AI Email Generation Tools Compared: Brew vs Loops vs Customer.io

The Rise of AI in Email Platforms

Every email platform now claims AI capabilities, but the depth and quality of these implementations vary enormously. Some platforms have bolted on a ChatGPT wrapper that generates subject lines. Others have built AI deeply into their core product, using machine learning models trained on email-specific data to optimize every aspect of campaign creation and delivery.

We spent four weeks building identical email programs on three platforms that have made AI a central part of their value proposition: Brew, Loops, and Customer.io. We evaluated their AI features across five dimensions: template generation, subject line optimization, content personalization, send-time optimization, and sequence intelligence.

Template Generation

Template generation is where AI differences become immediately apparent. Brew offers a natural language template builder where you describe the email you want, and the AI generates production-ready HTML with proper email client compatibility. The generated templates include ghost tables for Outlook, inline styles, and responsive fluid layouts. You can iterate by providing feedback in natural language.

// Brew\'s AI template generation via API
const template = await brew.ai.generateTemplate({
  description: "A product launch announcement email for developers. " +
    "Include a hero section with the product name, a features grid " +
    "with 3 key features, a code snippet showing basic usage, " +
    "and a CTA button.",
  style: {
    tone: "technical",
    colorScheme: "dark",
    layout: "single-column"
  },
  compatibility: ["gmail", "outlook-2019", "apple-mail"]
});

console.log(template.html);    // Full HTML template
console.log(template.preview); // Preview URL

Loops takes a different approach with a visual drag-and-drop builder augmented by AI suggestions. You build the template structure manually, and AI assists with copy generation, image suggestions, and layout refinements. This is less automated than Brew but gives you more direct control over the output.

Customer.io provides AI copy assistance within their existing template editor. You can highlight a text block and ask AI to rewrite it, expand it, or translate it. Their AI does not generate complete templates but is effective for content iteration. It is the most conservative implementation but also the least likely to produce unexpected results.

Subject Line Optimization

Subject lines are the most universally implemented AI feature across email platforms, but the quality of optimization varies significantly. Brew\'s subject line AI analyzes your historical open rate data, subscriber segments, and industry benchmarks to generate and rank subject line variants. It also predicts open rates for each variant, which is useful for planning.

Loops generates subject line variants using a large language model and lets you A/B test them, but does not provide predictive scoring. Their generator tends to produce creative, engagement-focused subject lines that work well for product-led growth (PLG) companies.

// Comparing subject line generation across platforms

// Brew - includes predictive scoring
const brewSubjects = await brew.ai.subjectLines({
  emailId: "launch-announcement",
  count: 5
});
// Returns: [{ text: "...", predictedOpenRate: 0.34 }, ...]

// Customer.io - basic generation
// Done through the UI, generates 3 variants
// No predictive scoring, relies on manual A/B testing

Customer.io\'s subject line AI is functional but basic. It generates a handful of variants based on your email content and lets you pick. There is no predictive scoring or automatic optimization. For teams that are already doing manual A/B testing, this adds convenience but not intelligence.

Our Testing Results

In our head-to-head test, we used each platform to generate 10 subject line variants for the same email and sent them to comparable audience segments. Brew\'s top-performing AI-generated subject line achieved a 31.2% open rate. Loops achieved 28.7%. Customer.io achieved 27.1%. The baseline (our manually written subject line) achieved 25.3%. All three AI tools outperformed manual creation, but the gap between them was meaningful at scale.

Content Personalization

Content personalization goes beyond inserting a first name. True AI personalization adapts the email\'s content, length, tone, and structure based on what the platform knows about each recipient. This is where the three platforms diverge most sharply.

Brew\'s personalization engine uses behavioral data (what features the recipient uses, their engagement patterns, their industry) to dynamically adjust email content. For a changelog email, a power user might see technical details about the API changes, while a less technical user sees the same updates framed in terms of benefits. This happens automatically through Brew\'s content blocks system.

Loops focuses on segment-based personalization rather than individual-level personalization. You define segments and create content variants for each segment. The AI helps generate these variants but does not dynamically select content per-recipient. This is simpler to implement and easier to debug, making it a solid choice for teams without dedicated data engineering resources.

Customer.io offers the most powerful conditional content system through their Liquid templating engine, but it requires manual configuration rather than AI-driven automation. You write the logic, and the platform executes it. They have recently added AI suggestions for segmentation rules, which helps bridge the gap.

Send-Time Optimization

Send-time optimization (STO) uses machine learning to determine the best time to deliver each email to each recipient based on their historical engagement patterns. Brew implements STO across all plans, analyzing open and click timestamps to build per-recipient delivery profiles. In our testing, STO improved open rates by 8-12% compared to fixed send times.

Loops offers send-time optimization on their growth plan and above. Their implementation is solid and produced similar results to Brew\'s in our testing (7-10% improvement). Customer.io offers STO as a premium feature, and their implementation is among the most configurable, allowing you to set constraints like "only send during business hours" or "never send on weekends."

Sequence Intelligence

The most advanced AI application in email is intelligent sequence optimization, where the platform automatically adjusts sequence timing, content, and branching based on recipient behavior. Brew\'s sequence builder includes what they call "adaptive sequences" that modify themselves based on aggregate performance data. If step 3 of your onboarding sequence consistently underperforms, Brew suggests content changes and can automatically adjust send timing.

// Brew\'s adaptive sequence configuration
const sequence = await brew.sequences.create({
  name: "Onboarding v2",
  adaptiveMode: true,  // Enable AI optimization
  optimizationGoal: "activation",
  trigger: { event: "user.signup" },
  steps: [
    {
      template: "welcome",
      delay: "0m",
      aiOptions: {
        optimizeSubject: true,
        optimizeSendTime: true,
        generateVariants: 3  // AI creates 3 content variants
      }
    },
    {
      template: "getting-started",
      delay: { min: "12h", max: "48h", optimize: true },
      exitCondition: { event: "user.first_api_call" }
    }
  ]
});

Loops provides sequence templates with AI-generated content but limited automatic optimization. The sequences are static once created, and optimization requires manual iteration. Customer.io has the most sophisticated workflow builder in terms of branching and conditional logic, but the AI layer is primarily advisory rather than autonomous. It suggests optimizations that a human must approve and implement.

Verdict and Recommendations

For teams that want the most AI-automated email experience, Brew is the clear leader. Its AI permeates every aspect of the platform, from template creation to sequence optimization. The tradeoff is less manual control and a reliance on Brew\'s AI models making good decisions. For teams that want AI assistance with a human-in-the-loop approach, Loops strikes a good balance between automation and control. For teams with complex conditional logic needs who want AI as an advisor rather than an executor, Customer.io remains the most flexible choice.

The honest assessment is that AI email generation in 2025 is genuinely useful but not transformative. The biggest time savings come from template generation and subject line optimization. Content personalization and sequence intelligence are promising but still require significant human oversight to produce reliably good results. Choose the platform whose AI philosophy matches your team\'s comfort level with automation.