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    Predict customer behavior in a few lines of code

    @fdy/faraday-js
    const configuration = new Configuration({
      headers: { authorization: "Bearer YOUR_API_KEY" },
    });
    const faraday = new FaradayClient(configuration);
    // upload orders, identify customers
    await faraday.uploads.createUpload("orders", "orders.csv", file);
    const cohort = await faraday.cohorts.createCohort({
      name: "Customers",
      stream_name: "orders",
    });
    // segmentation for personalization
    const personaSet = await faraday.personaSets.createPersonaSet({
      name: "Customers",
      cohort_id: cohort.id,
    });
    // activation pipeline
    const scope = await faraday.scopes.createScope({
      name: "Customers Scores",
      preview: true,
      population: { cohort_ids: [cohort.id] },
      payload: { persona_set_ids: [personaSet.id] },
    });

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  1. Integrations/
  2. Aurora

Predictions in Aurora

Faraday easily integrates with AWS Aurora, enabling you to embed AI-powered predictive analytics anywhere else in your stack. Discover your brand's bespoke personas, score your customers for churn risk, find repeat purchasers, and more, enabling you to confidently engage the right customers, at the right time, with personalized, relevant content. The best part? No code—and no PhD—required.

Aurora logoAurora
  • Database
For developers

Aurora variants

  • aws_aurora_mysql logo

    Aurora (MySQL)

  • aws_aurora_postgres logo

    AWS Aurora Postgres

Aurora recipes

  • Churn scores in Aurora (MySQL)

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  • Churn scores in AWS Aurora Postgres

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  • High spenders in Aurora (MySQL)

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  • High spenders in AWS Aurora Postgres

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  • Lead scores in Aurora (MySQL)

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  • Lead scores in AWS Aurora Postgres

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  • Likely buyers in Aurora (MySQL)

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  • Likely buyers in AWS Aurora Postgres

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  • Persona assignments in Aurora (MySQL)

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  • Persona assignments in AWS Aurora Postgres

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  • Repeat purchasers in Aurora (MySQL)

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  • Repeat purchasers in AWS Aurora Postgres

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