Claude is the large language model from Anthropic. If you know ChatGPT, the analogy is straightforward: it is an artificial intelligence assistant with which you can hold conversations in natural language, ask it to write, analyse, summarise, translate, explain or reason about virtually any topic.
But Claude is not simply "another ChatGPT". It has specific features that make it more suitable than its alternatives for certain business use cases, and this guide aims to explain what those cases are, how to get the most out of it, and what limitations you need to know before you start integrating it into your workflow.
Why Claude and not ChatGPT
Before getting into the how, it’s worth answering the why. What does Claude have that GPT-4 doesn’t?
The first difference is the context window. Claude can process enormous documents in a single conversation — in its most advanced versions, up to two hundred thousand words — without the quality of the responses degrading as the conversation grows longer. This makes it particularly useful for analysing long contracts, processing text databases, reviewing extensive technical documentation, or working with multiple documents at the same time.
The second difference is reasoning. Claude tends to be more careful with claims it cannot verify. When it does not know something, it is more likely to say so explicitly than to invent a plausible-sounding answer. For business use, this matters: the cost of relying on an incorrect answer presented with confidence can be high.
The third difference is style. Claude writes more naturally, less corporately, and its texts require less editing to sound as though a person wrote them. For content generation — emails, proposals, articles — this significantly reduces revision time.
That said, GPT-4is better at other things: it has access to tools such as web search and image generation in its most recent versions, it has a more mature plugin ecosystem and its integration with other platforms is more extensive. The honest answer is that the choice depends on the use case.
How to access Claude
Claude is available on claude.ai with a free version and paid plans. The free version has limitations on the number of messages and access to the most advanced models. The Pro plan —twenty dollars a month— gives priority access to Claude Sonnet and Claude Opus, the most capable models.
For business use with integration into other tools or applications, Claude is available through the Anthropic API, which is pay-per-use based on the number of tokens processed.
The five use cases where Claude excels in a business
Analysis of long documents. Upload a fifty-page contract, an audit report, a supplier’s general terms and conditions, or the minutes of a board of directors meeting, and ask Claude to identify the most important clauses, risk points, key dates, or obligations to monitor. The ability to process complete documents without losing the thread is where Claude outperforms most of its competitors.
Drafting business communications. Commercial follow-up emails, service proposals, responses to complaints, client presentations, results reports. Claude produces texts that sound human and respect the tone you specify. The key is to give it context: don’t simply ask it to write a follow-up email — tell it who the client is, what stage the conversation is at, what you want to achieve with the email, and what tone it should use.
Analysis and synthesis of information. Give it ten press articles about a sector and ask it to synthesise the main trends. Pass it the responses from a customer satisfaction survey and ask it to group the comments by category and identify the most frequent patterns. Give it the sales results from the last quarter and ask it to explain what is happening and what factors might be behind it.
Code generation and automations. Claude writes code in practically any programming language and explains what it does in terms that non-programmers can understand. It can generate Python scripts to automate repetitive tasks, write complex formulas for Excel or Google Sheets, build SQL queries to extract data from databases, and create automations for tools such as n8n or Make.
Meeting preparation and decision-making. Give it the context of a negotiation, a hiring decision, an investment decision or an operational problem, and ask it to identify the questions you should be asking yourself, the factors you might be overlooking, or the possible scenarios and their implications. Claude does not make decisions for you, but it is a surprisingly useful interlocutor for thinking more clearly.
How to write better prompts
The quality of Claude’s responses depends directly on the quality of the instructions you give it. There are a couple of principles that make the difference.
Be specific about the context and the objective. "Write an email to my client" produces a mediocre result. "Write a follow-up email to a client of a logistics company to whom we presented a web redesign proposal ten days ago and who has not yet replied. The tone should be professional but approachable; we want to remind them of the proposal without pressuring them and offer them a call to answer any questions. The email subject line should be creative, not generic" produces a result you can use straight away.
Specify the format you want. "Summarise this document for me" produces a paragraph. "Summarise this document for me as a list of five points, each no longer than two sentences, aimed at someone who needs to make a decision in the next five minutes" produces something actionable.
Use the role. You can tell Claude to act as an expert in a given area. "Act as a finance director with twenty years of experience analysing this business plan" produces a different analysis —and usually a more useful one— than asking it to "analyse the business plan".
Iterate. Claude remembers everything said in the conversation. If the first response is not exactly what you need, don’t start from scratch: tell it what works and what needs to change. "The tone is right but the text is too long, cut it in half and remove the examples" is more efficient than starting a new conversation.
The limitations you need to know about
Claude has a knowledge cut-off date: it does not know what has happened in the world after a certain date, unless you provide that information directly in the conversation. For tasks that require up-to-date information — current prices, recent news, real-time market data — it needs to be supplemented with web searches or data you provide yourself.
Claude makes mistakes. Especially in complex numerical calculations, in highly specific niche information, or in data that depends on particular sources. Any important factual information must be verified before use.
Claude has no memory between conversations. Each new conversation starts from scratch. If you want it to have context about your company, your clients or your processes, you must provide it at the start of each conversation.
Integrating Claude into your team’s workflow
The greatest leap in value does not come from one person using Claude sporadically. It comes from the whole team using it systematically for the tasks where it adds most.
This requires two things: identifying the specific use cases where Claude improves efficiency in your particular business, and creating standardised prompts for those use cases so that anyone on the team can achieve quality results without having to learn how to write prompts from scratch.
At BAI we help businesses do exactly that: map the processes where AI can generate the most value, build the prompts and workflows that make it systematic, and train your team to use it properly. The result is not magic: it is a measurable reduction in the time spent on repetitive tasks and an improvement in the quality of written outputs.