AI tips & trends

Sturdy's Customer Intelligence Platform performs real-time revenue threat root cause analysis, and delivers cross-functional insights to the teams and systems to mitigate churn.

Portland, OR — April 1, 2025 — Sturdy.ai, a pioneer in AI-powered customer intelligence, today announced it has raised $6M in Series Seed funding. Voyager Capital led this round, with participation from Fortson VC as well as existing investor, Grotech Ventures. The funds will be used to deepen Sturdy’s AI capabilities, expand integrations with customer data silos, and grow its go-to-market and engineering teams.

Modern Teams Need Actionable Intelligence to Protect and Grow Revenue

With customer expectations higher than ever and retention under pressure, the need for proactive, AI-driven revenue insights has never been more urgent. According to industry data, reducing churn by just 5% can increase profits by up to 95%. Enterprises have spent millions on building silos of applications to get closer to their customers and create active communication channels in the hope of mitigating churn risk early. Yet, this has failed to provide the proactive warning signals required. Sturdy closes the gap by seeing across these silos for a unified view of customer communication.

“We’re creating an AI-first intelligent interface for all things customer. This allows Sturdy to provide an almost magical understanding of every customer interaction across every data silo,” said Steve Hazelton, CEO and co-founder of Sturdy.ai. “This funding enables us to move faster to empower teams to stay ahead of risk and unlock new revenue opportunities.”

Investors Bet Big on AI-Powered Revenue Threat Detection

The funding round attracted a strong syndicate of investors aligned on Sturdy’s vision for a more innovative, AI-native approach to revenue intelligence. Voyager Capital, known for backing category-defining SaaS platforms, led the round, with General Partner Diane Fraiman joining Sturdy's board.

“Sturdy is tackling one of the most urgent and overlooked problems in enterprise software—how to extract proactive insights from the flood of daily customer interactions,” said Diane Fraiman, Managing Director of Voyager Capital. “Retention has become a critical topic in boardrooms. We believe that every business will have a system of intelligence in the next 3 years. Sturdy’s platform is positioned to become essential infrastructure for any company serious about protecting and growing revenues while truly putting their customers first.”

“Sturdy is one of the most powerful and immediate applications of AI and natural language processing we’ve seen,” said Thomas O’Keefe, CEO of Solo LLC. “At both Solo and previously at Syntrio, it has delivered instant value—surfacing proactive, actionable customer insights and driving measurable improvements in retention.”

About Voyager

Voyager Capital is a leading West Coast early-stage venture firm, providing entrepreneurs with the resources, experience, and connections to build successful companies for today’s modern economy. Voyager invests primarily in B2B technology companies, including AI-driven business solutions, software-driven hardware, sustainable agriculture, and supply chain. The firm's domain expertise, go-to-market, and team-building resources are proven to help build market leaders. Voyager Capital has over $550 million under management with offices and resources in Seattle, Portland, Vancouver, and Calgary. 

About Fortson VC

Fortson VC is a seed-stage venture firm based in the Pacific Northwest, built for exceptionally rare founders who are pushing the boundaries of what’s possible.  Led by Cole Younger, Fortson brings over two decades of early-stage investing experience and a disciplined approach grounded in authenticity, grit, and courage.  While driven by curiosity, our primary focus is B2B software and the technological frontier around it—the infrastructure, intelligence, and automation shaping the future of how businesses create value.

About Grotech Ventures

Founded in 1984, Grotech Ventures is a leading early investor in high-potential technology companies. Grotech seeks innovative, early-stage investments across the technology landscape and continues to invest and add value throughout the life cycle of each portfolio company. The firm has a strong combination of financial backing, industry relationships, and deep domain and operational expertise to accelerate growth. With more than $1.0 billion in committed capital, Grotech supports early-stage companies through investments starting as small as $500,000. For more information, visit http://www.grotech.com.

About Sturdy

Founded in 2020, Sturdy is an AI-forward autonomous Customer Intelligence platform that proactively identifies churn risks across all customer-facing silos. Sturdy analyzes unstructured customer interactions—emails, calls, support tickets, chats, and more—discovering revenue threats, pinpointing root causes, and delivering cross-functional insights in real time. Sturdy has analyzed billions of customer interactions, giving it one of the largest proprietary datasets in the category and enabling its models to surface insights faster and more accurately than competitors. At a time when customer retention is a top priority for every business, Sturdy turns the noise of customer conversations into a strategic advantage.

For more information, visit www.sturdy.ai or reach out to Joel Passen at joel@sturdy.ai

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We’re making it easier than ever to turn customer feedback into action while saving businesses hundreds of thousands of dollars per year. With Sturdy’s new Jira Connect, any AI-powered Signal in Sturdy can be automatically logged in Jira—helping teams capture, prioritize, and resolve issues faster than ever.

Sturdy for Jira is a Game Changer

Every team needs to know more about their customers. 

Turn customer feedback into valuable Jira content automatically. Sturdy’s AI accurately detects feature requests, bug reports, and other critical product feedback. Customizable agents then deliver this context-rich intelligence to a configurable staging area in Jira with all relevant user and account details, such as segment, ARR, and more. The content is objectively summarized automatically. From there, assigning it to an epic, task, sprint, or release is just one click.

Productivity Gains that Move the Needle

Businesses are unknowingly spending hundreds of thousands of dollars per year on something as simple as manually logging Jira issues. A single customer-facing rep wastes nearly 87 hours annually on repetitive data entry—scaling up to a staggering $354,200 per year for a team of 100 reps. By integrating Sturdy’s AI-driven automation, businesses can reclaim thousands of hours, improve productivity, and reinvest those savings into growth and innovation—all while ensuring more accurate, real-time data flows into Jira effortlessly.

Align product teams with customer reality.

By centralizing AI-powered insights in Jira, Sturdy ensures that product and engineering teams get a complete, objective picture of what’s working, what’s broken, and what needs to be built—without relying on anecdotal feedback. Customer-reported issues appear in Jira moments after they happen, ensuring your product and engineering teams stay ahead of emerging trends and critical bugs—without the lag of traditional reporting.

Effortless setup, immediate impact.

Sturdy’s turnkey integration takes minutes to configure. Once connected, your team gains instant access to context-rich, structured feedback—helping you make faster, data-driven decisions that improve customer satisfaction.

Want to get started? Click the 'Schedule Demo' button at the top of the page.

We’re making it easier than ever for teams to tap into the power of customer conversations. With this integration, Sturdy’s AI-driven insights—trained to spot key behaviors and trends unique to your business—are now right where your team works. That means more proactive decisions, better collaboration, and a serious productivity boost.

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Here’s how Sturdy works with Slack.

• Get the right insights, right in Slack. Sturdy delivers AI-powered Signals where your team already works, flagging risks, expansion opportunities, and other key moments in real-time. No more digging through conversations—just actionable insights when you need them.
  
  
• Stay on top of every conversation. If your team works asynchronously in Slack channels, it’s easy for important feedback to get lost. Sturdy keeps you ahead by surfacing critical insights before they slip through the cracks.
  
  
• Act fast, not after the fact. Whether it’s a service risk, a feature request, or a potential upsell, Sturdy helps teams spot and respond to what matters—without disrupting their workflow.
  
  

Seamless sync with your tools. Sturdy doesn’t just stop at Slack. Insights discovered in customer Slack channels automatically flow into Jira, CSPs, CRMs, and other systems, ensuring the right teams get the right info—without extra work.

He doesn’t talk much, but when he does, you’d better listen.

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Quote from C-3PO, Star Wars: A New Hope

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A few days ago, I spoke to a business leader, and they asked, "How would Sturdy work for customers who never contact us?"

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"Do you know who those customers are?"

"No idea."

"Would you like to?"

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“Dark Customers.” It is almost impossible to source this list. Your customer might be dark to five silos, and bright in just one. 

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(By the way, there is a little-known filter in the Accounts page of Sturdy that lets you sort by “Last Inbound.”  Check it out. You can see the last time any customer sent you an inbound message.)

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Let’s be fair. In a recurring-revenue business, a lack of inbound contact isn’t necessarily bad. Sometimes your customers don’t feel the need to chat with you, but they like you just the same. 

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But, here’s the cool thought. What should happen when a Dark Customer suddenly reaches out? 

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For example, Acme Corp sends an email to your CS team for the first time in 18 months. What needs to happen next?

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I would want to know. So, we’re working on that. Naming such a signal is a bit tricky, if you have ideas, let us know.

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The future doesn’t belong to systems that store data and automate workflows—it belongs to those that synthesize information, surface insights, and drive action.

The days of bouncing between screens, hunting for information, and manually aligning teams? Numbered.

Every day, we are getting closer to a workplace where:

-Knowledge workers won’t be glorified data entry clerks. Technology will finally do the heavy lifting, freeing them to focus on strategic work. These people will be responsible for outcomes without being encumbered by the tedium. As a result, we will need fewer people to acquire and keep our customers.

- Every team continues to work on their screen of choice, but the data they have access to will be aggregated across every system. They may be on different screens, but everyone will be on the same page. The next era is about alignment, automation, and AI-driven decision-making.

- There will be a fundamental shift in the tech business model. Businesses won’t pay for ‘seats’—they’ll pay for intelligence. The old model of software—charging for logins, licenses, and user seats—is dying. No one wants to pay for access to another tool; they want outcomes, insights, and automation that drive real impact. The solutions that deliver intelligence over any interface will define the next era of technology.

The shift is happening—those who embrace it will lead, while those who resist will be left behind. The future belongs to businesses that trade inefficiency for intelligence, that replace busywork with impact, and that empower people to think, create, and drive outcomes—not just enter data. Innovation doesn’t wait.

I've seen a slew of new AI companies doubling down on analyzing usage data as the silver bullet for predicting churn. It’s an attractive idea—track how often customers log in and how many features they use, and you’ll magically, often with some proprietary algorithm, you'll know who’s at risk and who’s primed for expansion.

That’s not how reality works.

Usage data alone is riddled with false positives, often creating a distorted view of account "health." A customer heavily engaging with your product isn’t necessarily satisfied—they might be struggling and frustrated. A drop in product usage doesn’t automatically signal churn risk—perhaps the customer has completed implementation and is now deriving value without needing to log in frequently.

🚨 High Usage ≠ HappinessCustomers with high usage might actually be frustrated and, therefore, a risk. Why are they opening support tickets and emailing their CSMs?Are they engaging because they love the product—or because they can’t figure something out? What are they saying? What’s the context?

⚠️ Low Usage ≠ Churn RiskThe modern technology landscape isn’t about engagement for engagement’s sake—it’s about delivering value with minimal friction. ✔️If your product makes life easier, customers shouldn’t need to use it constantly.

✔️Instead of measuring time spent, measure outcomes.

✔️Instead of chasing logins, track behaviors.This requires context—something raw usage data doesn't provide.

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📉 Usage ≠ RenewalsIn SaaS, high usage doesn’t guarantee a renewal.Renewals are driven by:

✔️ Perceived value (or lack thereof)

✔️ ROI & business impact

✔️ Alignment with evolving needs

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To truly predict and drive retention, track the right contextual signals like:

✔️ Contract issues

✔️ Bi-directional responsiveness and closed-loop resolutions

✔️ Budget and procurement discussions

✔️ Expansion/contraction language

✔️Change order requests

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Look for specific context beyond sentiment.

🔍 No Context, Limited InsightsUsage data doesn’t explain why something is happening. Why did usage drop?

⁉️ Did the customer stop needing what you sold them, or are they trialing a competitor?

⁉️ Have users given up on your solution and found a workaround?

⁉️ Is usage dropping in specific customer segments (e.g., corporate accounts)?

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You won’t find these answers in product telemetry alone.

Companies that get this wrong focus heavily on usage metrics and then wonder why their churn predictions fail.

The ones that get it right combine usage data with contextual signals—the insights that explain the "why."

Real-world signals tell you how customers feel and what they need, not just which buttons they click and how often.

If your account management strategy is built purely on tracking usage and opinions, you’re looking at a puzzle with half the pieces missing.

Our data scientists have combed through mountains of unstructured customer usage data to crack the code on proactively identifying accounts that are a churn risk. After analyzing thousands of signal combinations, we found that four key indicators—Budget Issues, Unhappiness, Value Issues, and Urgency—are the ultimate predictors of revenue risk.

Nearly every B2B tech and services company sees the same pattern: when these signals align, it’s time for action.

Hold on, what is unstructured usage data? It’s the raw, untamed data that tells you what customers are *really* doing and saying—not just what they’re willing to admit in a survey or conveyed by numbers of daily average logins (also critical but lacking context). Here are the harbingers of risk; when combined, they are what the team needs to act on right now. 🧯

1️⃣ Budget Issue: This signals a customer struggling to justify the cost, possibly due to tighter budgets or a perceived lack of value.

2️⃣ Unhappy: Customer dissatisfaction can stem from unmet expectations, unresolved issues, or lack of engagement.

3️⃣ Value Issue: If a customer doesn’t see the ROI, they’ll start questioning the worth of your service.

4️⃣ Urgent: An urgent flag indicates an immediate problem that requires rapid action. They are expressing a need to engage with a teammate now.

If improving revenue retention is a key priority in FY25, here is some food for thought. If you believe data is the essential foundation for improving retention, imagine the possibilities with 50-100x more data about your customers. Here’s the thing: Every business has this customer data, but 99% of businesses are sleeping on a data set that could change their business. It’s the unstructured data that’s sitting in ticketing systems, CRMs, chat systems, surveys, and the biggest silo by volume - corporate email systems. Most of us still rely on structured data like usage, click rates, and engagement logs to gauge our customers' health. However, structured data provides only a partial view of customer behavior and revenue drivers. Unstructured data—like customer emails, chats, tickets, and calls —holds the most valuable insights that, when leveraged, will significantly improve revenue outcomes.

Why Unstructured Data is Essential for Revenue GrowthImproving Customer Retention: Unstructured data helps businesses identify early warning signs of dissatisfaction, allowing them to create proactive interventions before customers churn. Repeated mentions of poor experiences, response lags, product-related frustration, and more in call transcripts, cases, and emails indicate potential churn risks. By identifying these trends while they are trending, businesses will improve retention.

Fueling Product Innovation: Let’s face it: Our customers bought a product or service. Post-sales teams don’t develop products and are limited in what they can directly impact. Product teams need more unbiased, unfiltered contextual customer data, and they need it consistently. Unstructured data provides real-time feedback on how customers use products and services. Businesses can analyze customer feedback from multiple channels to identify recurring requests and pain points. This data fuels product innovation and informs customer-led roadmaps that lead to higher engagement rates and more profound value. Developing products that directly respond to customer feedback leads to faster adoption, better advocacy, and a competitive advantage.

Identifying Expansion Opportunities: Unstructured data reveals customer needs and preferences that structured data often overlooks. Businesses can uncover untapped expansion opportunities by analyzing email, chats, and case feedback. These insights help identify additional products or services that interest customers, leading to new upsell or cross-sell possibilities. To drive immediate improvements in revenue retention, the key isn't pouring resources into complex churn algorithms, chatbots, or traditional customer success platforms—it's being more creative with the data you're already collecting. Start listening more closely to your customers, identify the patterns in their pain points, and share this knowledge with your peers who can improve your offerings. This is the year to start thinking outside of the box.

Last year, I bought a pair of ski pants and the zipper fell out on the first chair lift. I called Burton, and they offered an exchange. New pants, first chair, same problem. Support informed me that I was required to return the pants for repair. The repairs would be completed after ski season. For the inconvenience, Burton offered me a 20% discount on my next purchase of skiwear. The next time I am in the market for skiwear that I can't wear during ski season, I will use that coupon.

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I started my first business over 25 years ago. Since that day, I have lived in an almost constant state of fear that somehow, somewhere, things would get so broken that we'd treat a customer like this.

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Let's be clear, no one who runs a business wants stuff like this to happen. Yet, it happens all the time.

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If you run a software company, your engineering team will have usage tools and server logs to tell you when your product is "down" or running slowly. They can report which features are being used and which ones aren't. You'll learn that certain features in your product cost more to run than others, maybe because of a bad query, code, or something else. And you'll know what needs to be upgraded.

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However, every time a customer contacts a business, they are "using" (or "testing") your product. If you sell ski pants, your product is ski pants, and your customer service team. If you sell software, your product is your tech and your customer service.

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Yet, your customer-facing teams have very poor usage data, if any at all. Which feature of our service gets used the most (billing, success, support)? What are the common themes? Is one group working more effectively than the others? Does a team need an upgrade? 

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(BTW, what costs more, your AWS bill or your payroll?)

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The reason your customer-facing teams don't have usage data is because this data is "unstructured," and it is everywhere. Imagine if your engineering team needed to check 50 email inboxes, 1,000 phone recordings, a CRM, and a ticket system to get your product usage statistics. 

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That's where your customer-facing teams are today. Until you can get answers from these systems as easily as an engineer can, you’ll continue to churn, annoy customers, and try to hire your way out of a retention problem. It won’t work.

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The question is no longer about whether you will use AI; it’s when. And no matter where you are on your journey, navigating the ethical implications of AI use is crucial. Ethical AI is not just a buzzword but a set of principles designed to ensure fairness, transparency, and accountability in how businesses use artificial intelligence. In the case of Sturdy, we’ve made ethical AI a core commitment. These principles guide our every move, ensuring AI benefits businesses without crossing the line into unmitigated risk.

What Is Ethical AI?

Ethical AI refers to developing and deploying AI systems that prioritize fairness, transparency, and respect for privacy. For businesses, this means using AI to make smarter decisions while ensuring that the data and technologies used do not cause harm or reinforce biases. The importance of this cannot be overstated—AI has the potential to either empower or exploit, and ethical guidelines ensure we remain on the right side of that divide.

Sturdy’s Commitment to Ethical AI

Sturdy's approach to AI revolves around several inviolable principles:

1. Business-Only Data Use: Sturdy’s AI systems focus solely on improving how businesses make decisions. They don't delve into personal data or manipulate information for other purposes. The data processed by Sturdy comes from business sources like support tickets, corporate emails, or recorded calls—never from personal channels.
2. No Ulterior Motives for Data: The data collected by Sturdy is knowingly provided by our customers, and the company doesn't use this data for any purpose beyond what's agreed upon. This ensures transparency and trust between the platform and its users.
3. Privacy and Protection: One of the most critical aspects of Sturdy’s approach is its commitment to not allowing any entity—whether a business or government—to use its technology in ways that violate privacy. If a client were found to be doing so, Sturdy would terminate the relationship.
4. No Deception: Our product is engineered to prevent deception. It never manipulates or deceives users, ensuring that the insights drawn from AI are used to enhance business practices rather than exploit loopholes.

Human Oversight and the Role of AI

At the core of Sturdy’s AI principles is the belief that AI should not replace human decision-making but augment it. Our Natural Language Classifiers (NLCs) are built to detect risks and opportunities based on the probability that a conversation indicates a particular issue. For example, when a customer complains about a "buggy" product, Sturdy’s AI might tag it as a "Bug" and label the customer as "Unhappy." However, humans remain in control—analyzing the situation and deciding the best action.

Final Thoughts

Sturdy's approach to AI exemplifies how businesses can responsibly use technology to drive growth and improve operations while safeguarding ethics. They demonstrate that AI doesn’t need to infringe on privacy or replace human decision-making. Instead, AI should be a tool that empowers teams, ensures transparency, and upholds ethical standards. Navigating the ethics of AI is not just a challenge—it’s an ongoing commitment, and Sturdy is setting a new standard for how it should be done.