What is Claude? How Anthropic's AI works, what it can do, and where it falls short

By the LinkinGrow editorial team. Published September 28, 2026. Written for US business, marketing, and technology leaders. About a 16 minute read.

Claude is a family of AI models and an assistant built by Anthropic, a US AI safety and research company. It writes, analyzes documents, reasons through problems, writes code, and can search the web when that feature is turned on. It is careful by design, but careful is not the same as correct.

Like other assistants, the name covers several layers: the models themselves, the Claude apps, the Claude Code tool for developers, the API, and versions offered through major cloud providers. They share technology but differ in features, limits, and data terms.

This guide focuses on the structure that stays stable rather than any single model version. Anthropic updates model names, plan limits, and features often. Anyone making a purchasing or compliance decision should confirm current documentation and contract terms.

What Claude actually is

Claude is a large language model: a system trained on very large amounts of text and code to predict and generate language. Recent Claude models also accept images and documents such as PDFs, so they can read charts, screenshots, and scanned pages alongside written instructions.

Anthropic was founded in 2021 and is based in San Francisco. The company describes its mission around building AI systems that are reliable, interpretable, and steerable. That focus shows up in how Claude is trained and in the published policies that govern its behavior.

Claude models are released in tiers. Larger models handle complex reasoning and long, multi step work. Smaller models respond faster and cost less, which suits high volume tasks. Some models offer an extended thinking mode, in which the model works through a problem in more steps before answering.

How Claude is trained

Claude begins as a pretrained model that learns patterns from public web data, licensed data, and other sources described in Anthropic's documentation. It is then refined so that it follows instructions and behaves helpfully and safely.

Constitutional AI

Anthropic's distinctive method is called Constitutional AI. Instead of relying only on people rating individual responses, the model is guided by a written set of principles, its constitution, and learns to critique and revise its own outputs against them. Anthropic has published the principles and the research behind the approach.

In practice this tends to make Claude more likely to explain its reasoning, acknowledge uncertainty, and decline clearly harmful requests. It does not make Claude a source of truth. The constitution shapes behavior; it does not add facts the model never learned.

Training cutoff

Each model has a training cutoff. Without search or supplied documents, Claude knows nothing about events after that date and may present outdated information confidently. Treat any answer about prices, people, or recent news as unverified unless it cites a current source.

How Claude creates an answer

A Claude response is assembled from several inputs. Understanding them explains why two people asking the same question can see different answers.

1. 1. Context. The conversation so far, any system instructions, project knowledge, and uploaded files. Claude supports very long context windows, so it can work across entire reports or codebases.
2. 2. Model knowledge. What the model absorbed during training, up to its cutoff.
3. 3. Tools. When enabled, web search, connected apps, or code execution add current or private information.
4. 4. Generation. The model writes the answer word by word, choosing likely continuations. This is why wording and emphasis vary between runs.

Web search and citations

Claude can search the web in supported plans and through the API. When it does, answers include citations to the pages it used. Search is not always on and not used for every question, so a response without citations likely came from training data or the conversation alone.

Connected tools

Through integrations and the Model Context Protocol, an open standard Anthropic introduced in 2024, Claude can connect to services such as document stores, calendars, and business systems. This lets it answer from a company's own data, subject to the permissions an administrator grants.

The Claude product family

Within the apps, Projects let teams keep shared instructions and reference files together, and Artifacts display documents, code, and small interactive tools in a separate panel beside the chat. Research features can run multiple searches and compile a longer, cited report.

What Claude can do well

• Long document work. Summarizing, comparing, and extracting from contracts, filings, and research that would exceed other tools' limits.
• Writing and editing. Drafting in a specified tone, restructuring arguments, and tightening prose.
• Software development. Reading, explaining, and changing code, including multi file changes through Claude Code.
• Structured analysis. Working through options, spreadsheets, and data with visible reasoning.
• Following detailed instructions. Adhering to formats, style guides, and constraints across a long task.

These strengths are reported by Anthropic and reflected in public benchmarks, but benchmark scores do not predict performance on a specific company's work. Test with your own tasks.

Where Claude falls short

It can still be wrong

Claude can produce confident statements that are false, including invented quotes, figures, or references. Anthropic acknowledges this in its documentation. A calm, well reasoned tone makes errors easier to miss, not less likely.

Citations need checking

When Claude cites a page, the page may not say exactly what the answer claims. Open the source and confirm the specific statement before relying on it.

Answers vary

The same question can produce different emphasis, different examples, and different named companies from one run to the next. A single test says little about what users typically see.

Caution can cost usefulness

Claude sometimes declines or hedges on requests that are legitimate. Anthropic has worked to reduce unnecessary refusals, but teams in regulated or sensitive fields should test their real use cases.

Privacy, data controls, and business use

Data terms depend on the account type. For consumer plans, Anthropic's privacy policy explains how conversations are stored and gives users a setting that controls whether their chats may be used to improve models. For commercial products, including Claude for Work plans and the API, Anthropic states that it does not train its models on customer content by default.

Enterprise plans add administrative controls such as single sign on, role based permissions, audit logs, and custom data retention. Organizations with strict requirements should review Anthropic's commercial terms and Trust Center, and the terms of any cloud provider through which they access Claude.

A practical rule: decide which information employees may share before rollout, choose the plan whose terms match that decision, and review it whenever Anthropic updates its policies.

Claude and brand discovery

Buyers increasingly ask assistants to shortlist vendors, compare products, and explain categories. When they ask Claude, the answer may name some companies and omit others. That shortlist forms before anyone visits a website.

The following is LinkinGrow analysis, not Anthropic documentation. Claude's answers draw on two broad sources: what the model learned in training and what it retrieves through search at the time of the question. A company is more likely to be described accurately when its official information is clear and accessible, its facts are consistent across the web, and credible independent sources discuss it.

Because answers vary, visibility has to be measured rather than assumed. That means asking real buyer questions repeatedly, recording whether the company is named, cited, or recommended, and checking whether the description is correct. Anthropic sells no paid placement in Claude answers, and no provider can honestly guarantee one.

How to evaluate Claude responsibly

1. 1. Record the environment. Note the product, model, plan, whether search was on, the date, and relevant settings.
2. 2. Use representative work. Test real tasks after removing information your plan is not approved to receive.
3. 3. Define a scoring rule. Measure accuracy, source support, completeness, consistency, and task completion.
4. 4. Repeat the test. Run each prompt several times and keep every output, not only the best one.
5. 5. Check the sources. Verify each material claim and citation against the original.
6. 6. Keep people accountable. Assign qualified reviewers wherever output influences a decision.

Frequently asked questions

Who makes Claude?

Claude is made by Anthropic, an AI safety and research company based in San Francisco. It is a separate company from OpenAI, which makes ChatGPT, and from Google, which makes Gemini.

Is Claude better than ChatGPT?

It depends on the task, the model versions compared, and the settings. Each has strengths that change with new releases. The reliable way to decide is to test both on your own work with the same scoring rule.

Does Claude search the internet?

It can, when web search is available and enabled for the plan or API request. Otherwise it answers from training data, the conversation, and any files you provide.

Does Anthropic train Claude on my data?

For commercial plans and the API, Anthropic states it does not train on customer content by default. Consumer plans have their own settings and terms. Review the current policy for your account.

How can a company appear in Claude answers?

There is no guaranteed placement. Useful foundations include accessible official information, consistent entity facts, original evidence, and credible independent coverage. Measure real buyer questions repeatedly and separate being named from being cited, recommended, or described correctly.

Source notes

Product capabilities and account terms change often. Documented product, training, and privacy statements in this article were checked against Anthropic materials. The discussion of business discovery and measurement is LinkinGrow editorial analysis. Accessed September 28, 2026.

• Anthropic: Meet Claude
• Anthropic Docs: Models overview
• Anthropic Research: Constitutional AI
• Anthropic: Claude's constitution
• Anthropic Docs: Web search tool
• Anthropic: Introducing the Model Context Protocol
• Anthropic: Privacy policy
• Anthropic Trust Center