Artificial Intelligence That Creates More Career-Defining Moments For Users

There are pivotal moments that have the potential to change so much. We take on new jobs, new projects, get promoted, start hiring for a key role. When the right people coordinate during these small windows of time, great things can happen, but we may not hear about them until the opportunity to connect, do business, or celebrate together has passed.

A startup called Ren is fixing this by teeing up information about key moments happening to the people you know so that you can act. 

The transcript has been edited for clarity.

Lionel Foster: Canay, welcome to Catalyst. Thanks for joining.

Canay Deniz: Thanks for having me.

Lionel Foster: All right, I’m going to hand things over to JP.

JP Bowgen: Canay, it’s always a pleasure. Excited to be here with you and illuminate all things Ren.

I think our listeners at this point know a bit about Camber Creek, but the purpose of this conversation is really to illuminate more about you and the company you’ve founded.

Without going too deep too quickly, I’d love to hear more about your background. A lot of the reason we invested in your company is because of the person at the helm, you, and the story that led to this company.

So walk us through it. What’s Canay before Ren?

Canay Deniz: Yeah, I appreciate it.

It’s definitely an immigration story. A westward journey, really, before I arrived in the States.

If we go all the way back, I was born in a refugee camp. My parents had fled difficult circumstances. I spent roughly the first year of my life there.

Then we moved further west. We received asylum and immigrated to Switzerland, which is really where my luck in life begins.

If you know anything about Switzerland, it’s probably one of the most comfortable places on the planet to arrive after a journey like that.

I grew up there. We started at the bottom of the food chain, but that’s where we began. From that point forward it became a fairly classic immigrant story.

My mother found work. My father did as well, though at one point he was hit by a truck while riding his bicycle. It badly injured his leg and kept him out of the workforce for a while, which added some challenges as we were trying to establish ourselves in a new country, without language skills and without a support network.

But ultimately we got integrated into the school system. I grew up there, studied there, made friends there, and before long I felt Swiss.

From an early age I was always very curious and very hungry to learn and understand how things worked.

After high school, what we call “Gymnasium”, I attended ETH Zurich, which is one of the stronger technical universities in Europe. For Americans unfamiliar with it, I usually lead with the fact that our most famous alumnus is Albert Einstein.

ETH has an exceptionally strong tradition in engineering and science. That’s where a lot of my technical education took shape. I met a lot of great friends there, worked on interesting projects around machine learning, and that eventually led to my first job.

My first role was with a startup that had spun out of ETH alongside a computer science professor and two of my friends. I joined when the company was around 10 people.

The work was fairly technical. We were trying to predict failures in power plants, gas turbines, generators, and similar equipment. We built predictive analytics algorithms to determine when those machines would fail.

We did that for a number of years and eventually gained traction in telecom, analyzing cell tower signals and related infrastructure. The company raised capital, grew very quickly, and started seeing a lot of traction in the United States.

At some point the team got together and decided I should be the person to move west again—to New York—to establish US operations, hire a team, and close some of the first partnerships.

So I did that for a while.

After roughly five years, which is actually a fairly long stint for a non-founder at an early-stage startup, I felt it was time to branch out and learn something new.

I didn’t know exactly what came next, but that same curiosity and hunger that had driven me before told me it was time.

And then, through one of those serendipitous chains of events, I met a new group of people. That ultimately led to the founding of Ren.

JP Bowgen: Your story itself is pretty incredible, and there are quite a few subtle flexes embedded in there.

Albert Einstein as an alumnus of ETH certainly isn’t the smallest one.

For listeners who may not know, ETH Zurich is one of the top research institutions in Europe, if not the top.

I want to ask a broader question before we get into Ren.

You talked a lot about hunger. Having come to Switzerland, built a life there, and then eventually moved to the United States, how much of your success do you attribute to luck versus skill versus hunger?

How do you think about that mix?

Canay Deniz: I’ve had this conversation with a lot of people who have unconventional paths.

Luck is always a major component.

What’s interesting is that many highly successful people—Fortune 500 CEOs, government leaders, military leaders—will often tell some version of the same story. They consider themselves lucky.

But somehow they also seem to keep finding themselves in situations where luck can happen.

There’s a concept we talk about called engineered serendipity. One of my favorite sayings is that luck favors the prepared. You do everything in your power to prepare, but preparation alone isn’t enough.

I don’t think anyone who’s truly successful attributes everything solely to hard work. Most people acknowledge that they’ve received help.

Very often people break luck into three ingredients: the right timing, the right people, and the right context. When those three things come together, something magical can happen.

And when it does happen, it can completely alter the trajectory of your life.

That has happened to me multiple times.

In my experience it usually comes down to meeting the right people at the right time, discovering that you’re aligned around a mission, building trust and rapport very quickly, and then deciding to do something together.

Lionel Foster: Canay, you shared a lot there. But one thing jumped out at me immediately: the word “Gymnasium.”

That tells me you had a German-language education. Is that right?

Canay Deniz: Yeah, exactly. Switzerland is divided into four language regions, and I grew up in the German-speaking part. That’s my primary language.

My mother tongue is Turkish, and I picked up English along the way.

Now my kids speak Spanish, German, and English.

Lionel Foster: Oh my goodness.

Let me pull back the curtain a bit.

There’s actually a random German-language connection here.

I spent my senior year of high school as an exchange student in Germany, at a Gymnasium in a suburb of Hamburg called Pinneberg.

Canay Deniz: Really? Nice.

Lionel Foster: And JP occasionally sends me Slack messages in German because he’s studying the language.

Canay Deniz: We should start a German group chat just for fun.

JP Bowgen: If the spectrum is zero to fluent German, I’m definitely the third-smartest person on this podcast.

Lionel Foster: I just wanted to put in a plug for being well traveled and somehow developing an affinity for the German language.

Canay Deniz: Yeah, man.

JP Bowgen: To build on that, you’ve had two major geographic leaps in your life.

First, your family arrives in Switzerland and builds a life there. Then you establish success, attend one of Europe’s top universities, and eventually move to North America for work.

Can you compare those experiences?

How do you think about arriving in Switzerland versus later moving to the United States?

Canay Deniz: I’ve actually been thinking about this a lot recently because I became an American citizen not long ago.

So now I’m Swiss and American, despite having been born in neither country.

I have enormous appreciation and gratitude for both places.

Both countries have given me a lot.

Switzerland gave my family support when we needed it most. There are many things Switzerland does exceptionally well.

But when I compare Switzerland to the United States, some of the clichés exist for a reason.

If you’re a hungry person—and I was very hungry, and still am—the mentality around change is different.

In Europe, many systems have evolved over hundreds or thousands of years specifically to preserve stability and avoid disruption.

Company-building, by definition, introduces something new into an existing system. So very often the questions you’ll receive focus on risk. What could go wrong? How might this fail? How do we minimize downside?

In the United States, people understand all of that too.

Everyone knows startups are risky.

But there’s an additional question: What if this works? What if it works beyond anyone’s expectations? That mindset struck me immediately when I arrived in New York.

Lionel Foster: Who asks those risk-focused questions in Europe? Investors? Customers? Everyone?

Canay Deniz: Pretty much everyone.

Investors, customers, employees, every stakeholder.

Of course everyone cares about upside, but the starting point is often risk-minimization.

Here in the United States, people certainly understand risk, but they’re also much more willing to imagine outsized success.

Again, I’m generalizing. Both places are nuanced and evolving.

But if you ask what immediately stood out to me when I arrived in New York, it was hearing people say: “Yes, I understand all the ways this could fail. But if it succeeds, how big could it become?” That perspective was everywhere.

And honestly, I think I may have grown up in Switzerland physically, but mentally I’ve always been at least a little bit American in that regard.

JP Bowgen: You pointed to the concept of what can go wrong. From this side of the table, I can confidently tell you that a lot of things are going very right at Ren.

So let’s fast-forward to what you’re doing today. Walk us through it. What is Ren? What are people able to do with it? Give the audience a picture of what this company is building toward.

Canay Deniz: Yeah, totally. We just spoke about luck a little bit, right? Putting the right people at the right time into the right context so that magic can happen.

In a nutshell, that’s what Ren is trying to systematize.

Ren Systems is the name of the company. For anyone curious, it’s Rensystems.com. The idea is that we’re trying to systematize serendipity so that magic can happen more often in your life.

The first application we’ve found for that is sales and business development. Broadly speaking, the people who get the most immediate value from Ren are what we call dealmakers.

Lionel Foster: Hold on one second. I have to stop and appreciate that phrase. Trying to systematize serendipity. It’s got alliteration. It’s easy to understand. If you were a stand-up comic, you’d pause after that line and let it land because that’s quality.

Please continue.

Canay Deniz: I appreciate it.

Funny enough, I have the same habit a lot of founders have. I buy a lot of domain names. I actually own systematizingserendipity.com, and it redirects to Ren.

So thank you for pausing on that.

What I mean by it is simple: I want to help people stop missing important moments in the lives of the people they care about.

That’s really the origin story of Ren.

This wasn’t one of those stories where I sat alone in a garage and came up with an idea.

The serendipitous moment I mentioned earlier involved meeting a very interesting group of people. At the forefront was Mike Hayes, who, as JP knows, is also on the board and was one of the original founders of Ren.

Mike and I spent hours sitting in coffee shops talking about luck: his background, my background, and how unusual our paths had been.

For people who don’t know him, Mike is a former Navy SEAL, a SEAL Team commander, later a business leader, and now an investor. Just an incredibly impressive person.

We connected over the unusual nature of our journeys.

One of Mike’s observations was that every time something amazing—or something really difficult—happened to someone he cared about, he tended to hear about it weeks or months later.

And his reaction was always the same:

“If I had known in the moment, I could have reached out. I could have helped. I could have been there.”

The original idea behind Ren came from that place.

It was fundamentally an altruistic idea.

Half of the name Ren comes from the Confucian virtue of benevolence.

The mission started with a simple belief: help people show up for each other at the right time.

Then, of course, you ask the practical question: Is this a company? Is this technology? Is this a product? Can this actually make money?

So Mike and I spent months interviewing people before we even started building software.

That’s when we discovered that the most immediate application was in financial services, professional services, commercial real estate, and other relationship-driven industries.

The people succeeding in those businesses—the rainmakers, the dealmakers—win because they consistently connect with the right people at the right time in the right context.

The same ingredients of serendipity.

We realized that this group was incredibly underserved and that they all experienced the exact same problem Mike had described.

They constantly found themselves learning about opportunities after the fact. A deal had already gone to a competitor. A company had already made a strategic move. A key executive had already changed jobs. And they missed it because no human being can keep track of everything happening across all the people and companies they care about.

Even if reading the news was your full-time job, you’d still miss most of it.

That was the opening we saw.

The rise of AI happened at almost the perfect time. We had already been working on AI before it became fashionable, and then the broader market acceleration amplified what we were building.

So today, in a nutshell, Ren helps you stop missing the moments that matter across the people and companies you care about, so you can act on information at exactly the right time and hopefully create business opportunities.

JP Bowgen: A lot of those themes feel like a combination of your personal experiences and your professional experiences.

I’m curious whether you have examples from your own life where acting at exactly the right moment materially changed an outcome.

We’ve heard customer stories where someone sees something in Ren, acts on it, and creates an opportunity that otherwise never would have existed.

But what about you personally?

Canay Deniz: Honestly, becoming CEO of this company is a Ren story before Ren even existed.

I was preparing to leave my previous company and reached out to a friend of mine who runs a cybersecurity company.

I had seen some news about them—maybe they had just raised a large round—and I sent him a note saying, “I’m about to leave my company, I’m about to get married, and when I get back I’d love to run a few ideas by you.”

He responded with one sentence: “Before you leave, you should meet my friend Mike.”

That was Mike Hayes.

We met, started talking, and eventually that became Ren.

You can call it random. You can call it serendipitous.

But it happened because I saw a signal, reached out to someone, got introduced to another person, and that chain of events completely changed my life.

Mike and I joke about this sometimes.

He’s already written two books and says that someday he’ll write another book entirely about all the incredible things that happened because of Ren.

We’re collecting stories every day.

Some of them are business outcomes. Some of them are personal outcomes.

Recently one of our enterprise customers reached out completely unprompted.

One of their top producers sent us a message saying, “I just wanted to thank you. I landed a career-defining deal because of something I saw on Ren. I would have completely missed it otherwise.”

My first reaction was gratitude.

My second reaction, as a founder, was: “Can we turn this into marketing?”

So I asked him, “Can you give me a rough sense of the deal size? Five figures? Six figures?”

And I added the little eyes emoji.

He responded that it was a $40 million construction deal.

My jaw hit the floor.

I thought, “Okay. That’s pretty cool.”

Lionel Foster: Let me pause there for a second because if someone doesn’t understand how Ren works, this might sound like actual magic.

And in some ways it is.

But let me explain.

Ren can connect to LinkedIn, email accounts, CRMs, calendars, and other sources of relationship data. It stitches together your professional graph and then layers intelligence on top.

It’s pulling information from hundreds of thousands of news and data sources, building a personalized feed around the people and companies that matter to you, and surfacing the most relevant developments.

And it goes beyond that.

If I have a meeting at 3:00 p.m., Ren can tell me what I need to know about the people I’m about to meet with.

It does the homework for me.

That’s where the magic starts.

Canay Deniz: Exactly. Thanks for that explanation.

The onboarding process takes roughly one or two minutes.

Anyone can sign up.

The first thing Ren needs to understand is who you care about.

That’s where integrations come in.

You connect the places where you already store information about people and companies.

For me personally, I’m a heavy Ren user.

I use it every day because my work revolves around people.

Hiring is people.

Selling is people.

Fundraising is people.

So Ren connects to CRM systems, Outlook, calendars, email accounts, business phones—wherever those relationships live.

From there, it builds an understanding of the people and companies that matter most to you.

Then we go do the reading.

Every day, millions of things happen. Most people rely on LinkedIn, a few newsletters, maybe some Google Alerts. What we hear repeatedly from users is: “I had no idea how much I was missing.”

Our goal is to close that gap. The information gets delivered through a simple feed.

You can use it on your iPhone, through the web application, or directly inside Salesforce, if your organization uses Salesforce.

Our primary customers are companies, but any individual can sign up and start using Ren.

In fact, that’s often how we end up with enterprise customers. Dozens or even hundreds of people inside a company start using the product before the company eventually decides it wants a broader deployment.

We have some of the broadest coverage available across the English-speaking information ecosystem.

Mainstream media, local news, industry publications, government filings—you name it.

We read everything we can get our hands on.

The challenge isn’t information scarcity. It’s information overload.

So our job is to act as an enormous noise filter, tuned specifically to find the signals that matter to you as an individual.

That’s really what Ren does.

Lionel Foster: That’s a great explanation. Camber Creek became an investor a few years ago and then a Ren customer not very long afterward.

I want to tell a quick story. One of our team members, shortly after getting onboarded, received an alert about a contact of his in real estate who had just closed a deal. The only place the news appeared was a small local publication.

Our colleague reached out to congratulate him, and the response came back almost immediately: “First, thank you. Second, how in the world did you hear about that?”

Because this wasn’t widely reported. It was tucked away in a local source.

Then he followed up with something like:

“Whatever you’re using, I need it.”

That’s the kind of reaction Ren creates. It sounds like magic because, in many ways, it feels like magic.

Canay Deniz: Yeah, that’s awesome. And honestly, it’s something we hear all the time.

JP Bowgen: I think everyone on our team has a story like that.

I had one myself a couple weeks ago.

I logged into Ren and saw a local publication report that the CEO of a major apartment owner in the United States—an organization with tens of thousands of units—had stepped down.

I don’t have a close relationship with the CEO, but I do know someone else within the organization.

So I reached out and mentioned that I had heard the CEO was stepping down.

She responded within thirty seconds: “Oh my God. What? I haven’t even heard that.”

Lionel Foster: Exactly.

JP Bowgen: Experiences like that happen over and over again.

Which gets to a broader question.

We’re all LinkedIn users. We all have contact lists.

Where do those tools fall short? What are they not getting right that Ren is trying to solve?

Canay Deniz: LinkedIn is a victim of its own success.

Everybody is on it.

I don’t know the current user count, but it’s enormous. And like a lot of people, I fell into the trap of gamifying it at one point—trying to collect followers, connections, and so forth.

The result is that many people end up with networks where 80 or 90 percent of the people are individuals they barely remember or don’t actually know.

That creates a lot of noise.

You’re seeing posts, ads, updates, and content from people who are no longer relevant—or perhaps never were relevant—to your day-to-day life.

Then you layer on all the engagement mechanics. Someone played a game. Someone commented on something. Someone reshared something.

For most professionals, LinkedIn has effectively become a résumé repository.

You’re hiring someone? Check LinkedIn.

You’re about to meet someone? Check LinkedIn.

That’s mostly how people use it.

There are certainly power users who meticulously curate their networks and invest a tremendous amount of time into the platform. But even then, by the time something appears on LinkedIn, it’s often already too late.

If you’re a dealmaker, you don’t want to learn that someone already got the job.

You want to know that leadership is changing, that there are rumors of a transition, or that conditions are developing that may create an opportunity.

If you’re in executive search, you want to know before the hiring process begins.

If you’re in real estate, learning that a transaction already closed isn’t nearly as valuable as seeing the signals that indicate a transaction is likely to happen.

Those are the predictive indicators.

Those are the things that matter.

And even if your goal is simply relationship-building—congratulating people when good things happen—you’ll still miss most of those moments because you’re not spending twenty-four hours a day on LinkedIn.

Most people consume content there. Very few actively publish.

And when people do publish, it’s usually marketing, branding, or broadcasting—not necessarily the information most relevant to building deeper relationships.

That’s the gap we saw.

There are other signal-monitoring products in the market, but most of them are built for different user types and different use cases.

We saw an opportunity to flip the LinkedIn feed on its head.

Instead of ninety percent noise and ten percent signal, we want ninety percent signal and ideally eliminate the noise altogether.

JP Bowgen: One could argue that LinkedIn’s purpose is to help activate relationships. I see something happen. I reach out. Someone gets promoted. I congratulate them. Someone lands a customer. I connect with them.

But what I’m hearing from you is that most people don’t actually build that muscle. How does Ren help people move from consuming information to acting on information?

Canay Deniz: First, you make it incredibly easy. Everything about Ren is designed to feel effortless. The backend is unbelievably complicated. We’ve got people with quantum physics PhDs building models designed to reduce noise and maximize signal. It’s technically difficult work.

But the user experience should feel simple.

One of my favorite observations is that we’ve turned fifty-, sixty-, and seventy-year-old wealth managers, investment bankers, and real estate professionals into AI power users—often without them even realizing they’re using AI.

Because the experience is so straightforward.

Ren sends an email: “Here’s what you need to know.”

That’s it. Simplicity drives adoption.

Then, when it comes to taking action, we make that easy too.

On LinkedIn, if you care about something, the easiest thing to do is click the Like button and move on with your day. In Ren, the most prominent button is Reach Out.

You tap it, and Ren drafts a message for you. It uses the context from the news event, incorporates what it knows about the relationship, and creates a human-sounding first draft.

Most users still edit the message, and that’s exactly what we want. But editing is much easier than starting from a blank page.

Everyone knows how hard it is to write the first sentence.

If you already have a draft in front of you, even if you rewrite most of it, you’re much more likely to send it.

And over time, Ren learns.

It learns your tone, your style, when you’re formal, when you’re casual, and how you typically communicate.

So the drafts become better and better.

Users can then send messages through email, text, LinkedIn, WhatsApp, and other integrations we’ve built. The result is that reaching out becomes almost frictionless. And the people we serve, dealmakers, love that. Because they know a LinkedIn Like is unlikely to generate a business opportunity. A thoughtful personal message might. And a thoughtful personal message can lead to a meeting. And a meeting can lead to a relationship. And in the hands of a true rainmaker, that’s where the magic happens.

Lionel Foster: Canay, I’m curious how your team thinks about the broader implications of all the information flowing through the platform.

You’re gathering incredibly high-quality signals about who people care about, what topics matter to them, what locations are relevant, and how relationships evolve.

At least theoretically, you could imagine all kinds of insights emerging from that. Patterns in wealth management. Patterns in commercial real estate. Patterns in how deals come together.

You could imagine predictions, recommendations, all sorts of possibilities. At the same time, users love Ren because it serves them directly. So there’s an obvious sensitivity around what happens with data behind the scenes.

How do you think about that?

Canay Deniz: One of the reasons we’ve been successful is that we’re extremely serious about privacy, cybersecurity, compliance, and security generally.

When you sell to Fortune 500 companies, you quickly discover that much of the job has nothing to do with writing code.

It’s about security reviews, compliance reviews, governance processes, and understanding how large organizations operate.

People trust us because we’re not doing advertising games or selling data.

That’s not the business.

Now, you’re absolutely right that we occupy a unique position.

One of the big questions in AI today is: what’s the moat?

Why won’t someone replicate what you’re doing?

In our case, thousands of senior dealmakers, including some of the most influential people in the country, have effectively trained our systems.

They’ve taught us what they care about, who they care about, when they care, and why.

That collective understanding is incredibly valuable.

We understand user intent.

We understand relationship context.

And we’re very good at answering the question:

Why now?

Why does this matter right now?

So far, we’ve used that knowledge primarily to serve individual users.

But increasingly, our customers are asking us to help solve a different problem.

Many large organizations miss opportunities inside their own client base.

I recently spoke with the global CRO of a major company who told me he discovered through the news that an existing client had signed a large agreement with one of their competitors.

And he kept repeating: “We weren’t even in the room.”

They had a relationship with the client.

But another business unit inside the company should have been involved and wasn’t.

That’s the challenge of scale.

Large organizations don’t always know what everyone else inside the organization knows.

So one of the major roadmap initiatives we’re building right now addresses exactly that.

Internally we call it Smart Intros.

The idea is simple: What’s the optimal path to reach any person or company you want to connect with?

Who is the best possible introducer?

Today people search a CRM. Then they search LinkedIn. Often they hit dead ends. Maybe the last interaction happened three years ago.

Maybe the relevant employee left the company.

Maybe the mutual connection barely knows the target.

We can do better than that.

Because we understand relationship strength and relationship depth at a level most systems don’t.

We are uniquely positioned to answer: Who inside my organization is best positioned to introduce me to this person?

That’s something customers are actively asking for, and it’s something we’re actively building.

Historically, we’ve helped people leverage their own networks.

Increasingly, we’re helping organizations leverage the collective network of everyone inside the company.

There are privacy concerns and guardrails that need to be handled carefully.

You can’t simply expose everyone’s relationships to everyone else.

But there are ways to build that responsibly.

And honestly, I’m incredibly excited about it.

JP Bowgen: We talk about AI tools all the time at Camber Creek.

Personally, I spend a lot of time in Perplexity. I may even move some of my workflows to Claude.

One thing I’ve noticed is that these tools quickly learn preferences.

Perplexity seems to know that I admire how Bill Gurley writes and communicates.

But that raises a question.

If we’re all using AI and we’re all borrowing from the same influences, doesn’t everyone eventually start sounding the same?

How do you prevent that?

Canay Deniz: Everybody starts sounding like Bill Gurley.

JP Bowgen: If that’s my legacy, I won’t complain. But seriously: how do you preserve individuality?

Canay Deniz: Our head of AI recently wrote about this distinction between general-purpose AI and purpose-built AI.

We’re hyper-focused on the individual human.

Every Ren experience is unique.

No two users see the same information at the same time.

No two users receive the same suggested messages.

Everything is adapted to who they are, who they know, what they care about, how they communicate, and what they’re trying to accomplish.

In many ways, your version of Ren is a completely different product from mine.

And that was intentional.

My hope for AI is actually that I spend less time with technology and more time with people.

I want technology to amplify what makes me uniquely me.

I want it to help me be more helpful.

I want it to help more people become luckier.

I want it to systematize serendipity at scale.

The same idea applies to companies.

Every company is unique. Every customer is unique.

We want to understand how they serve clients and how we can help them become more present, more informed, and more responsive.

General-purpose tools like Claude and ChatGPT absolutely have a place. I use them every day.

Many of them are incorporated into our own workflows.

But our DNA is different.

Our DNA is customization.

Because once you’ve worked with enough dealmakers, you realize that no two operate the same way.

The human is the differentiator.

The human is the product.

The human is the X factor.

And that’s what we’re trying to amplify.

That’s why we’re pushing hard in the opposite direction of a world where everything turns into AI-generated sameness.

Lionel Foster: Canay, you mentioned data privacy earlier, and I want to bring that together with something else we discussed: general-purpose AI systems.

I don’t think people are thinking about this enough.

Here’s a real-world example. There’s a CRM platform that’s important in our industry. They recently announced integrations with some of the large language models, including Claude.

The promise is compelling: use Claude as the interface for your CRM. From a functionality standpoint, that sounds amazing.

But when I think about the chain of interaction, I see a few places where things could get complicated.

There’s the user. There’s the CRM provider. The user probably understands the CRM’s privacy policies and is comfortable with them.

Then there’s the connection between the CRM and Anthropic.

That’s where things become less obvious.

What exactly happens when Claude accesses your CRM data?

I was curious enough to look into it.

Depending on the version of Claude and the setup you’re using, one of the strongest privacy controls available may simply be deleting the conversation afterward.

Even then, the information may remain in backup systems for up to thirty days.

For someone who is deeply committed to data privacy, that feels problematic.

So I’m curious: Ren interacts with some of these general-purpose AI systems.

How are you navigating that?

How are you helping customers understand what data is accessible to third parties and what data isn’t?

Because customers trust Ren, but they may have a different level of trust in those third parties.

Canay Deniz: If you’re concerned, imagine how a Fortune 500 bank feels. Not only are they concerned: they’re regulated.

To be very clear, one of the reasons we’re able to partner with organizations like that is because their data is effectively fortified.

There isn’t some third party accessing sensitive customer information.

We are the only party accessing it.

When we use general-purpose LLMs, we’re extremely careful about where and how they’re used.

The pieces that interact with those systems are intentionally separated from sensitive customer data.

Building that separation properly is one of the most important capabilities a company can develop if it wants to sell into highly regulated enterprises.

There are really multiple dimensions to this discussion.

On one hand, it’s easy to imagine a future where there is a single conversational interface for everything you do in business.

And maybe that interface is a chatbot.

Personally, I’m not entirely convinced.

I use Claude constantly. But there are many situations where writing a detailed prompt is actually more cumbersome than a purpose-built user experience. Sometimes a chatbot is the best interface. Sometimes it isn’t.

Our philosophy is to remain obsessed with the problem rather than the interface.

The question isn’t whether something can be done in Claude. The question is whether the problem disappears. That’s the bar.

Does the user stop thinking about the problem?

Does the workflow become effortless?

When I see all of these integrations emerging—CRM connected to Claude, this connected to Claude, that connected to Claude—I sometimes find the positioning a little strange.

If your value proposition is essentially, “You don’t need our product anymore; just use Claude,” that feels like an odd place to land.

I’d rather ask: what is the optimal solution?

What makes the problem vanish entirely?

What allows someone to stop thinking about it forever?

That’s the standard we’re trying to hold ourselves to.

We integrate with the tools people already use.

Email is a great example.

One of our early hypotheses was that people already have strong muscle memory around email. Email remains one of the most fundamental tools in business. So we built Ren in a way that allows people to do much of what they need directly within Outlook or Gmail.

They don’t necessarily need to open Ren. They don’t need to open a CRM. They certainly don’t need to open Claude.

They can stay inside the workflows they’re already comfortable with.

That turned out to be a very successful hypothesis.

Adoption has been strong because people don’t have to change how they work.

We’re absolutely exploring MCP and similar approaches, and some customers are asking for them. But it’s worth remembering that last year everyone was talking about copilots.

This year everyone is talking about Claude. Next year it may be something else. Everything is moving very quickly. So our goal is to remain agile and stay focused on solving the underlying problem rather than becoming attached to a particular interface.

If people want to work in Claude, great. If they want to work in Copilot, great. If they want to work in Salesforce, great. If they spend their entire day in email, that’s great too. Ren should meet them wherever they already are. That’s our philosophy.

JP Bowgen: As a slight non sequitur, we’ve now said “systematizing serendipity” several times.

I actually tried typing it directly into my browser just before this conversation.

I can confirm that despite being an incredibly difficult phrase to type correctly, it does redirect to Ren’s website.

But putting that aside, let’s spend the remainder of our time talking about what’s ahead.

You’ve shared a lot with me privately about the roadmap, the team, and the technology.

What can you share publicly about what’s coming next for Ren?

Canay Deniz: The thing I’m most excited about is what we discussed earlier: Smart Intros.

Internally, we often call it the relationship map.

It’s the collective understanding of relationships across individuals and organizations.

There’s tremendous potential there.

We’re actively working on secure and thoughtful ways to help organizations leverage the collective strength of their networks.

That’s probably the roadmap item I’m most excited about.

Beyond that, another major focus is reducing friction even further.

One of the goals I’ve set for Ren is helping people become more passive consumers of value.

Being proactive is hard.

People are busy.

There’s noise everywhere.

Every additional thing someone has to think about is a burden.

I empathize with that more than ever now.

I have a two-year-old. The company is growing quickly. Life gets busy. And the busier you become, the more you appreciate solutions that simply work without demanding attention.

You could present someone with a platter of gold, but if engaging with it requires effort, it becomes just one more thing on their list.

So we’re constantly asking ourselves: how do we reduce friction to zero?

How do we let someone lean back and still receive value?

That philosophy influences product design, onboarding, delivery, everything.

Today onboarding takes roughly a minute.

That’s already fast.

But from my perspective, that’s still one minute too many.

For a truly busy dealmaker, even sixty seconds is friction.

So we’re pushing aggressively toward making the experience as effortless as possible.

A good example involves meeting preparation.

Today, users receive a Ren Digest each morning with relevant information before their meetings.

We also have a feature called Ren Agent.

People can reply to those emails and ask for more information.

They might request a complete meeting brief, background on attendees, additional context, and so on.

Usage has been very strong.

So naturally we ask: why make users ask for it? Why not simply provide it? Why not let someone click a single preference and automatically receive detailed meeting briefs before every meeting?

Those briefs can include attendee backgrounds, LinkedIn profiles, recent company news, earnings information, investment activity, suggested talking points, and other context tailored to the user’s goals.

People find that incredibly valuable.

So that’s another major area of focus: asking less from users and delivering more value automatically.

There are other initiatives as well, but those are probably the categories I’m most excited about right now.

JP Bowgen: That’s a good teaser. And from Camber Creek’s perspective, we’re excited to continue supporting the company.

It’s still early in our partnership.

We have many years ahead of us.

One thing I genuinely enjoy is seeing the reactions Ren generates.

Every company in our portfolio receives positive feedback from customers.

But if I plotted the number of screenshots our team receives from users saying, “This made my life easier,” Ren would be all the way at the far right side of the chart.

It’s not even particularly close.

The product consistently creates those moments.

And I think that’s a direct reflection of the idea we’ve talked about throughout this conversation: generating serendipity.

JP Bowgen: I’m looking forward to many more years of seeing those stories emerge. It’s been a pleasure working together. Here’s to what’s ahead.

Canay Deniz: Thank you. I really appreciate it.

Lionel Foster: Thank you, Canay. This was fun.