[Klaviyo](https://www.klaviyo.com/) made a big splash last year, bringing entry-[level predictive scoring](https://faraday.ai/blog/why-you-need-predictive-lead-scoring-today) to their massive audience. And we love it—the industry is catching up to what we’ve been doing for years. With AI-powered tools like [predictive analytics](https://faraday.ai/templates/lead-prioritization), [personalized product recommendations](https://faraday.ai/templates/next-best-offer), and advanced [sentiment analysis](https://faraday.ai/blog/seamus-bigquery-interview) for their emails lists, Klaviyo is giving marketers powerful capabilities to forecast customer behavior, personalize messaging, and automate campaigns. But if you’re looking to take it to the next level, there’s a critical missing piece: [deep consumer insights powered](https://faraday.ai/features/faraday-identity-graph) by [third-party data](https://faraday.ai/docs/abstractions/traits).

## Klaviyo’s predictive tools, and their limitations

[Klaviyo’s AI tools](https://www.klaviyo.com/features/ai) offer a solid foundation for email marketers, helping to predict engagement and automate messaging. But recent changes—including increasing costs and [stricter policies around active contacts and list sizes](https://help.klaviyo.com/hc/en-us/articles/24263920096027)—are making efficiency more important than ever.

Though Klaviyo’s AI is powerful, their analysis is also stymied by its lack of inclusion of third-party data. This type of rich demographic and behavioral data inherently improve the depth, nuance, and critically, speed-to-deployment of predictive models. It also radically improves the accuracy and value that they can be expected to produce.

Only with this type of rich third-party data can marketers expect to achieve the highest levels of  speed and precision with their predictive marketing, and that’s where Faraday’s built-in integrations comes in.

## Optimizing Klaviyo lists with Faraday personas

Integrating Faraday’s [personas](https://faraday.ai/docs/abstractions/persona_sets) and [customer segmentation](https://faraday.ai/docs/how-to/connections/segment) capabilities into your existing Klaviyo stack takes your email lists to the next level, allowing you to gain deep insights that Klaviyo alone can’t provide.

With Faraday, you can segment your email lists not just by basic engagement metrics but by [demographics, life events, property details, and other behavioral signals](https://faraday.ai/features/faraday-identity-graph). This level of insight empowers you to tailor content, messaging, and campaigns that are perfectly suited to your audience. Whether it’s understanding the impact of a new home purchase or identifying consumers in a particular life stage, Faraday’s data-driven approach helps you reach the right people at the right time with the most relevant messaging.

By adding these third-party insights to your Klaviyo platform, you unlock smarter segmentation, faster insights, and a deeper understanding of your customers—making your email marketing more efficient, relevant, and impactful.

### The inclusion of this this data improves your Klaviyo lists by:

* **Building smarter segments** based on real-world demographics, life stages, and property data.  
* **Refining automated journeys** to align with consumers’ actual behaviors and preferences.  
* **Improve conversion rates** by sending the right message to the right people at the right time.

## The cold start problem—and how to overcome it

An additional benefit of integrating third-party data into your Klaviyo stack is the ability to avoid the [cold start problem](https://www.sciencedirect.com/topics/computer-science/cold-start-problem), a classic challenge faced by many marketing tools, including Klaviyo’s out of the box predictive scoring. While these tools are able to generate generally accurate predictions on long time customers using only first-party data, they quickly run into issues when targeting leads or recently acquired customers with very little observed behavior. 

In these cases, the model struggles to quickly generate meaningful insights, as it lacks the foundation of prior data to build from. This delay in data accumulation can significantly limit the effectiveness of campaigns until enough data has been collected.

Faraday inclusion of our third-party data eliminates this barrier by enabling you to build highly targeted customer segments right from the start. Instead of waiting months for data to accumulate, Faraday’s built-in data provides immediate insights, empowering you to craft campaigns optimized for engagement and conversion from day one. Without waiting for slow data accumulation, you can launch campaigns quickly with confidence.

## So who will actually convert? Let’s find out.

Your Klaviyo lists might still be growing, but are they optimized for conversion? Are you maximizing their value-generating potential? With Faraday, you can build a free persona model and see for yourself. Think of all the ways you could use this—better segmentation, more precise messaging, and automated journeys that actually resonate.

Klaviyo is a great start for any email marketing, but Klaviyo \+ Faraday together can take your email marketing to the next level\!

Enhance your Klaviyo lists with Faraday’s third-party data and personas to unlock deeper insights, smarter segmentation, and higher conversion rates—solving the cold start problem and optimizing your email marketing from day one.

Leveling up your Klaviyo lists with Faraday personas

I’m really happy to share some company updates with you, including new financing and additions to our leadership here at Faraday.

![Robin Spencer](/images/authors/robin.jpg)

First up is that [Robin Spencer](https://www.linkedin.com/in/robinbspencer/) has joined as COO. She arrives here from Clearbit, where she was COO for several years leading up to their acquisition by Hubspot in December. Robin had been working with us quietly behind the scenes for much of the year and has had a tremendous impact on our team and company strategy already. I couldn’t be more pleased that she’s now fully on board to steer our go-to-market teams and business operations through the next stage of scaling. I can already tell Robin is a game changer for us.

Here’s what she has to say about joining Faraday:

“It is special to return to Vermont and continue doing the work I love for a company built here. I'm grateful for the opportunity to work with a team that genuinely cares about our clients and each other. Faraday has a lot of potential, and I'm eager to help us realize it so we can support more companies.”

![Peter Levine](/images/authors/peter.jpg)

I’m also thrilled to announce that my friend [Peter Levine](https://a16z.com/author/peter-levine/) has joined our board as an independent board advisor. (While Peter is a partner at a16z, this position is in a personal capacity.) From his days as an operator to his role now at arguably the best tech venture firm in the world, Peter brings a massive amount of best practices knowledge on how great software companies grow and thrive.

I also asked Peter to share some thoughts on why he’s excited about Faraday:

“As soon as I met Andy and the team at Faraday I knew this company was something special. In a world where AI makes big promises but rarely delivers on them, Faraday has found a genuinely practical application that’s been helping thousands of brands for over a decade.”

Finally, we’ve closed some additional financing. Longtime Faraday ally Intercap, headed by board member Jason Chapnik, led the round as part of a coalition that included some of our earliest angels. Jason noted: “Faraday had been developing its technology for several years before the rest of the world caught on to AI. Now is the time for us to capitalize on our lead.”

Other founders will know that a startup is a community—and this remains the case even after almost 12 years. When longtime neighbors double down and new ones show up to help, really magical things can happen. 2025 is going to be a great year.

Robin Spencer joins as COO, Peter Levine joins the board, and we closed some additional funding.

New additions to the team, board, and financing

We're happy to announce a new partnership between Faraday and Simpli.fi, the leading Advertising Success Platform, which provides programmatic advertising solutions and workflow software to over 2,000 media teams, agencies, and brands.

Under this partnership, Simpli.fi will incorporate Faraday's [identity graph](/features/faraday-identity-graph) of more than 1,500 consumer attributes and individual-level [customer behavior predictions](/features/customer-behavior-predictions)into its sophisticated media buying program. Simpli.fi users can now create highly effective lookalike audiences, powered by Faraday, that enable marketers to target their best-fit customers with relevant engagement at scale.

"It's about combining the science and the art," Faraday CEO Andy Rossmeissl says while chatting with Simpli.fi's David McBee about lookalike audiences on [Simpli.fi TV](https://simpli.fi/simplifi-tv/andy-rossmeissl-simpli-fi-tv). Faraday's data science–combined with the artistic approach in which Simpli.fi makes these insights actionable–results in campaigns that show real ROI.

Clients interested in leveraging customer behavior predictions to create lookalike audiences of likely buyers and deploy them through Simpli.fi can contact their account manager to get started.

Faraday's identity graph and customer behavior predictions come together with Simpli.fi's media buying program to create lookalike audiences that enable marketers to target likely buyers with relevant engagement at scale.

Introducing a new partnership between Faraday and Simpli.fi

Faraday is thrilled to highlight **LeadConduit**, the ActiveProspect integration for Faraday. Between LeadConduit helping you acquire, optimize, and distribute leads, and Faraday scoring your leads with likely-to-convert predictions, your leads have never been easier to manage. Read on for details on how ActiveProspect and LeadConduit can help scale your lead management efforts:

[ActiveProspect](https://activeprospect.com/) is a comprehensive SaaS platform that empowers companies across industries to scale quality lead acquisition from any source, protect against litigation risk by documenting proof of consent, and accelerate speed-to-lead with automated process flows. With almost 20 years of experience in the industry, ActiveProspect has developed a reputation as the industry-leading consent-based marketing platform.

ActiveProspect’s three main products –[TrustedForm](https://activeprospect.com/trustedform/), [LeadConduit](https://activeprospect.com/leadconduit/), and [LeadsBridge](https://leadsbridge.com/)– are designed to help businesses capitalize on marketing opportunities and maximize conversions.

- [TrustedForm](https://activeprospect.com/trustedform/#howitworks) is the de facto standard for documenting express written consent by providing independent certificates of authenticity used for legal compliance and campaign optimization.
- [LeadConduit](https://activeprospect.com/leadconduit/#howitworks) streamlines the leading buying process to help businesses efficiently acquire customers at scale. Custom lead flows automatically enhance and filter leads in real time to deliver the highest-quality prospects to your CRM or lead buyer.
- [LeadsBridge](https://leadsbridge.com/platform/) automates your customer acquisition workflows from major ad platforms with seamless integration to your revenue tech stack. Utilize over 380 integrations to sync your leads, target custom audiences, and conversion tracking to boost sales and productivity.

Overall, [ActiveProspect](https://activeprospect.com/get-started/) offers the only complete solution for consent-based marketing powered by patented technology. Its TrustedForm, LeadConduit, and LeadsBridge products are just a few examples of the company's commitment to delivering high-quality solutions that help businesses succeed in today's increasingly competitive marketplace.

**Ready to try Faraday? [Create a free account](https://faraday.ai/signup).**

Faraday is thrilled to highlight LeadConduit, the ActiveProspect integration for Faraday. Between LeadConduit helping you acquire, optimize, and distribute leads, and Faraday scoring your leads with likely-to-convert predictions, your leads have never been easier to manage.

Faraday integration spotlight: LeadConduit

Personalization is more important now than ever. The circumstances around COVID demanded that brands ramp up digital strategies in order to stay competitive, creating a considerable amount of noise in inboxes and ad spaces (though [direct mail is making a comeback](/blog/personalized-direct-mail-strategy)). Consumer inboxes, Instagram feeds, and the like are riddled with emails and ads–some personalized, some not–and each leaves a different impression. The result is that brands need to work harder & smarter to stand out from the competition.

However, achieving true [personalization at scale](/blog/personalization-at-scale-guide) is much easier said than done. Collecting [first-party](https://hightouch.com/blog/what-is-first-party-data) and behavioral event data allows for a comprehensive understanding of how customers engage with your brand. This foundational data must be joined across various data sources and can be further [enriched](/blog/first-party-vs-third-party-data-marketing) to construct a comprehensive and unified customer profile. Subsequently, artificial intelligence (AI) can be employed to create [customer predictions](/features/predictions), identifying ideal customers and the best engagement strategies for each. Finally, a [Reverse ETL](https://hightouch.com/blog/reverse-etl) platform activates customer profiles and AI models out of your data infrastructure and into the downstream tools that power your marketing and business operations.

## Use cases for AI-powered personalization

Personalization that’s driven by AI has applications across the entire customer journey. Let’s take a look at a few standouts.

### Customer retention through proactive engagement

It’s always better to be proactive rather than reactive, and engaging with your customers is no exception to this rule. While traditional engagement can be personalized after an individual has interacted with your brand through ads, purchases, form submissions, and so on, AI-powered personalization allows you to engage with resonant content from the very first interaction, leaving your customers feeling understood, and that you see them as more than just clickstreams. On top of that, adding [propensity to churn predictions](/predict/category/churn_scores) to the mix gives you an additional layer of proactivity.

### Internal talk track alignment

The benefits of AI-powered personalization aren’t exclusive to external outreach. Savvy brands are adopting it to create frictionless experiences for their customers by ensuring every sales rep is on the same page when it comes to [talking points](/blog/sealed-lead-optimization) for each buyer persona. Additionally, it’s likely that some reps on your team will be more successful with certain personas than others, which can be used to foster persona-specific coaching among reps.

## How Faraday and Hightouch enable hyper-personalization

If you want to build this robust personalization, good news: Faraday and Hightouch have partnered to help brands hyper-personalize every customer journey with ease. Let’s dive into the highlights of the partnership that brands hungry for true personalization can reap the benefits of.

### Unify customer data in the warehouse

Hightouch enables you to build a Composable Customer Data Platform ([CDP](https://hightouch.com/blog/composable-cdp)) directly on your existing data infrastructure. In practice, this means that you are able to store, unify and activate all of your customer data directly in/from our data warehouse rather than splitting data in different silos.

Traditional CDPs collect [clickstream](https://hightouch.com/blog/clickstream-data) and [event data](https://hightouch.com/blog/event-tracking), store it in their own data silo, perform [identity resolution](https://hightouch.com/blog/what-is-identity-resolution) to build [Customer 360](https://hightouch.com/blog/what-is-customer-360) records, and then sync data to marketing tools. The Composable CDP does all of these functions, but around your data warehouse so that it can unify all customer data, including clickstream events but also offline interactions, third-party enrichment data, data from operational servers, and more. This is an essential structure for personalization because it ensures that AI models and marketers alike have access to the full view of what each customer does while providing brands with the piece of mind that data remains within their own infrastructure.

You can use ETL tools like Fivetran to collect some of this data in the warehouse, and [Hightouch Events](https://hightouch.com/platform/event-collection) to collect digital events into it as well. Hightouch’s [Customer 360 Toolkit](https://hightouch.com/platform/customer-360) then enables you to unify customer records in the warehouse by performing identity resolution.

### Use AI for customer predictions & first-party data enrichment

With your first-party customer data consolidated in the warehouse, you can use Faraday to enrich it with [built-in, permissioned, and opt-in consumer data](/features/data), then predict the likelihood that they’ll take virtually any action.

Start by using [AI for customer segmentation](/blog/predictive-personalization-machine-learning), leaving you with rich insights into who your customers are to guide the personalization of copy & creative. Next, build customer loyalty with a strong [churn prevention strategy](/blog/churn-prevention-machine-learning) by predicting churn scores, make your sales reps as time-efficient as possible by implementing [predictive lead scoring](/blog/predictive-lead-scoring-b2c) to find which leads are worth pursuing, expand your brand’s reach with confidence using an [AI-powered market sizing analysis](/blog/bottom-up-market-sizing-predictive-analytics), and more.

### Turn predictions into personalization with Reverse ETL

Now that you’ve consolidated all of your customer data in the warehouse, enriched it, and used AI for predictions, it’s time to put that data to work. Reverse ETL syncs data from your warehouse to your everyday tools. You can do this and build different audiences without writing any code using Hightouch’s [Customer Studio](https://hightouch.com/platform/customer-studio). It’s easy to build a different audience based on their attributes and predictive models and trigger various actions like personalized email campaigns directly from your warehouse source of truth into your everyday marketing tools.

## How to embed personalized, predictive high-spender scores in your stack with Faraday and Hightouch

Let’s walk through how you can use AI to predict high-spender scores to find your most valuable customers, create bespoke personas to enable hyper-personalization, then embed them in your stack by leveraging Faraday and Hightouch.

### Connect your data and define your dataset

First, you need to sync your data warehouse with Faraday by creating a connection, after which you’ll define a dataset so Faraday knows who is who in your data. Once your data is defined, you can easily group it into unique segments that we call cohorts–like your customers and high-spending customers.

[![Faraday dataset](/images/blog/faraday_hightouch/faraday-hightouch-dataset.png)](/images/blog/faraday_hightouch/faraday-hightouch-dataset.png)

### Predict high spend scores to find your most valuable customers

With your data in Faraday, you’ll build an outcome to describe the predictions you want to make–high spender scores, in this case. You’ll plug in your _customers_ cohort and your _high spenders_ cohort so that Faraday will predict how likely people in the former will enter the latter by spending big.

[![Faraday high spenders outcome](/images/blog/faraday_hightouch/faraday-hightouch-outcome.png)](/images/blog/faraday_hightouch/faraday-hightouch-outcome.png)

### Predict customer personas to guide personalization

In addition to your spend prediction, you can use AI to predict personas within your customer base so that you can engage with incredibly resonant targeting & messaging. Faraday combines your data with rich, built-in data, then uses machine learning algorithms to segment your customers into bespoke personas based on similar trait groupings. These personas provide useful insights into traits like household income, marital status, and shopping style that you can use to guide engagement. You can even take your personalization a step further by adding more traits for analysis, like health & exercise or dog ownership, to see who your customers really are.

[![Faraday customer personas](/images/blog/faraday_hightouch/faraday-hightouch-personas.png)](/images/blog/faraday_hightouch/faraday-hightouch-personas.png)

Now that your personas are segmented, use the resulting traits to create resonant copy & creative for your engagement. For example, you could include images of older women exercising in your emails to resonate with customers in the Glamorous Grandma Gloria persona.

### Create a pipeline to apply high spender scores & customer personas

With both your customer personas and your high spender outcome created, you’re ready to make them actionable by applying both personas and high spender scores to your customers.

[![Faraday pipeline creation](/images/blog/faraday_hightouch/faraday-hightouch-pipeline.png)](/images/blog/faraday_hightouch/faraday-hightouch-pipeline.png)

Now that you’ve applied your high-spender predictions and personas to your customers, create a deployment to sync them to your data warehouse.

[![Faraday pipeline deployment](/images/blog/faraday_hightouch/faraday-hightouch-deployment.png)](/images/blog/faraday_hightouch/faraday-hightouch-deployment.png)

### Create custom audiences in Hightouch Customer Studio based on Faraday predictions

Hightouch offers a visual audience builder that makes it easy to define custom segments based on your business criteria. For example, you could build an audience of customers who left an item in their cart but did not complete a purchase. You can similarly build audiences based on your predictive scores from Faraday, to turn those predictive scores ultimately into different user groups that you’ll take different action with.

[![Hightouch Customer Studio gif](/images/blog/faraday_hightouch/faraday-hightouch-customer-studio.gif)](/images/blog/faraday_hightouch/faraday-hightouch-customer-studio.gif)

From there, Hightouch uses reverse ETL to sync your customer predictions to your preferred activation platform, like HubSpot, Iterable, or Mailchimp, where you can create a personalized campaign to target your high-value customers. You can sync additional fields from your warehouse to these platforms, to fully utilize the personalization strategies that you’ve devised for these customers with Faraday. You can set up these syncs on a recurring schedule as needed, so your personalization campaigns can refresh as you run new predictions through Faraday.

**Ready to achieve true personalization at scale?** [Create a free Faraday account](https://faraday.ai/signup), and [book a demo with Hightouch](https://hightouch.com/demo?ref=/).

Faraday and Hightouch partner to help brands put AI to work, creating highly-tailored customer experiences.

Hyper-personalizing customer journeys with AI

AI matters when it makes something you already do work better. Faraday is a [Google Cloud partner](https://cloud.google.com/blog/products/ai-machine-learning/building-an-open-generative-ai-partner-ecosystem?ref=faraday-blog) that helps hundreds of US brands grow their revenue using AI. These brands did growth initiatives, lead scoring, LTV maximization, acquisition campaigns, personalization and churn reduction before Faraday—but with Faraday, they improve their margins, finding hidden signals that may cover every adult in the United States.

Built on [Google Cloud AI](https://cloud.google.com/products/ai?ref=faraday-blog), Faraday lets brands use the world's most advanced artificial intelligence (AI) and machine learning (ML) tools by choosing from tried-and-true recipes. Users sign into the self-service app at https://app.faraday.ai, pull key data from their existing data stacks, define their business objectives, and let Faraday - powered by Google Cloud’s [BigQuery ML](https://cloud.google.com/bigquery-ml/docs?ref=faraday-blog) - do feature engineering, model optimization, cross-evaluation, backtesting, bias detection, and scoring. What's more, Faraday is batteries-included, with built-in life event, demographic, financial, and property data on 240 million US adults. This consented, opt-in data is included by default in Faraday's models, without clients ever having to come into contact with privacy-sensitive data.

Seamus Abshere, Faraday CTO says that Faraday could only be built on Google Cloud:

"Google Cloud is 3-5 years ahead of the competition because its integration of AI with data warehouse is already mature. For years, our data scientists and developers have been working in the same system - BigQuery ML. Google Cloud's approach to AI breaks down traditional barriers between data analysis and software development. It makes our data scientists happy to directly develop infinite scale production systems," Abshere said.

Faraday works with customers like Boll & Branch, Advia Credit Union, Aspiration, Snap Finance, Tula Skincare, Ethos Life Insurance and ADT to grow revenue. Boll & Branch increased its DTC revenue using persona predictions, one of the options available in the Faraday app:

"Using Faraday, we saw a 30% lift in conversion with our personalized email campaigns," says Katia Unlu, Chief Digital Officer at Boll & Branch.

Advia Credit Union doubled auto loan conversions using Faraday propensity predictions, sending direct mail and email promotions to the best-fit members.

“Faraday’s platform gives organizations a framework for applying AI to improve critical programs like marketing or consumer campaigns,” said [Manvinder Singh, Managing Director, Partnerships](https://www.linkedin.com/in/manvinder/?ref=faraday-blog) at Google Cloud. “We’re delighted to support Faraday’s platform and growth on Google Cloud, and to make their platform more accessible to customers via the Google Cloud Marketplace.”

The Faraday platform was built on Google Cloud, and utilizes Google Cloud AI and ML services to deliver more capability and value to customers.

Faraday is now available in the Google Cloud Marketplace.

Faraday is a proud Google Cloud partner and uses Google Cloud AI to help US brands grow revenue with cutting-edge AI and ML tools.

Faraday gives clients access to Google Cloud AI using tried-and-true recipes

This week, Faraday is thrilled to announce a series of product updates that mark a revolutionary moment in our own history, as well as the broader AI practice. These updates don’t just make our users’ lives easier, though that’s certainly a major part of it. They also bring us one step closer to the world that all of us at Faraday are invested in building: a world where brands can use AI in a manner that’s both widely accessible and intrinsically responsible.

What does accessible, responsible AI look like? How did we get here? And why does it matter? Read on to find answers—and join us in the revolution.

## Accessible AI for all

AI becomes accessible when _anyone_ can use it to make a prediction. You don’t need a million dollar marketing budget to get your foot in the door, you don’t need a data science degree to build a model, and you don’t need to write a line of code. Today, for the first time, Faraday users can cast all those barriers aside and make predictions about their customers’ behavior in just a few clicks.

This level of accessibility has been four years in the making, and while it seems like a no-brainer today, it was a risk when we committed to the new product roadmap. Our 2018 decision to invest in a sweeping, accessible AI product update was a gamble—and maybe a somewhat audacious decision at the time.

Back then, we were growing increasingly aware that brands wanted more control over their predictions. But pivoting from what was an intensely collaborative experience to a fully self-serve platform would require thousands of engineering hours, all for a technology that was still more of a buzzword than a common business solution. The software had to take a quantum leap forward.

Four years later, [AI is everywhere](https://hbr.org/2021/09/ai-adoption-skyrocketed-over-the-last-18-months) and Faraday’s quantum leap is here. We’re thrilled to be able to offer AI to the entire brand landscape, from retail to finance and beyond, paving the way for more and more companies to connect with their customers.

## Responsible AI for all

There’s a reason they say that with great power comes great responsibility, and AI is no exception.

Machine learning algorithms train on historical data, using patterns from the past to make predictions about the future. It should come as no surprise that, left unchecked, these algorithms will surface injustices that have been baked into decades of consumer data, reflecting common biases around race, gender, class, religion, and more. It’s completely possible to mitigate these biases and produce responsible predictions that avoid or even correct for past injustices, but it takes expert know-how.

For the first six years of our company’s life, we were tightly involved in every predictive model and we could be stewards of the crucial ethics involved. With the world moving toward AI for all, we had to make sure that it was truly AI for all and deeply embed responsible AI principles into everything we were doing.

As a result, Faraday has doubled down on responsible AI. We’ve always employed proven approaches for mitigating bias and stood by our ethical consumer data practices, but now we’re rolling out automatic bias detection and mitigation for our users as well. We’re serious about building a future where AI helps—not harms—our community, and we wouldn’t release a new wave of features without ensuring that our users are equipped to use them responsibly.

## The revolution is here

When Robbie, Seamus, and I started Faraday, AI was largely reserved for the Amazons and Walmarts of the world. The cost to develop, train, and supervise predictive models was exorbitant, and only the biggest corporations could afford that kind of investment. They’ve been reaping the benefits—and the profits—that come with predicting customer behavior ever since.

This summer, we’re ringing in an AI revolution at Faraday, one where any brand, not just the Fortune 100, can use practical, powerful AI without compromising on ethics. We’ll continue building on these updates for the rest of 2022 and beyond, and we hope you’ll join us for the ride.

This summer, we’re ringing in an AI revolution at Faraday, one where any brand, not just the Fortune 100, can use practical, powerful AI without compromising on ethics.

Company