Quentin Fournier
AI is no longer an experiment. It's a business necessity.
Over the past year, businesses of all sizes have increasingly turned to AI to enhance internal workflows, boost productivity, and automate repetitive tasks. But with the rapid rise of AI models, one question keeps surfacing: Which model should your business rely on?
Today, the two most competitive AI models are Claude 3.7 by Anthropic and GPT-4o by OpenAI. Both are state-of-the-art, both are powerful—but they shine in very different ways.
In this guide, we’ll explore each company, their latest models, the tools available, how they perform under real business conditions, and help you make an informed decision based on your use case.
Founded in 2015 and backed by Microsoft, OpenAI has become synonymous with AI mainstream adoption. Its GPT model family has evolved rapidly:
OpenAI powers ChatGPT, which integrates seamlessly with Microsoft products (Outlook, Word, Excel), and offers custom GPTs, plug-ins, memory, and API access.
Founded by ex-OpenAI employees, Anthropic emphasizes AI safety, interpretability, and natural interaction. Their Claude models follow a simpler but focused evolution:
Claude is accessible via Claude.ai, Slack, and API. Unlike ChatGPT, it doesn’t offer plug-ins or custom assistants but excels in handling structured data, large documents, and nuanced reasoning.
OpenAI’s ChatGPT interface is built for speed and utility. The layout is extremely clean and task-focused, with a neutral "What can I help with?" prompt and immediate access to voice input and attachments. It’s ideal for professionals who want to get to work fast—especially those jumping between modalities (text, audio, file input). However, its tone is more robotic and utilitarian, which may feel cold or transactional in contrast to Claude’s softer approach.
Claude’s interface feels welcoming and slightly more personal. The greeting “Hi Q, how are you?” introduces a warm tone that some business users may appreciate, especially those engaging in long-form interactions or using it regularly for creative or strategic tasks. The model selector (e.g. “Claude 3.7 Sonnet”) is visible and editable upfront, giving clarity about which version you’re using. It encourages transparency, which is valuable for teams testing multiple LLMs. However, its minimalism may limit quick-access features like file upload, plugins, or memory toggles—which ChatGPT makes more accessible.
Both are simple and accessible — Claude feels more conversational and deliberate—better for focused, thoughtful tasks. ChatGPT is streamlined and versatile—ideal for fast-paced, multi-modal workflows.
Here’s how the latest models compare on key benchmarks like reasoning, math, coding, and multilingual tasks. These tests help evaluate how well each AI performs in real-world scenarios — from technical depth to everyday usability.
Claude 3.7 shines in accuracy and depth — ideal for tasks like internal reports, summaries, or analysis where clear thinking and instruction-following matter most. Its top scores in reasoning and math reflect a model built for precision and reliability.
GPT-4o, while slightly behind in a few areas, excels in speed, adaptability, and multimodal tasks like visual reasoning. It’s designed for dynamic business needs — from working with images to fast team interactions.
In short: Claude is a careful thinker. GPT-4o is a fast responder. Both excel — just in different business contexts.
We put both models through a series of common business scenarios using real business cases (summarizing PDFs, call summaries, brainstorming on next moove etc.).
In the first image (NDA Summary), Claude 3.7 shines with a clear, formatted, and informative response. It presents the document's key elements using bullet points, making it highly scannable and suited for professional use. The tone is assertive yet neutral, and the structure reflects what you’d expect in a legal or operational summary that could be reused across teams.
GPT-4.1, on the other hand, delivers a very short, overly summarized answer. While technically accurate, it lacks structure and nuance. There’s no formatting or depth—elements that are particularly important when summarizing formal documents. For business users who want clarity and actionability, Claude's output would better serve executive or legal teams.
In the second image (SaaS Client Onboarding), GPT-4.1 adopts a list-style format with clear steps, which is a solid structure for operational tasks. Each step is practical and concise, which fits how many business users plan internal processes. It’s a bit generic, but clean.
Claude 3.7 takes a different approach—it provides the same steps but wraps them into a narrative-style answer with some persuasive writing. This makes it more engaging for users who might want to use the answer for customer-facing material, documentation, or marketing-sounding onboarding.
In this HR use case, Claude 3.7 delivers a highly polished, stylized summary with formal titling ("Code of Conduct Summary") and categories like Core Values & Ethics, Workplace Conduct, and Resource Usage. The formatting feels like it was written for documentation or an HR handbook, and the output reads cleanly with a corporate voice — ready for Notion or Confluence.
But GPT-4.1, while also accurate, adopts a simpler structure — clean bullets, clear headers, but less style and narrative tone. It gets the job done for internal reference but lacks the presentation polish Claude naturally applies.
Verdict: Claude excels at turning dense compliance material into well-organized, shareable summaries that reflect HR tone and expectations. GPT is faster and simpler, but less refined.
Here the use case was about drafting a client refund mail response and Claude 3.7 writes a customer-centric, empathetic reply. It adds phrases like “We take full responsibility”, includes expected refund processing time, and lists three follow-up actions. It’s emotionally attuned and anticipates customer concerns — great for brand voice and CX.
On the other side, GPT-4.1 sticks to a formal, helpful template. It checks all the technical boxes but sounds more generic. It includes placeholders (e.g., “[Your Name]”), which is useful for internal drafting but would require more editing for external use.
tu meVerdict: Claude wins again for customer-facing messages where empathy and tone matter. GPT-4.1 offers the faster baseline structure, better suited for support reps drafting internally.
Here the use case was pretty straightforward, we asked to draft 5 linkedin campaign ideas for a new HR software. Claude 3.7 presents copy-ready ideas with formatting, e.g., CTA guidance, hashtags, and detailed structures (“Carousel,” “Founder Journey Series”). It’s practical and near-publishable — especially for marketers looking for plug-and-play content.
While GPT-4.1 offers brief and useful ideas, but with less structure and without copywriting framing. It's great for brainstorming, but you'd need to build out each idea into a full post.
Verdict: Claude delivers ready-to-use output for marketing teams. GPT-4.1’s ideas are valid but lean more “internal doc” than “client-ready asset.”
The last use case is a product use case. A very common one in the process of building new features from customer conversations. Claude 3.7 gives a robust product roadmap-style output — including labeled feature areas (e.g. "Hybrid Response Mode"), bullet explanations, and even a graph for usage metrics. The tone is product-led, with real SaaS formatting. Ideal for internal docs, slides, or stakeholder communication.
GPT-4.1 focuses on actionable recommendations with a Value + Description format. It’s more concise and digestible, great for task management or early product notes — less design-heavy, but easier to adapt.
Verdict: GPT is more robust on delivering actionnable anwsers for internal stakeholders needing visualized, structured ideas. Claude is more complete but the task was supposed to deliver a short and synthesized reply.
Claude 3.7 tends to produce richer, more polished outputs ideal for business users who want to reuse answers in formal settings or share them externally. GPT-4.1 is fast, clean, and reliable for internal use but less tailored for polished or presentation-ready answers. Both have their merits, and depending on the use case (internal note vs. client email), either could win. So if your team writes for others, Claude is your partner but if your team works behind the scenes, GPT may be your speed.
Test both on Calk AI — use your own workflows, emails, PDFs, and meeting notes — and see what works best. No need to pick one up front. You’ll get both (and more) under one roof.
Choosing between Claude 3.7 and GPT-4o isn’t about which is better overall—it’s about choosing what fits your current business needs.
Claude 3.7 is your go-to when your tasks require clarity, structure, and polish. It excels at summarizing long documents, explaining complex ideas in clean bullet points, and sounding professional. If you often deal with sensitive materials, legal docs, strategy decks, or anything that needs to be client-ready—Claude’s natural tone and organized style shine. Also Claude 3.7 and 4 are the best models to code.
GPT-4o, however, offers unmatched versatility. It handles voice input, vision tasks, dynamic prompts, and general-purpose writing with speed. Its structured approach makes it excellent for operational workflows, internal documentation, and iterating creative ideas.
Ultimately, both tools are excellent in different contexts—and the good news is: you don’t have to guess.
You can test both directly in Calk AI and compare them side-by-side (including other models like Mistral, Gemini, and more). Calk lets you feed business data to your agents and evaluate real-world performance. Try onboarding flows, document summaries, or campaign ideas—and see which AI delivers for your company.
After reading this table, you should be able to align each model with a real need inside your business.
Still unsure? You don’t have to choose blindly.
Try both in Calk AI — compare them directly on your workflows, like onboarding flows, PDF reviews, sales sequences, or support automation. Test them with your real tools and see which one fits better.
Claude 3.7 shines with its polished writing style and strong GitHub integration, making it ideal for technical documentation, policy drafts, or dev teams — if you have the tech setup to support it. It’s great at pulling structured insights from large internal databases, though it may require more custom implementation.
GPT-4o, on the other hand, is more versatile out-of-the-box. It supports voice and image inputs, generates visuals via DALL·E, and handles task reminders — perfect for teams in marketing, support, or ops. It’s easier to set up, and works well across documents, tools, and modalities without deep technical skills.
In short: Claude offers depth, but needs more configuration. GPT-4o offers range, and works fast across more business scenarios.
Both Claude 3.7 and GPT-4o are powerful — but they shine in different ways. Claude is great for structured thinking, clean writing, and use cases that involve technical or operational clarity. GPT-4o is more flexible, fast, and multi-modal — ideal for teams that need quick answers, visuals, or automation at scale.
But it depends on you :
If you're still unsure which to go for, good news: you don’t have to choose.
On Calk AI, you can access both models (and more) in one place — fully connected to your data, tools, and workflows. No switching. One price. Real value.
Try the best of both worlds — start with Calk AI.
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