports. NBIM (Norway's sovereign wealth fund) saved an estimated 213,000 hours through productivity improvements. AIG compressed underwriting review times by 5x while improving accuracy.
• Automotive: Cox Automotive integrated Claude across their CRM and dealer platforms. Lead responses more than doubled, and content creation went from weeks to same day.
• Technology: Palo Alto Networks saw 20-30% faster feature development. Zapier runs 800+ internal Claude agents with 10× year-over-year growth in completed tasks.
• Strategic Partnerships: Accenture is training 30,000 professionals on Claude. IBM, Cognizant (350,000 employees), and Databricks (10,000+ customers) have all formed partnerships to bring Claude into enterprise workflows.

Simplify Claude connectivity with CData

CData Connect AI makes it easy to connect Claude with your enterprise data sources, BI tools, and analytics platforms. With the official CData connector inside Claude's interface, you can enable natural language queries against live data, eliminating manual steps and enabling smooth, automated data integration.

Ready to get started? Download a free 14-day trial of CData Connect AI today! As always, our world-class Support Team is available to assist you with any questions you may have.