🚀 7 AI APIs Every Web Developer Should Try in 2026

You don't need to train your own AI model to add AI features to a web application.

A few API calls can give your app access to text generation, image generation, voice, speech-to-text, and more.

Here are 7 AI APIs worth experimenting with if you're a web developer.

1. OpenAI API 🤖

If you want to add AI-generated text, structured data, or AI-powered features to a web application, the OpenAI API is one of the easiest places to start.

You can use it for things like:

• AI chat
• Content generation
• Summarization
• Data extraction
• Structured JSON responses
• AI assistants

A simple request can look like this:

const response = await fetch("https://api.openai.com/v1/responses", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
  },
  body: JSON.stringify({
    model: "gpt-5",
    input: "Explain React hooks in simple terms.",
  }),
});

const data = await response.json();

console.log(data);

Best for: AI features that need text, reasoning, or structured output.

2. Google Gemini API 🧠

Google's Gemini API is another great option for building AI-powered applications.

One of the interesting parts is its multimodal capabilities, which means you can build applications that work with more than just text.

You can use Gemini for:

• Chatbots
• Text generation
• Image understanding
• Document analysis
• Multimodal applications

For example:

const response = await fetch(
  "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent",
  {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      "x-goog-api-key": process.env.GEMINI_API_KEY,
    },
    body: JSON.stringify({
      contents: [
        {
          parts: [
            {
              text: "Give me 5 ideas for a developer portfolio.",
            },
          ],
        },
      ],
    }),
  }
);

const data = await response.json();

console.log(data);

Best for: Multimodal applications and general AI features.

3. Anthropic Claude API 🦀

Claude is another popular option for developers building AI-powered applications.

Its API can be useful for:

• Long-form text generation
• Summarization
• Document analysis
• Coding assistants
• AI agents

A basic request looks like this:

const response = await fetch("https://api.anthropic.com/v1/messages", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "x-api-key": process.env.ANTHROPIC_API_KEY,
    "anthropic-version": "2023-06-01",
  },
  body: JSON.stringify({
    model: "claude-sonnet-4-5",
    max_tokens: 1024,
    messages: [
      {
        role: "user",
        content: "Explain closures in JavaScript.",
      },
    ],
  }),
});

const data = await response.json();

console.log(data);

Best for: Text-heavy applications, coding tools, and document-based workflows.

4. Replicate 🎨

Replicate is interesting because you aren't limited to one AI model.

It provides an API for running models that other developers and organizations have published, so you can experiment with different models without managing the infrastructure yourself.

You can use it for things like:

• Image generation
• Image editing
• Video generation
• Speech
• Open-source AI models

A prediction can be created through its API:

const response = await fetch(
  "https://api.replicate.com/v1/predictions",
  {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      Authorization: `Bearer ${process.env.REPLICATE_API_TOKEN}`,
    },
    body: JSON.stringify({
      version: "MODEL_VERSION_ID",
      input: {
        prompt: "A futuristic developer workspace",
      },
    }),
  }
);

const data = await response.json();

console.log(data);

Best for: Experimenting with different AI models and generative media.

5. ElevenLabs 🔊

Want to add an AI voice to your application?

ElevenLabs provides APIs for generating speech from text, with different voices and models.

You could use it to build:

• AI voice assistants
• Audiobook apps
• Voice-based interfaces
• Podcast tools
• Accessibility features

For example:

const response = await fetch(
  "https://api.elevenlabs.io/v1/text-to-speech/VOICE_ID",
  {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      "xi-api-key": process.env.ELEVENLABS_API_KEY,
    },
    body: JSON.stringify({
      text: "Hello from my web application!",
      model_id: "eleven_multilingual_v2",
    }),
  }
);

const audio = await response.arrayBuffer();

Best for: Text-to-speech and voice-powered applications.

6. Groq ⚡

Groq is worth checking out if you're interested in fast AI inference.

Its API is OpenAI-compatible, so developers familiar with OpenAI-style APIs can get started without learning an entirely different approach.

For example:

const response = await fetch(
  "https://api.groq.com/openai/v1/chat/completions",
  {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      Authorization: `Bearer ${process.env.GROQ_API_KEY}`,
    },
    body: JSON.stringify({
      model: "openai/gpt-oss-20b",
      messages: [
        {
          role: "user",
          content: "Give me a JavaScript project idea.",
        },
      ],
    }),
  }
);

const data = await response.json();

console.log(data);

Best for: Fast AI-powered applications and experimenting with different models.

7. AssemblyAI 🎙️

Not every AI feature needs a chatbot.

Sometimes you just need to turn audio into text.

That's where AssemblyAI comes in.

You can use its API for applications involving:

• Speech-to-text
• Meeting transcription
• Podcast transcription
• Audio search
• Voice-based applications

A basic transcription request can look like:

const response = await fetch(
  "https://api.assemblyai.com/v2/transcript",
  {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      Authorization: process.env.ASSEMBLYAI_API_KEY,
    },
    body: JSON.stringify({
      audio_url: "https://example.com/audio.mp3",
    }),
  }
);

const data = await response.json();

console.log(data);

Best for: Building applications that understand spoken audio.

Which one should you try?

It depends on what you're building.

The interesting part is that you don't need to become an AI engineer to start experimenting with these.

If you can make an HTTP request, you can start building AI features.

And that's probably the best way to learn:

Don't just use AI tools. Build something with them. 🚀

Which AI API would you add to the list?