Backing from semiconductor and manufacturing leaders will scale Flexcompute's research toward AI that understands the laws of physics, not just patterns in data

BOSTON, Oct. 12, 2026 /PRNewswire/ -- Flexcompute, the physics company, today announced strategic investment from Samsung Ventures and Applied Ventures, LLC, the venture capital arm of Applied Materials, Inc., among other investors. The funding will accelerate Flexcompute's work on the Physics World Model: AI that predicts how any design will behave in the real world by learning the laws of physics themselves, from a chip package warping under heat to a spacecraft reentering the atmosphere. Details of the investment were not disclosed.

Today's AI learns from the past: text, images, simulation results. Flexcompute takes a different approach. Its team of more than 70 PhDs has built CFD, electromagnetic, structural and thermal solvers from the ground up on GPUs. Through Tokenized Physics, Flexcompute builds both neural networks and first-principles physics directly into the Physics World Model, so every prediction obeys the same conservation laws as the physical world and stays accurate on designs, even ones the model has never seen.

"AI is changing how products are designed, but those products still have to obey the laws of physics," said the representative of Samsung Ventures. "Flexcompute is building AI that understands those laws, not just the data. We believe the Physics World Model will shape how the next generation of hardware is developed."

The approach is already solving problems that traditional simulation cannot reach. For a full advanced semiconductor package, with more than 800,000 solder joints, an ASIC, and 32 optical engines, Flexcompute solved a 5-billion degree-of-freedom (DOF) warpage model within 2% of commercial finite-element results in minutes.

"Every industry is racing to put AI to work on real engineering problems, and the limit is how quickly each one can be validated against the laws of physics," said Yu Cao, Chief AI Officer of Applied Materials. "Flexcompute has built something unique: simulation fast enough to keep pace with AI and rigorous enough for production decisions. In advanced manufacturing, that means more of the design cycle happens digitally, saving time and cost."

Customers access the Physics World Model today through Physics Twins: models of their own products that engineers and AI agents can question, test and optimize before anything is built. Engineers set the objective and approve the result, agents run the iterations, and physics governs what works.

"Language models learned the world from text. Hardware is governed by laws, not text, and no amount of data substitutes for them," said Vera Yang, Co-Founder and President of Flexcompute. "We are building the verification layer between bits and atoms: a Physics World Model any engineer or AI agent can ask whether a design will work, before it is built. Samsung and Applied see what we see: the next leap in AI comes from understanding the physical world."

Flexcompute will use the investment to grow its research team, scale GPU compute, and extend the Physics World Model across fluids, electromagnetics, structures, heat, and multiphysics couplings.

About Flexcompute

Flexcompute is a frontier AI lab building a Physics World Model that bridges data-driven AI and the laws of physics. Founded by researchers from Stanford and MIT, its team of more than 70 PhDs develops GPU-native solvers for fluid dynamics, electromagnetics, structures, and heat. Through Tokenized Physics, Flexcompute builds both neural networks and first-principles physics directly into its Physics World Model. This creates a verification layer that grounds AI predictions in trusted physics and helps engineers and AI agents evaluate how designs will perform before they are built. Engineering teams at more than 250 companies across aerospace, automotive, semiconductors, photonics, and advanced manufacturing use Flexcompute to evaluate, explore, and optimize designs, allowing them to innovate with confidence. Learn more at flexcompute.com.

About Samsung Ventures

Samsung Ventures is the corporate venture capital arm of Samsung, investing globally in early and growth-stage technology companies across semiconductors, AI, and advanced manufacturing.

About Applied Ventures

Applied Ventures LLC is the venture capital arm of Applied Materials, Inc., the global leader in materials engineering solutions for the semiconductor industry. Applied Ventures invests in companies developing technologies that advance semiconductor and display manufacturing.

Media Contact

Silvie Casanova

Flexcompute

[email protected]

SOURCE FlexCompute Inc.

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ATHENS, Ga. and SAN JOSE, Calif., Oct. 12, 2026 /PRNewswire/ -- Blue Lake Biotechnology, Inc., a clinical-stage intranasal vaccine company developing parainfluenza virus 5 (PIV5)-vectored vaccines that harness the full breadth of the immune system to protect against serious infectious diseases, today announced that interim data from the company's Phase 1/2a pediatric clinical trial of RSV vaccine candidate BLB201 will be presented as a late-breaking abstract during the International Society for Vaccines 2026 Annual Congress in Antwerp, Belgium. The oral presentation will include updated safety and immunogenicity data from both RSV-seronegative and RSV-seropositive children ranging in age from eight to 59 months.

Presentation Details

Title: PIV5-vectored Intranasal RSV Vaccine is Safe and Immunogenic in Infants and Young Children

Date/Time: October 12, 2026 17:20 CET

Presenter: Biao He, Ph.D., CEO, Blue Lake Biotechnology

About RSV and BLB201

Respiratory syncytial virus (RSV) is a highly contagious virus that infects over 64 million people worldwide each year. While RSV typically causes mild, cold-like symptoms, it can cause severe and potentially life-threatening disease in infants, older adults, the immunocompromised, and people with certain chronic health conditions. In the U.S., RSV causes up to 80,000 hospitalizations among children under five and up to 160,000 among older adults annually, with up to 10,000 deaths.

BLB201 is an intranasal RSV vaccine candidate being evaluated in Phase 1/2a clinical testing in children ages eight to 59 months. Interim data have indicated that BLB201 may prevent symptomatic RSV infection in young children. BLB201 has received Fast Track designation from the U.S. Food and Drug Administration for prevention of RSV-associated acute respiratory disease in adults over 60 and pediatric populations. BLB201 uses a proprietary PIV5 vector to express the RSV-F protein. PIV5 has been used for decades in canine vaccines and is not known to cause human disease.

About Blue Lake Biotechnology

Blue Lake Biotechnology, Inc. and affiliate CyanVac LLC are developing intranasal vaccines designed to activate mucosal, systemic, and cellular immunity. Our proprietary PIV5 platform mimics natural infection while expressing proteins from targeted pathogens. Our clinical-stage pipeline includes vaccines designed to prevent respiratory infections and overcome limitations of existing vaccine technologies.

Learn more at Blue Lake Biotechnology.

Contact:

Samuel Wu, Chief Business Officer  

Blue Lake Biotechnology, Inc. and CyanVac LLC

[email protected]

650-609-2231

SOURCE Blue Lake Biotechnology, Inc.

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RESTON, Va. – General Dynamics (NYSE: GD) announced today that its board of directors has elected Danny Deep to be a director of the corporation.

Deep, age 56, has served as the president of General Dynamics since December 2025. He has been with the company for more than 20 years. Prior to his role as president, he held various operating roles within the company, including executive vice president for Global Operations, executive vice president for Combat Systems, and president of General Dynamics Land Systems.

Danny’s deep operational experience and superb judgment honed during a decades-long career at General Dynamics bring important skills to the company’s board,” said Phebe Novakovic, chairman and CEO. “We look forward to his valuable contributions.”

Headquartered in Reston, Virginia, General Dynamics is a global aerospace and defense company that offers a broad portfolio of products and services in business aviation; ship construction and repair; land combat vehicles, weapon systems and munitions; and technology products and services. General Dynamics employs more than 120,000 people worldwide and generated $52.6 billion in revenue in 2025. More information is available at www.gd.com.

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FALLS CHURCH, Va. – General Dynamics Information Technology (GDIT), a business unit of General Dynamics (NYSE:GD), announced today that it was awarded the Enterprise Network Operations and Cybersecurity Support (ENOCS) contract to deliver comprehensive enterprise IT and cybersecurity services for the Army National Guard and other federal government partners. The new $1.3 billion contract, awarded by the General Services Administration (GSA) Assisted Acquisition Services, has a one-year base period and six one-year option periods.

Through this contract, GDIT will support the Guard and other federal government partners to upgrade and build new enterprise IT environments that support mission needs. GDIT will provide integrated IT services, including standing up new operations centers, workforce support, technology provisioning and on‑site services. The company will also operate, modernize, integrate and defend the Guard’s classified and unclassified networks, further strengthening its cyber posture. In addition, GDIT will apply advanced artificial intelligence, data analytics and communication capabilities to enhance mission execution. Together, these capabilities will create a more agile and resilient enterprise environment – streamlining operations, enabling faster access to IT services, improving security and elevating service quality for the Guard and its partners.

“The Army National Guard depends on resilient, modern networks to support communities and government partners and safeguard the nation,” said Brian Sheridan, GDIT senior vice president for Defense. “We look forward to bringing the full strength of GDIT’s digital modernization, AI and cyber capabilities to enhance the mission readiness of the Guard and its partners.”

The award builds on GDIT’s partnership with the Army National Guard and a broad portfolio of Army-wide support, including delivering enterprise mission IT services for U.S. Army Europe, global integrated base defense sustainment support, flight school training and mission training complex support.

GDIT is a business unit of General Dynamics, a global aerospace and defense company that offers a broad portfolio of products and services in business aviation; ship construction and repair; land combat vehicles, weapons systems and munitions; and technology products and services. General Dynamics employs more than 120,000 people worldwide and generated $52.6 billion in revenue in 2025. More information about General Dynamics Information Technology is available at www.gdit.com. More information about General Dynamics is available at www.gd.com.

General Dynamics announced today that Paul Nedzbala, who currently serves as senior vice president and chief business officer at GDIT, has been appointed acting president of GDIT. Nedzbala joined GDIT in 2018 when it acquired CSRA, where he served for 19 years in a variety of roles, including executive vice president.

“Paul is a proven leader who brings decades of experience in federal IT services,” said Phebe Novakovic, chairman and chief executive officer. “We are grateful for his willingness to serve in an interim capacity until a new GDIT president is named.”

Amy Gilliland, who joined General Dynamics in 2005 and has served as president of GDIT since 2017, is no longer with the company.

“We thank Amy for her contributions to our company and wish her all the best in her future endeavors,” said Novakovic.

RESTON, Virginia -- General Dynamics (NYSE:GD) announced today that its board of directors has elected Danny Deep, who currently serves as president of the company, to be CEO, effective January 1, 2027. Deep will succeed Phebe Novakovic, who will transition to executive chairman after serving as CEO since 2013.

“Danny is a highly skilled executive with rich operating experience. It has been a pleasure working closely with him and I am certain he will be an outstanding CEO,” said Novakovic. “I very much look forward to our continuing collaboration.”

“On behalf of the board, we thank Phebe for her outstanding leadership and lasting contributions to General Dynamics,” said Laura J. Schumacher, independent lead director. “Phebe has led with vision, integrity and a deep commitment to our people and our Ethos. We have greatly benefitted from her efforts in setting a clear strategic vision, creating enduring value and in building a strong and capable leadership team.”

“We look forward to her continuing role with the company and to working together with Danny,” said Schumacher. “We have every confidence that he will continue the outstanding leadership and legacy that Phebe has exemplified.”

“Phebe has been an extraordinary leader for General Dynamics, and I am grateful for the close partnership we’ve shared and the opportunity to continue working together in the future,” said Deep. “I am profoundly honored to be selected as the next CEO of General Dynamics and humbled and deeply thankful for the board’s confidence.”

Deep has been with the company for 25 years, serving in positions of increasing responsibility. Before becoming president of the company in 2025, he served as executive vice president of Global Operations, executive vice president of Combat Systems, and president of Land Systems.

Headquartered in Reston, Virginia, General Dynamics is a global aerospace and defense company that offers a broad portfolio of products and services in business aviation; ship construction and repair; land combat vehicles, weapon systems and munitions; and technology products and services. General Dynamics employs more than 120,000 people worldwide and generated $52.6 billion in revenue in 2025. More information is available at www.gd.com.

Quick summary: Customer success and sales lose expansion revenue when they define the same moments differently, and writing down five shared terms gives both teams one language for who owns what and when to act.

Customer success flags an account as expansion-ready. The sales team never follows up because they were waiting for a different cue.

Scenarios like this play out every day inside revenue organizations. Customer success and sales often share goals, collaborate regularly, and even report on many of the same accounts. Yet they often use different definitions for four moments in the customer lifecycle: expansion-ready, renewal risk, ownership, and commercial opportunity. When those terms mean different things to each team, handoffs slow down, opportunities stall, and the customer experience grows inconsistent.

A shared revenue strategy requires a shared revenue dictionary.

The challenge of unclear boundaries.

In our annual CSM Confidential Report, we asked CSMs to name their single biggest challenge in commercial conversations. The most common answer, given by 24% of respondents, was unclear boundaries between CS and sales teams.

As customer success has taken on a larger commercial role, many organizations have expanded responsibilities without establishing a common framework for how the two teams should work together. Questions that should already have clear answers often get decided account by account.

Who owns what? What does an account look like when it’s ready to expand? How will the handoff work? Who’s going to handle the outreach? How should renewal risk change ownership?

Without shared definitions and answers to those questions, your teams develop their own interpretations. A shared revenue dictionary creates consistency.

Start your revenue dictionary with these five entries.

Expansion-ready account

- Where the definition differs: CS often marks an account as ready by looking at usage depth and stakeholder engagement, while sales is more likely to wait until a budget cycle ends or the customer shows clear intent to buy.

- The shared definition: An expansion-ready account has demonstrated sustained value from the product, needs more seats or features, has shared positive feedback, and has a confirmed commercial window for a buying conversation.

- What a shared definition changes: CS sends sales opportunities that they can act on immediately. Sales gains confidence in the opportunities that CS recommends.

Expansion trigger

- Where the definition differs: CS may view increased product usage as enough to start an expansion conversation, while sales waits for an explicit request from the customer.

- The shared definition: An expansion trigger is a predefined event, customer behavior, or combination of the two that both teams recognize as the appropriate moment to begin active commercial outreach.

- What a shared definition changes: Expansion conversations happen at the right time instead of getting delayed, because both teams are watching for the same thing.

Renewal-risk account

- Where the definition differs: CS often identifies risk when a customer shows signs of disengagement or a shift in sentiment. Sales may not recognize that there’s a renewal issue until it affects forecasting.

- The shared definition: A renewal-risk account is one that meets defined risk criteria, such as declining usage, negative sentiment or executive or sponsor turnover. Each one raises the likelihood of downsizing, delaying or not renewing.

- What a shared definition changes: Both sales and CS see risk early enough to coordinate a response and save the account from churn.

Ownership trigger

- Where the definition differs: Without a defined trigger, ownership is negotiated case-by-case, sometimes even mid-conversation with the customer.

- The shared definition: An ownership trigger is a predetermined, documented event that transfers responsibility for a post-sale revenue opportunity from one team to another.

- What a shared definition changes: With a RACI framework documented, ownership is clear. But the handoff itself matters, too. When CS brings sales into a growth conversation, the customer shouldn’t feel passed from one team to another. Sales should have the context it needs to pick up the conversation naturally, so the customer never repeats themselves and the opportunity stays intact.

Rules of engagement

- Where the definition differs: Left undocumented, sales and CS build their own informal expectations for how to work together, which amounts to no standard, fewer post-sale expansions, and an inconsistent customer experience.

- The shared definition: A documented framework that defines who identifies, qualifies, owns, and closes opportunities, when responsibility changes hands, what customer context gets passed between teams and how credit gets assigned across the revenue organization.

- What a shared definition changes: Sales and CS operate from the same revenue playbook, making collaboration on every account.

Agreeing on shared definitions is only the first step. Applying them consistently across every account requires visibility into customer behavior and the ability to catch those moments as they happen. With ChurnZero’s AI agents, CS and sales see the same expansion opening and the same renewal risk at the same moment, with account context already attached. Outreach goes out once, from whoever owns it. When CS and sales carry that context forward, the growth conversation continues instead of restarting. A shared revenue dictionary gives both teams the same language, but strong collaboration puts that language into practice. Write the definitions down this quarter, and the next expansion conversation starts with both teams already agreeing.

This is a guest post by Marley Wagner, head of customer success programs and strategy at EverHealth.

Quick summary: Your customers can log in every day and still fail to get what they bought. Score them across five dimensions instead: adoption, business outcomes, relationships, sentiment and support health.

One of the biggest misconceptions about health scores is that they’re designed to measure a customer’s activity when they should be designed to measure a customer’s success. A customer who logs in every day, attends every training session and opens every email isn’t necessarily healthy. Healthy customers are the ones who are achieving what they purchased your product to do. Effective health scores should combine inputs across multiple dimensions rather than relying on one category of data.

Think about health through the following five lenses. The right mix will likely vary based on industry, company size, maturity and how long the customer has been using your product. And while your health score doesn’t need to include every bullet, it can get you into the right mindset so you can narrow it down to what matters most in your environment.

Product adoption

Focus on:

- Are customers using the features that matter most to what they’re trying to accomplish?

- Have they adopted the workflows tied to business value as they define it?

- How quickly did they reach that value? (This might not be the same as how you internally measure time to value.

Whether customers use the standard, newest or most popular features matters less because that functionality may not apply to their goals.

Business outcomes

Focus on:

- Have they reached the success milestones established during onboarding?

- Are they seeing measurable return on investment (ROI)?

- Are they making progress toward the objectives they set when they started?

Following your process in a standard way isn’t required for success; CSMs should flag deviations as a trigger for outreach, but a different route doesn’t automatically mean a customer is at risk.

Relationships

Focus on:

- Are key stakeholders, including the executive sponsor, participating in strategic conversations?

- Do you have relationships beyond a single champion?

- Have there been any recent changes or departures among key contacts?

Having a quarterly business review (QBR) won’t tell you much on its own. Even if the right stakeholders attend, they need to engage for you to assess the relationship.

Customer sentiment

Focus on:

- What is the CSM hearing in conversations?

- How do executive stakeholders feel about the partnership?

- Are renewal conversations becoming more positive or more cautious?

CSAT captures a single moment, so it rarely gives a full picture. And by the time a bad NPS score comes in, it’s often too late to act.

Support and operational health

Focus on:

- Is onboarding progressing as expected and as mutually agreed upon?

- Are issues being resolved quickly and effectively if and when they arise?

- Are recurring problems preventing customers from realizing value?

Comparing ticket volume between churned and renewed accounts can sometimes reveal meaningful patterns, but the number itself matters less than how the tickets were resolved.

Quick summary: NRR and GRR run on the renewal cycle, so you won’t see your first 90 days in them. Marley Wagner offers four leading indicators you can move sooner: time to first value, product adoption, execution velocity and movement in renewal risk.

New customer success leaders often put a lot of pressure on themselves in the first few months. Within a short time, you expect to learn the product, lead a new team, and show impact to prove yourself as a worthy addition to the company. During a recent ChurnZero webinar, Marley Wagner, Head of Customer Success Programs and Strategy at EverHealth, walked through a 30-60-90 day framework for new customer success leaders. One of her recommendations is to be deliberate in what you measure.

Check net revenue retention (NRR) and gross revenue retention (GRR) for early signs of progress and you won’t find much. Those numbers likely won’t move because they are tied to a full renewal cycle. You rarely see day-one changes in those metrics within 90 days.

Leading indicators work differently. They show whether your changes are working before the revenue number catches up. Marley suggests four helpful metrics to watch in the first 90 days.

Metric #1: Time to first value.

Tweak the onboarding process and this one can move quickly, Marley says. She likes it because it shows whether customers are getting to use the product the way they want. Finishing the steps in an onboarding flow doesn’t say much by itself. What matters is whether that happens faster than it did before. Because time-to-first-value can move inside a single quarter, it’s one of the earliest signs that what you’re doing is working.

Metric #2: Feature and product adoption.

Product adoption can also be an early indicator of progress. For example, a feature could have launched or updated before you arrived but customers have yet to use it effectively or at all. Adding a slide about that feature to QBR and check-in decks, or adding some training, can be enough to move adoption.

Usage alone doesn’t prove a customer is getting value from the product. But it’s still one of the better leading indicators because it shows what customers are using. You’ll have to find out later if that usage pays off for the customer.

Metric #3: Execution velocity.

Execution velocity measures the team’s output, whether CSMs are able to effectively use their time to execute on their objectives. That could mean more strategic meetings and fewer status updates because a manual task finally got removed from their plate.

You might move certain tasks from CSMs to the support team. Other ways are automating data collection that used to live in a spreadsheet or building a deck template so team members don’t have to rebuild the same presentation from scratch every quarter. Any of these free up hours CSMs can spend protecting the account instead of doing admin work, and it’s one of the easiest wins to show early.

Metric #4: Movement in renewal risk.

Movement in renewal risk tracks how early a CS team can flag accounts that are unlikely to renew, rather than finding out at the last minute. It’s the hardest of the four to see this early, but it’s possible, according to Marley. A common pattern shows up across CS teams that can jeopardize renewals. CSMs will wait for the customer to bring up the renewal instead of raising it themselves, out of habit or nerves.

Coach the team to start that conversation six months out. Leaders get a more accurate read on which accounts are at risk, and CSMs get runway to act long before the renewal date. Addressing the renewal early gives the best accuracy in predicting retention or churn before NRR or GRR would be able to show it.

Build your own list.

These four metrics aren’t the only options. Every business needs its own metrics that are tied to a product or a specific problem a new leader was hired to solve. Use this list as a starting point, then build one that fits your business.

Watching a metric that’s already moving is a better use of the first 90 days than staring at one that hasn’t caught up yet. NRR and GRR will get there but they’re just not the first thing to check.

Quick summary: SaaS companies face pressure to accelerate customer onboarding, but it’s important to balance automation with a personalized experience. Keeping AI behind the scenes and automating strategically helps teams work more efficiently while delivering value to the customer.

SaaS businesses have a lot of incentive to streamline and automate their customer onboarding. Many companies are shifting to a consumption-based pricing model where they invoice their clients based on how much they use the platform – which means SaaS providers are financially motivated to get customers onto their platform faster.

But at the same time, customers expect personalized service that addresses their specific needs. And if you rush to automate your whole onboarding process, you risk missing important details that separate a finished onboarding from one that actually delivers value.

As the VP of Customer Experience Delivery at ChurnZero, I spend a lot of time thinking about how to streamline the customer experience without sacrificing the personal touch that makes a big difference for our clients. Let’s get into the risks of automating, along with ways to strategically improve your customer onboarding without fumbling your first impression.

The risks of automating customer onboarding.

There are some trade-offs that happen when you automate onboarding tasks that human beings used to do:

- Business context: B2B implementations require a lot of contextual information about how the customer wants to use the software. Generic AI tools often lack the ability to process these details and see the big picture.

- Repeatability: B2B implementations have stages and steps that repeat, but the way each customer gets there almost never does. Their internal processes, their data structure, and the way their accounts and contacts are organized all feed into the build, and none of it looks the same twice. Outside of the repeatable parts, it’s kind of the Wild West, and that’s where automation struggles.

- Performance measurement: Automation is supposed to enable teams to work faster. But time spent onboarding is only one piece of the puzzle, and businesses should be tracking other metrics that predict a customer’s long-term success.

How to automate onboarding while delivering value to the customer.

Onboarding teams can roll out automation tools to work more efficiently without sacrificing the customer experience. It just requires some strategic planning around where and how to automate:

Define success by more than just time-to-value.

Onboarding teams want to move faster because it frees up resources and helps the bottom line. But strict timelines (like a mandatory 45-day, 60-day, or 90-day setup) put the focus on the date instead of on what the customer can actually do when you’re finished.

In the B2B world, timing is a dangerous primary indicator. It matters to me as a leader for staffing and capacity, but we very rarely talk about it with customers beyond setting goals and making sure we’re aligned on what they want to do. Instead of just focusing on how fast you get through onboarding, you should measure if the onboarding actually delivered value and set your customer up for success:

- Customer satisfaction scores: Conducting surveys at key points of the journey can help you determine your customer’s satisfaction and find areas for improvement.

- Use case deployment: Confirm if your customers are using your product for the specific use cases they presented during the onboarding process.

- Adoption of what you built: Are customers actually using the configurations you built for them during implementation? When they aren’t, there’s sometimes a good reason, like priorities or processes changing. Dig in and find out why.

Maintain a personal connection.

SaaS implementations require many touch points with the customer. At ChurnZero, we’re dealing with customer experience professionals all day, every day, so their bar is higher. They know the game and they know what we’re trying to do, which means we have to be really good at it. We’ve been deliberate about not asking customers to interact with AI tools in place of those conversations, and about not losing the context those conversations give us.

The implementation process involves highly complex information. We build a lot of AI into our own platform, and we use all of it. The tooling on the market for running an implementation team is a different story: most of what I’ve demoed is designed for B2C, so in the B2B world it either does too little to be worth the effort or takes so much customization that you’re better off with your own approach. That’s changing fast, and a couple of tools are starting to look interesting. In the meantime, you can roll out automation strategically behind the scenes to maintain a personal connection and control over the onboarding:

- Automate manual tasks. One of the best uses for AI is automating administrative and repetitive tasks like data collection and data entry, turning whatever process documentation a customer sends over into a starting point for their configuration, and the low-value setup work your team repeats on every build.

- Maintain human understanding: Human beings are still better at understanding customer requirements and providing guidance. While AI can gather information and provide advice behind the scenes, the onboarding team should be front-and-center making recommendations to the customer.

- Avoid AI on top of AI: Every stage of the customer journey has a meaningful amount of AI in it now. Sales uses it to summarize meetings and pull pipeline information, the SDR team runs AI outbound, and by the time any of that reaches your onboarding team, the inputs you’re analyzing were themselves generated by another AI tool. Each layer takes you one step further from reality because you’re looking at a summary of a summary.

Use onboarding to drive future customer value.

You can also drive value in the future by positioning the onboarding journey as the first step in an ongoing relationship with your customer. During onboarding, you can set your customer up for long-term success, which is what keeps the renewal conversation from being a battle.

Take the information gathered during onboarding, like the use cases they came to you for and the goals they set, and carry it into the business reviews your CSMs run. Three months in, you can look at what the metrics say, whether they’ve reached those goals, and what needs adjusting as you iterate.

Ideally, you can show that you had a plan in place from day one. And your customer success teams can look back at the customer’s journey and say, “Here’s what we accomplished.”

Experiment with limited customer groups.

Keep in mind, you don’t have to use automation to overhaul every aspect of the onboarding process right out of the gate. Onboarding teams can test new workflows or automate certain processes with a limited group of customers. Successful tests can be expanded, while unsuccessful tests can be abandoned or tweaked and re-tested.

Don’t feel like you have to fully commit to any approach. At ChurnZero, we like to try little experiments with a small number of customers to see how it goes. In my mind, there’s no bad experiment because every test teaches you something.

Customer onboarding should enable customer success.

As SaaS companies update their pricing models and manage client expectations, they should build an onboarding process that blends automation with personalized customer service. Relying on rigid implementation timelines puts the focus on a date instead of on what the customer can actually do with your product. And when you put AI front and center, you lose the context that makes an implementation work.

Keeping AI behind the scenes to handle repetitive tasks frees your onboarding team to work more strategically and handle personal interactions with customers. Measuring the value you bring, looking for opportunities to drive future renewals and experimenting with automated tasks can help onboarding teams work more efficiently but still set their customers up for long-term success.