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The latest from Sturdy — product news, insights, and resources.
Sturdy's MCP Server: One Call. Every Source. Already Resolved.
Another Step to Unlocking AI Outcomes: Resolve the Data First
The bottleneck is not your AI model. It’s the data it has access to. Sturdy’s MCP server delivers pre‑resolved, canonically organized context so your LLM can reason over it instead of guessing around it.
Another Step to Unlocking LLM Outputs: Resolve the Data First
For years, the problem was that data lived in silos. Different systems for sales, support, and calls. But the worst offenders were email and Slack. Email isn’t one silo; it’s as many silos as there are people on your team. Every rep, every CSM, every exec running their own inbox, none of it visible to anyone else. Slack is no different. Conversations buried in channels and DMs that nobody ever sees again.
What Changes
"Your LLM now has a single, usable data layer any user can query to inspect the full context of every prospect and customer."
“Every team now works from a single view of the relationship, not fragments of it. Sturdy gets everyone on the same page, no matter what screen they use.”
MCPs were a material step forward. They give LLMs a standardized way to reach outside their context window and pull live data from external systems without a human copying it in manually. An account record, an open ticket, a call summary, all accessible at query time without a custom integration.
Today, teams are dealing with a different version of the same problem. Every MCP server exposes a slice of the picture. The LLM can pull structured records, read a ticket, or fetch a call summary. What it cannot do is answer a question that requires all of them at once, because the data across those systems was never resolved against each other.
The entities don’t match. The timeline is fragmented. The thread that started the conversation often isn’t there at all.
The question every revenue team actually needs answered isn’t “what does this system say about the account?” It’s the question that requires the full picture: what has every person at our company said to every person at this company, across every channel, and what does that tell us about where this relationship actually stands right now.
No single MCP server can answer that. Most LLMs, handed raw data, will approximate an answer and present it with false confidence. That’s not intelligence. It’s a good guess.
That answer doesn’t live in any single system. It lives in the relationship between all of them. And if the LLM has to call multiple MCP servers to piece it together, resolve duplicate records, and reassemble a coherent account state on every query, the fragmentation problem hasn’t been solved. It’s just been moved into the inference layer.
What Sturdy’s MCP Does
Sturdy ingests from all of it. Email, call transcripts, support tickets, Slack, CRM, and meeting tools. Every channel where communication happens.
Before any of that reaches an LLM, Sturdy does the work that makes it usable. Entities are deduplicated and matched to canonical records. Interactions are classified. Signals are enriched, permission‑scoped, and source‑referenced. The relationship between interactions across systems is established once upstream.
Not inferred at query time. Resolved in advance, maintained continuously, and auditable.
That last part matters more than it sounds. LLMs are getting better at fuzzy matching, but revenue decisions cannot rely on it. “Probably the same account” is not good enough when you’re making retention calls, forecast commits, or expansion bets.
Then Sturdy exposes all of it through a single MCP server. One call. Pre‑resolved context with citations. The LLM starts from the signal, not the raw material.
The Token Cost Nobody is Talking About
There’s a practical consequence to raw MCP that most teams haven’t priced in yet. When an LLM has to reconstruct account context from scratch on every query, it burns tokens doing work that shouldn’t need to happen at query time.
Pulling from multiple sources. Resolving conflicts. Traversing relationships. Figuring out what it’s looking at.
At low volumes, this is invisible. At scale, it isn’t. The rediscovery tax on a raw MCP call runs roughly 60 to 80 percent of total token consumption per query. That’s the LLM figuring out context, not reasoning over it.
Sturdy removes most of that overhead. The context arrives already structured. The LLM starts from a position of knowing. The inference budget goes toward answering the question, not reconstructing the data.
What This Means for Teams Building on it
Sturdy’s MCP is designed for teams that have already provisioned an LLM and are now trying to make it useful. CTOs deploying models across their organization. Heads of Data and AI are trying to get real answers out of them. Operations teams are building agents that need reliable account intelligence.
The properties that matter:
Canonically resolved
Entity deduplication and matching happen upstream. The same account appears as one account regardless of how many systems it lives in.
Permission‑aware
Access controls are baked into the data layer. What a user can see reflects what they’re authorized to see in the source systems.
Source‑referenceable
Every signal comes with a citation. When something surfaces, the underlying interaction is linked.
Model‑agnostic
The data layer doesn’t change based on which model you use.
Nobody wants to spend 12 to 18 months normalizing data before they can build something useful. Resolving that data upstream changes what your LLM can do on day one.
Talk to us about connecting Sturdy to your existing AI deployment.
Another Step to Unlocking AI Outcomes: Resolve the Data First
The bottleneck is not your AI model. It’s the data it has access to. Sturdy’s MCP server delivers pre‑resolved, canonically organized context so your LLM can reason over it instead of guessing around it.
Another Step to Unlocking LLM Outputs: Resolve the Data First
For years, the problem was that data lived in silos. Different systems for sales, support, and calls. But the worst offenders were email and Slack. Email isn’t one silo; it’s as many silos as there are people on your team. Every rep, every CSM, every exec running their own inbox, none of it visible to anyone else. Slack is no different. Conversations buried in channels and DMs that nobody ever sees again.
What Changes
"Your LLM now has a single, usable data layer any user can query to inspect the full context of every prospect and customer."
“Every team now works from a single view of the relationship, not fragments of it. Sturdy gets everyone on the same page, no matter what screen they use.”
MCPs were a material step forward. They give LLMs a standardized way to reach outside their context window and pull live data from external systems without a human copying it in manually. An account record, an open ticket, a call summary, all accessible at query time without a custom integration.
Today, teams are dealing with a different version of the same problem. Every MCP server exposes a slice of the picture. The LLM can pull structured records, read a ticket, or fetch a call summary. What it cannot do is answer a question that requires all of them at once, because the data across those systems was never resolved against each other.
The entities don’t match. The timeline is fragmented. The thread that started the conversation often isn’t there at all.
The question every revenue team actually needs answered isn’t “what does this system say about the account?” It’s the question that requires the full picture: what has every person at our company said to every person at this company, across every channel, and what does that tell us about where this relationship actually stands right now.
No single MCP server can answer that. Most LLMs, handed raw data, will approximate an answer and present it with false confidence. That’s not intelligence. It’s a good guess.
That answer doesn’t live in any single system. It lives in the relationship between all of them. And if the LLM has to call multiple MCP servers to piece it together, resolve duplicate records, and reassemble a coherent account state on every query, the fragmentation problem hasn’t been solved. It’s just been moved into the inference layer.
What Sturdy’s MCP Does
Sturdy ingests from all of it. Email, call transcripts, support tickets, Slack, CRM, and meeting tools. Every channel where communication happens.
Before any of that reaches an LLM, Sturdy does the work that makes it usable. Entities are deduplicated and matched to canonical records. Interactions are classified. Signals are enriched, permission‑scoped, and source‑referenced. The relationship between interactions across systems is established once upstream.
Not inferred at query time. Resolved in advance, maintained continuously, and auditable.
That last part matters more than it sounds. LLMs are getting better at fuzzy matching, but revenue decisions cannot rely on it. “Probably the same account” is not good enough when you’re making retention calls, forecast commits, or expansion bets.
Then Sturdy exposes all of it through a single MCP server. One call. Pre‑resolved context with citations. The LLM starts from the signal, not the raw material.
The Token Cost Nobody is Talking About
There’s a practical consequence to raw MCP that most teams haven’t priced in yet. When an LLM has to reconstruct account context from scratch on every query, it burns tokens doing work that shouldn’t need to happen at query time.
Pulling from multiple sources. Resolving conflicts. Traversing relationships. Figuring out what it’s looking at.
At low volumes, this is invisible. At scale, it isn’t. The rediscovery tax on a raw MCP call runs roughly 60 to 80 percent of total token consumption per query. That’s the LLM figuring out context, not reasoning over it.
Sturdy removes most of that overhead. The context arrives already structured. The LLM starts from a position of knowing. The inference budget goes toward answering the question, not reconstructing the data.
What This Means for Teams Building on it
Sturdy’s MCP is designed for teams that have already provisioned an LLM and are now trying to make it useful. CTOs deploying models across their organization. Heads of Data and AI are trying to get real answers out of them. Operations teams are building agents that need reliable account intelligence.
The properties that matter:
Canonically resolved
Entity deduplication and matching happen upstream. The same account appears as one account regardless of how many systems it lives in.
Permission‑aware
Access controls are baked into the data layer. What a user can see reflects what they’re authorized to see in the source systems.
Source‑referenceable
Every signal comes with a citation. When something surfaces, the underlying interaction is linked.
Model‑agnostic
The data layer doesn’t change based on which model you use.
Nobody wants to spend 12 to 18 months normalizing data before they can build something useful. Resolving that data upstream changes what your LLM can do on day one.
Talk to us about connecting Sturdy to your existing AI deployment.
Our articles
Sturdy raises $3.1 million to strengthen its AI-led customer intelligence and automation platform
We are excited to announce that we’ve raised $3.1M in a financing round led by Lawson DeVries at Grotech Ventures. We'd also like to welcome Lawson to the board of directors. He brings over 20 years of software-focused venture investing and management experience with him.
Read the full press release here.
The idea for SturdyAI came from running SaaS businesses for the past 15+ years.
Our “Aha!” moment was when we realized that our customers were actually telling us what they want and need, every day.
The idea for SturdyAI came from building, bootstrapping, and scaling successful SaaS businesses. While running companies we realized that there is an ever-growing body of valuable data being created by our users. This feedback is just sitting in email accounts, in video conferencing systems, in chat logs, and buried in ticketing systems. We founded SturdyAI to empower businesses to solve problems that we faced as entrepreneurs and executives. At the end of the day, running a SaaS company is about keeping customers and taking advantage of the long tail of subscription revenue.
With the subscription business model reaching near ubiquity in many industries, particularly in cloud-based software, driving dollar retention (NDR) has evolved as the most important business metric. Companies with higher dollar retention are simply healthier and more valuable. So how does a subscription-based business drive dollar retention? Our earliest decks talked about, “getting your data in one spot”. But that wasn’t the problem we were trying to solve (wanting to see all the data in one spot is a symptom, not a solution). The problem wasn’t really a communication problem, it was a mining and refining problem. The problem we solve is separating the signals form the noise.
When a customer requests a copy of her contract, that message must get forwarded to the "Saves Team" - immediately. Save a customer — improve NDR.
Customers give us information to run our businesses better, to predict churn, to capture references, to get in front of renewals, to prioritize features, yet these critical signals are trapped and decaying in dozens, if not hundreds of data silos. Our customers are giving us the "answer to the test" in Slack, Email, Zendesk, Salesforce, Gong, Zoom, etc. Today, the only way we utilize this information is if someone manually identifies, records and escalates it.
These signals are immensely valuable. For example, reducing churn from 10% to 9% in a $10 million ARR business means that every customer is worth $17k more in lifetime value. And reducing churn in this example is just saving 5 customers.
Today's CX stack is missing a systems of intelligence. Sturdy fills the void.
Greylock's Jerry Chan may have coined the term system of intelligence. He wrote about the category in 2017 saying that "What makes a system of intelligence valuable is that it typically crosses multiple data sets, multiple systems of record." He actually predicted that SturdyAI would exist — "The next generation of enterprise products will use different artificial intelligence (AI) techniques to build systems of intelligence."
SturdyAI’s customer intelligence and automation solution empowers B2B SaaS companies and other subscription-based businesses to:
- Unify all sources of customer feedback like email, tickets, chats, call transcripts, surveys, and more, into a unified channel.
- Analyze all customer feedback for important business insights like churn triggers, contract requests, buyer changes, feature requests, quality of service issues, and more that help lift dollar retention (and more).
- Create just-in-time automations to drive insights to the people, teams, and systems that need them most to enable immediate actions.
We're just getting started.
We aren’t here to reinvent and change the way teams or companies work — necessarily. And that is what is so exciting about what we do. SturdyAI is the force multiplier for your business. If you already have a cutting edge BI tool, we just give it better data. If you have a good CX app, we make it more insightful. If you have spent years perfecting your customer health score, we have a new data source to make it more accurate. If you have a great Customer Success, Account Management, Operations, Marketing, and Product teams, we make them more efficient and provide them with better data.
“SaaS companies collect a ton of information from their customers every day, but much of it fails to convert to useful and actionable data. Now using AI and automations businesses can proactively understand whether their customers are likely to churn, which features will entice them to renew, are they experiencing bugs, are they happy or not, and much more.,” said Lawson DeVries, Managing General Partner, Grotech Ventures. “Customer retention and expansion are critical for SaaS businesses to maintain consistent growth trajectories, especially as we head into a more challenging environment for acquiring net new customers. Actionable customer intelligence is no longer a nice-to-have aspect for companies of all sizes – it is mission critical for businesses to thrive in today’s market. Grotech has a long history in this segment of the software market, and we are proud to be a catalyst to help fuel Sturdy’s continued strong growth and bring AI to companies that will need to do more with less now and in the future,” continued Mr. DeVries.
“Churn doesn't happen in a vacuum. It's a culmination of bug reports, feature requests, executive changes, response lags, unhappy sentiment, and more. Sturdy discovers the preemptive signals that help teams create more enduring relationships to lift dollar retention.,” said Steve Hazelton, CEO and co-founder of SturdyAI.
“Every SaaS company has a customer database of record, some have systems of action like customer success platforms but the critical component that most companies lack is a scalable system of intelligence — a system that listens to all of your customer feedback and routes the important things to the right people in the systems that they use every day. That is why we built Sturdy.”
Interested in learning more about SturdyAI? Get in touch.
Live product talk — Even unicorns have leaky buckets
Churn hurts
No matter how great your sales machine is at acquiring new customers, unwanted customer churn creates a real drag on exponential growth. If you’re not thinking about churn, you’re probably living in your own fantasy world with dragons, fairies, and other magical creatures.
SaaS companies are banking on their subscription revenue compounding. This is only feasible if you hold onto your base. What’s more: without the base, you can’t upsell and expand.
How closely are you listening to customer feedback?
Search the internet for ways to prevent churn and you’ll find all kinds of good advice. But what if we told you that your customers are sending you signals every day that have potential impact on top line revenue?
Listening to customers is harder than it sounds.
Customer-facing teams at unicorns interact with thousands of customer accounts and tens of thousands of users every month via email, chat, support tickets, video conferences, surveys, and more. Nearly 20% of of this "feedback" contains valuable insights that teams can use to improve products, strengthen relationships, and reduce churn.
You're invited
Join Joel Passen, 3x CRO and co-founder of Sturdy.ai, for a live 30 minute product talk to see how innovative customer-facing teams are leveraging AI-based solutions to better understand, improve, and expand customer relationships — and battle churn!
Jun 7, 2022 11:00 AM Pacific Time (US and Canada)
During this product talk you’ll learn:
- How post-sales teams are leveraging data that has previously been hiding in plain sight to detect potential churn
- How CX teams can easily deploy AI-based technology to gain new insights on how to deliver value to their customers
- How product, customer advocacy, and leadership teams can access unbiased customer insights
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Live presentation - How payroll companies are improving client retention rates with data hiding in plain sight
Teams at payroll companies interact with hundreds of customers every month via email, chat, support tickets, video calls, surveys, etc. Everyday customer conversations create an enormous and ultra-valuable data set.
On average, a $10m payroll company produces more than 10,000 customer conversations every month. Nearly 20% of those conversations contain valuable information that teams can use to improve client retention rates and improve the overall customer experience.
Stay competitive. Start improving processes, relationships, and revenue by using the most valuable data you already have: the conversations you’re having every day with customers.
Save your spot. Register now.
Join Sturdy’s CRO, Joel Passen (Paycor, Newton), for 30 minutes to see how innovative teams are leveraging customer conversations to impact the top line with Sturdy’s modern customer intelligence solution to:
- Gather valuable customer intelligence at scale
- Automate repetitive, inefficient, yet critical tasks
- Turn the voice of the customer into actionable outcomes
Live Workshop - The New Data Frontier — Leveraging Language for Customer Intelligence
Live Workshop: Leveraging Language for Customer Intelligence
Apr 28, 2022 10:00 AM Pacific / 1:00 PM Eastern
Register here
In B2B SaaS businesses, customer-facing teams interact with hundreds of customers every month via email, chat, support tickets, and video calls. Nearly 20% of those conversations contain valuable information that teams can use to improve products, strengthen relationships, and impact revenue. For subscription-based businesses, the insights that can be derived from a company’s language cube makes accessing this data a business imperative for leaders.
Customer language is an enormous data set. On average, a $30m B2B SaaS company produces more than 10,000 customer conversations every month. How closely are you listening?
Capturing, consolidating, and analyzing the true voice of the customer sounds like a good idea, right? To be a successful customer leader, your teams must be able to devise new ways to improve the overall customer experience and, at the same time, drive value. With a plan in place to use customer language — the authentic voice of the customer — your line of business is empowered to influence customer engagement through better product inputs, build deeper relationships with multiple stakeholders, and drive revenue retention and net dollar retention.
You and your team are invited!
Join Cynthia Beldner, Customer Success and Operations leader, for 30 minutes to see how innovative teams are leveraging customer conversations to:
- Gather valuable customer intelligence at scale
- Automate repetitive, inefficient yet critical tasks
- Turn the voice of the customer into data any team can access and use
This is also a great opportunity to see Sturdy in action.
Save your spot. Register now.
Salesforce integration 2.0: Enrich Salesforce with Sturdy Signal event insights
Sturdy’s two-way Salesforce integration makes customer insights – about products, processes, relationships, and revenue – actionable, trackable and reportable in any object in Salesforce.
Sturdy is a customer intelligence solution trusted by leading CX, product, and operations leadership at some of the most innovative B2B SaaS companies.
This easy to implement solution is designed to help businesses and organizations improve their products, processes, relationships, and revenue by using the most valuable data they already have: the conversations they’re having every day. Not only can Sturdy detect signals in conversations — in real time — accurately, now it can automatically push critical signals and insights to systems and humans that need this critical information the most - no coding required.
How to Enable Your Team
Sturdy detects events and insights– executive change, expansion opportunities, unhappiness – from your emails, call transcripts, chats, support tickets (wherever customers are talking with you)! The full details of the conversation and signals detected are sent to Salesforce. A new Signal Event is assigned to the right team member and, of course, recorded to enhance reporting, health scores, etc.
See for Yourself
Interested to learn more about how the Sturdy Customer Intelligence Platform can help empower your teams with the insights to build better products, relationships, and processes to help you teams scale? Request a demo and we’ll be happy to show you.
Announcing the new Renewal Signal
It is widely known that it costs five times as much to acquire new customers than it does to keep existing ones. Renewals are tied to more than just LTV (Lifetime Value), they also directly influence customer acquisition costs (CAC), budgeting, margins, and brand reputation. According to Gartner Group Statistics, 80% of your future profits will come from 20% of your existing customers. Renewals are the lifeblood of SaaS businesses. This is why we are excited to announce our latest language model that detects when customers are conversing about - Renewals.
Here is how it works.
Sturdy is an AI + automations platform that unites all user language and converts it to data so that other people, teams and products can leverage that data. For example, when a user says, “Hey, when is our renewal date?” in an email to the accounting team (or through any other channel), Sturdy will flag it. Next, using Sturdy's no-code automation engine, the signal is routed to the appropriate account manager or teammate (who likely would never have been notified or notified too late) who can take action.
In addition to relying on top-of-the-funnel demand gen activities to bring in new business, leaders must turn their attention to a key source of growth hiding in plain sight- your customers (we have a signal for this too - Expansion). Systematically detecting critical business signals like renewals and ensuring that the appropriate people on your team are responding quickly needs to be part of your growth playbook.
Announcing Sturdy Automations 💥
Whether your SaaS business serves 500 or 500,000 users, success hinges on relationships with your users. Unfortunately, listening to users isn't all that easy given the volume of everyday communications and the number of tools in play like email, ticketing systems, chat, video calls, Gong, etc. To compound matters, users are often communicating with multiple people on multiple teams. Deriving value from this data set that is practically hiding in plain sight has been, until now, nearly impossible.
Enter automation. Automation allows you to better understand your relationships with users and provide a better user experience in the process. Automation in this context is the process of using AI and robotic process automation to discover insights and trigger actions at scale.
Introducing Sturdy Automations
Take your workflows a step further with our automations! This new powerful functionality allows you to create your own automated workflows without writing a single line of code. Build out new combinations tailored to the needs of specific teams that want more information about your company’s users. Then extend workflows in the systems they work in the most. Today, Sturdy customers can begin adding custom automations in a few easy steps.
Step 1. Choose a Signal
The first step in building your automations is to pick a signal. A signal is transmission delivered intentionally or unintentionally by a customer that conveys information, instructions, or insights. Customers send signals that help us predict churn, capture references, get in front of renewals, prioritize features, and just run our businesses better. Our customers are giving us this information every day in email, tickets, chats, calls, and more. In fact, we know that nearly 17% of all user-to-business communications contain a signal.
Step 2: Select a field
Depending on the signal you've chosen in step one, you will then select a field. A field is a set of identifiers and attributes that describe a customer. Common examples of a field may include the customer ARR, segment, territory, support level, even custom fields are pulled into Sturdy. The list of fields is populated via API from your master customer database of record like Salesforce.com.
Step 3: Set a value
Now that the first part of our automation (signal + field) is ready, it is time to pick a value. Like fields, values are populated from your master customer database sent to Sturdy via API. For our automation, we selected the field Salesforce Account Customer Segment. The corresponding value in Salesforce is a monetary value imported from a pick list in Salesforce.com.
Step 4: Pick someone to notify
Your automation recipe is nearly complete. Now you just need to pick someone or a system to notify. To customize the exact notification that will occur, pick a notification method. Email and Slack are automatically enabled and available today. In just a few weeks, you can add Salesforce, your CSP, Jira, etc.
What’s next.
In the next few months, we’ll empower Sturdy users to create longer and more complex automation recipes with multi-step automations. And, later this year, our plan is to create a library of pre-prepared recipes to make it even easier to get started.
Sturdy's new Happy Signal means more customer references and deeper insights
Let's talk about the potentiality of happy users. They stay with your business longer and, on average, they spend 67% more than new customers. The power of user advocacy is punctuated by the demonstrable success of NPS leaders. In Fred Reichheld's recent book, The Ultimate Question 2.0 he notes that over the past decade the firms with the highest brand loyalty and subsequent NPS scores returned five times the U.S. median (for public companies with +$500m in revenue).
Happy users often require less support and inspire your customer-facing teams to deliver similar experiences across your user base. They provide valuable testimonials, reviews, references, and case studies. That’s we developed Sturdy's - Happy Signal.
Here’s how it works. We’ve built technology that detects items of importance like user happiness, among other things, in user-to-business communications like email, support tickets, video conferences, chats and more. For example, when a user responds to an email or support ticket with, “I can’t thank you enough --- you just saved me so much time! You’re the best!”, Sturdy will instantly recognize this as a signal, flag it, and get it to the right teammates.
Most businesses use CRM, spreadsheets, and reference management tools as the go-to location to find and request references but they lack functionality to build a sustainable customer reference pipeline. Continuously building a pipeline of references is a key use case and measurable value proposition for Sturdy.
Sturdy is like a lead generation tool for customer references. On average, businesses using Sturdy see a 2.5x increase in customer references in the first 6 months of getting started.
Sturdy releases new business Signal - Response Lag
The Response Lag signal calls out when customers are waiting for responses from customer-facing teams and are chasing your associates for updates, actions, access, etc.
Sturdys newest business signal is live in customer accounts. The Response Lag signal calls out when users are waiting for responses from customer-facing teams and are chasing your associates for updates, actions, access, etc. How do we do this? We start by ingesting every customer communication (emails, tickets, calls, chats, etc.). Then we use NLP/AI to discover signals like Response Lag. Next we transmit those signals to the people and systems so action can be taken.
While top line monetization opportunities tend to get the attention, often the biggest, near-term lift for B2B SaaS and SaaS-enabled businesses is operational in nature. The Response Lag signal gives managers insights into areas for service improvement and illuminates coaching opportunities that, ultimately, help to foster better relationships with customers.
Next up is our Security signal. It detects when Customers indicate in their conversation some sort of security concern, like: “Have you had a data breach?” Appropriately, look for the red customer signal called Security.
Sturdy releases new business Signal - Expansion
Expansion is a critical stage of a successful SaaS growth strategy and the overall customer journey. It’s all about further monetizing the customers you have, and broadening your footprint so you have a larger target market to pursue. That’s why we are excited to announce that we’ve added a new customer signal to our AI-powered customer intelligence platform called “Expansion”.
The new Expansion signal empowers Sturdy users to identify when their users express purchasing intent like adding more users, buying services, or upgrading their plan.
Given the volume of customer conversations across various communications channels, valuable customer signals like those that imply account growth are often trapped in layers of technology, across multiple teams, gathering digital dust. Our newest signal, Expansion, cuts through the noise and across silos to help customer success and account management teams seize on critical upsell opportunities.
Want to get Expansion signals? Getting started is refreshingly easy and won't strain your internal resources. 95% of the initial work to get started is done by the team at SturdyAI. Sturdy leverages data that you are already collecting with existing systems (email, CRM, ticketing systems, video conferencing, etc) and can be configured to leverage those same systems to receive insights so your teammates can work in the platforms they are most accustomed to. Clients typically start receiving their first customer signals in less than 4 weeks. Realizing value thereafter is nearly immediate. No change management or IT resources required!
