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Announcing Sixfold’s Series A Led By Salesforce Ventures

This $15 million injection of capital will accelerate the journey to a new era of AI-powered decision-making in insurance underwriting.

Announcing Sixfold’s Series A Led By Salesforce Ventures
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Stay informed, gain insights, and elevate your understanding of AI's role in the insurance industry with our comprehensive collection of articles, guides, and more.

We had an opportunity to chat with Sixfold's Co-founder and COO Jane Tran about the company’s amazing first year and the vision for the years to come, as well as her career journey, giving back, and tips on running a fast-paced AI startup.

What was your first job and how did that influence your career?

My very first job ever was as a cashier at an Italian deli around the corner from my parents’ house.

I think everyone should do a service job because it emphasizes the importance of good customer service like how to treat people. I also learned how to be quick because it's New York. New Yorkers don’t like to wait for their Bacon, Egg, and Cheese.

Walk us through your career journey from the Italian deli to co-founder and COO at  Sixfold.

I’ve had a good mix of enterprise and startup experience. I started my career at JP Morgan as part of their rotational analyst program. One of my last rotations was with the Turnaround & Process Improvement team for the Chief Information Officer—that’s where I fell in love with tech. I worked on really cool projects like improving the eDiscovery process and improving data governance. I had a blast. 

After that, I spent several years at Marsh and MetLife working with the CIOs on different strategy and planning projects before I decided to give startups to go. I was on the founding team at Unqork where I was Head of Solutions before becoming COO.

When I decided to leave Unqork, I kept in contact with Alex [Schmelkin, founding team at Unqork, and co-founder of Sixfold]. When he came up with the idea for what would become Sixfold, he asked me to join him to get this idea off the ground.

What does the name Sixfold mean and who came up with it?

So, all kudos due to Alex’s daughter Nina Schmelkin for that! She was doing a project for school around patterns. A sixfold pattern is considered one of the most interesting, naturally occurring patterns—snowflakes are a sixfold pattern. And so, when it came to choosing a name for the company, we were thinking about AI and the role that patterns play, and “Sixfold” seemed like an ideal fit.

Sixfold just turned one year old. How would you describe year one?

A ton of fun! We’re building really tangible use cases using cutting-edge tech. This first year has reinforced the importance of anchoring your work in first principles. AI is obviously super hot and evolving at warp speed, but we can't ignore the things that support great software development and great user experiences. That meant getting that foundation and discipline in place while at the same time making room for extensive R&D and a ton of iterations. 

We learned a lot. We tweaked a bunch. And I think we found product market fit. Our early customers are already starting to see value, and I’m really excited to see where that grows this year.

Do you have any notable “wow” moments from the first year?

Yeah, when we delivered our first end-to-end underwriting pilots and heard the underwriters say “we were able to complete this task in a fifth of the time.” I particularly love hearing how much they trust the tool.

Hearing that first positive user feedback feels like a major achievement! And, obviously, the recent closing of our Series A funding round.

Who are your role models and how did they influence your career? 

My parents. My mom runs a small business in kitchen supplies with her siblings — it was one of those things where they just sort of fell into it. They knew they could offer a really good product and create a fit within the market. They understood what customers wanted and knew that they could manufacture it. So they just went for it. That takes a lot of bravery. On the flip side, my dad hung wallpaper for a living. He's retired now, but he had that hard work ethic and true care for his craft. He developed a reputation for excellence and really worked his way up.

I think the combination of entrepreneurship, work ethic, and quality very much influences who I am.

A common conversation for startups is balancing “the need for speed” with employee happiness. How do you build that balance into the company culture? 

Unfortunately, I don't have a magic formula. I would say that from the get-go, Sixfold’s three founders — Brian, Alex, and myself — anchored ourselves on our Mission and a handful of operating principles like putting the customer first and being direct while being kind. We try to surround ourselves with people who share those principles so that naturally becomes the culture of the company. 

Jane together with Alex Schmelkin (Co-founder & CEO) and Brian Moseley (Co-founder & CTO).

The three of us really care about who works for us and how we all work together. Sometimes we may not have the best balance, but we always strive to be better. As founders, we care a lot about our work, but we also care deeply about family, friends, and life outside work. We understand that people who work with us have the same need for a balanced life outside work.

Do you have any tips when it comes to hiring?

Instinct is a huge part of it. It’s also helpful to have a great HR team in place — kudos to Marie [Sixfold’s HR Business Partner] for doing a lot of the initial groundwork, so by the time a candidate gets to me, they fit a lot of our criteria for that role. From there, a lot of it just comes down to just instinct. Ask yourself if they'll fit within the culture of this company.

Tell us about your mentoring work for different startups and organizations.

I'm on the board of directors and co-chair for an organization called Womankind. It helps survivors of gender-based violence in New York, with a focus on the AAPI community. They've been around for more than 40 years. They started with a single hotline for the NYC area, but have expanded to serve thousands of women every year across the US as one of the few true end-to-end organizations. So families get to stay together. They get legal help. They get job placement. Their kids have a safe place to be while they're figuring out, you know, the next steps. I'm really proud to be part of that organization. 

I've also mentored and advised a few other early-stage startups that I think are doing something new and interesting. This also helps me to understand what else is out there in the ecosystem. I’ve mostly been focused on B2B enterprise throughout my career, so I like learning about retail or other sectors.

I love being around people who are building interesting things. It’s super fun and it can be super informational too.

What are your top work tools that you feel like you couldn’t do without?

I don't do a lot of the things that “productivity hackers” do. I would say Apple Notes and Google Tasks are central to my workday. I keep extensive notes on my meetings— so that’s a lot of Apple notes. And then, for the important things with a deadline, I'll set up a Google task or calendar reminder. And that's how I organize.

What are you excited about for Sixfold’s second year? 

This year will be about continuing to mature our product and getting a lot of new customer use cases live.

We're working with a lot of great people and a lot of great customers. I’m looking forward to showcasing what we can do within this market and at this fidelity — a year ago, I don't think anyone would have thought that we’d be able to do what we’re doing, so I can’t wait to see what the next year or two will bring!

Want to work with Jane and the rest of the Sixfold team? Check out our career page

I’m thrilled to announce that Sixfold has been named a winner of this year’s Zurich Innovation Championship! Since 2018, Zurich Insurance Group has overseen an annual “collaboration program” with select startups from around the world to develop new offers and services for their customers. The yearly Championship has rapidly expanded to become the industry’s largest open innovation contest with thousands of applicants from over 30 countries resulting in more than 50 active initiatives implemented through Zurich Insurance’s global business. 

Celebrated for Pioneering Innovation

Sixfold was only one of nine teams selected out of a pool of more than 3,000 global applicants to take part in the accelerator portion of the Championship. Our team will take on the “Commercial Insurance” challenge to engineer technical solutions that “improve transparency and accountability, enhance risk management capabilities, and foster sustainability transition through a culture of trust and innovation.”

For the next four months, our team will collaborate with leaders from Zurich North America (ZNA) to build AI-powered risk analysis & summarization solutions to augment underwriter workflows through the automation of high-volume (but not necessarily high-value) tasks.

Improving Insurance Efficiencies

Unlike traditional accelerator programs, which focus on product development, the Innovation Championship aims to accelerate the adoption of a new solution within Zurich Insurance’s global business. We’re thankful to the leadership at Zurich Insurance for believing in Sixfold’s mission and our team, and we look forward to building an amazing solution that results in improved efficiencies that benefit Zurich’s customers, insurance brokers, and other stakeholders. 

This collaboration comes only two months after Sixfold’s selection to participate in the 12th cohort of Lloyd’s exclusive accelerator program, Lloyd’s Labs, which kicked off in April and we will be demoing in July. 

We’ve only just begun Sixfold’s second year — and it’s turning out to be a BIG one!

This article was originally posted on Linkedin

We talked with Sixfold’s latest hire, Head of AI/ML Ian P. Cook, PhD about his career journey, how emerging technology will overcome long-standing industry challenges, and his new role as Sixfold’s data science leader.

Welcome to the team, Ian! Walk us through your career journey up to this point.

I caught the bug for quantitative work when I was in grad school studying Public Policy at the University of Chicago. After graduation, I worked in various policy analysis roles, including at the RAND Corporation as well as doing work for all the major defense agencies and other federal orgs.

While doing policy work, I was simultaneously pursuing my PhD at the University of Pittsburgh for Political Science. My trusty “dad joke” is that I wasn’t smart enough to do grad school just once. As part of my research, I taught myself Python and found that my skills in econometrics translated well to the then-exploding field of data science. After I received my degree, I worked with startups and went from building tech products to building tech teams as Chief Data Scientist with a GovTech company and Chief Technical Officer for a business analytics SaaS.

Are there any tech projects you’re particularly proud of?  

One of my favorite projects was a matching & recommendation tool for patients. A significant predictor of poor health outcomes is missing doctor appointments, but as it turns out people don’t just “miss” them, they avoid them when they’re not happy with the style or approach of a doctor or practice. This was a problem that me and my team believed could be engineered around. 

I oversaw the team building the machine learning functionality for a web tool that assessed both patient preferences and the style of healthcare providers and then turned that into a kind of for healthcare. Not only was it fun to build, but I’m particularly proud to know that it helped keep people getting the care they need.

Why Sixfold?

Sixfold immediately piqued my interest. The company is attacking a clear and sizable pain point for a well-defined customer (anyone with startup experience will tell you that’s not always the case). Plus, they’re doing it with what I see as generation-defining tech—LLMs are amazing in their own right, and having the opportunity to put them to practical use is an exciting opportunity. After meeting with the team and the leadership, I knew that this was where I wanted the next step of my career to be. Excited to get to work with an amazing crew—tip of the hat to Stewart, Drew, and the whole engineering team!

Everyone’s talking about LLM-powered generative AI these days. From your perspective, what are the most intriguing possibilities and potential risks of this emerging generation of tech?

I sit somewhere in the middle between the extremes of the AI discourse: I don’t think AI will give rise to a post-human apocalypse, but I also don’t believe we can just sit back and toss every hard problem at an AI and implement whatever solution pops out. 

We’re going to see these tools accelerate transformation across every industry. In most cases, that will ultimately be a good thing. However, without clear intention behind how they’re applied and oversight into how they’re trained and deployed, there’s a real risk for these tools to cause harm—unintentional or otherwise. Part of the attraction to Sixfold was their emphasis on applying AI responsibly.

As someone with a strong data science background, what does it mean for data to be useful, not just accessible?

Access is an aspect of keeping data well-controlled—like security measures and access control for personally identifiable information, health records, financial information, and other sensitive material. 

For data to be useful, it has to address real problems and it has to have been corralled in a thoughtful, purposeful manner. Usefulness requires someone to understand the question the data is meant to help answer and to be aware of potential biases—both statistical and human-generated—which might limit the applicability of the data.

How do you see your role as the AI/ML leader at Sixfold?

I see my chief responsibility as empowering underwriters to do their best work ever by augmenting Sixfold’s product with AI-powered tools. Achieving that means supporting the people who are developing, testing, and deploying those tools. Some days that might mean coordinating priorities and ensuring everyone has the information and resources to deliver. Some days it might mean being chest-deep in the code myself. And some days, I’m sure it’ll be a little of both. 

What do you see as the challenges of implementing AI in insurance vs other industries?

I’ll admit to being relatively new to the insurance industry. That said, even a n00b like myself understands that it comes with unique challenges like complying with regulations across multiple levels of government; implementing stringent processes to handle and distribute the personal, closely-held data of both individuals and corporations; and making a convincing argument for change in a well-established industry where many are content using tools and methods that’ve been around for decades.

As a seasoned technologist, do you think there are types of tasks that will always be better suited for humans, rather than machines? 

AI is going to take on the tasks that slow us down. I like to think of it as a bionic-like tool that augments and improves human performance.

It’ll free us up to focus on the most important—and frankly most meaningful and rewarding—parts of our jobs.

I’ll also add this: the better the machines get, the more we’re going to lean on philosophy, the most thoroughly human of disciplines. Discussions about LLMs are loaded with terms like “reasoning,” “thought,” and “knowledge,” which philosophers have been wrestling with for centuries. I’m reminded of the discourse in my philosophy courses around intention and will, which are completely distinct from the mechanistic processes in deep learning architectures. Philosophy is often derided as a field with little practicality, but as a technologist, I see it becoming more practical by the day.

How do you keep up with the latest developments in your field?

A lot of reading! There are tons of great newsletters that cover the field. Ben’s Bites is fantastic, but there are tons of great ones across Medium, Substack, and Beehiiv. I’m also a fan of podcasts like AI Daily Brief, The Cognitive Revolution, and Talking Machines. I like listening to those while doing chores, walking my dog, driving, etc. 

Keeping up with the latest research is always a challenge—it was an issue even back in my PhD days because there were always new papers coming out. Part of me feels lucky to have gone through that back then because now AI is moving at warp speed and it’s even harder to keep up. But I’ve learned to master the art of “informed skimming,” which means quickly reviewing summaries, conclusions, and writeups to find key terms that will tell you if the paper is relevant to the problem area you’re taking on.

What tools do you rely on the most for your work?

I’m a devoted fan of Pycharm for coding. I’ve tried switching to VS Code and other flashy new IDEs when they come up, but I always go back to Pycharm. For note-taking, I stick to Apple Notes. There’s a whole world of “second brain”/knowledge management tools out there for taking notes, but I have to refrain from those (anyone familiar with the word “Zettelkasten” knows the depths of that particular rabbit hole).

I learned during grad school that the more extensible a tool is, the more time I waste fiddling with configurations. Tweaking color themes is not “optimizing my workflow,” no matter how many times I repeat it to myself.

What is the best thing a person can do who wants to pursue a career in AI/ML?

Some requirements are hard to skip over: a decent amount of math, and enough knowledge to turn that math into code.

But you don’t have to be a genius at either one. Learn some matrix math, and then play with those matrices and see how you can apply them in predictive software. Then learn a little more, and implement a little more. The key to mastering any skill set is repetition and perseverance. To parrot that old quote about how one becomes a writer: write.

More specifically, I think there are three things everyone who wants to work in this field needs to know: SQL, Git, and enough of one programming language to be productive. SQL is the language of data: getting it, moving it, storing it, everything—if you can’t get at the data, it’s going to be hard to trust that you can work with it. Git proves that you understand versioning, reproducibility, and collaboration. When it comes to becoming thoroughly fluent in at least one programming language, I’ll sidestep the religious wars about which language is best or most useful and just say that the important thing is becoming really productive in at least one language.

Any fun tech projects that you're working on at the moment (non-Sixfold-related)?

I’m a fly fisher in my spare time, and I use a fly fishing app called onWater Fish. I reached out to the app’s dev team and learned they needed some ML-like support. So I pitched in to try out some new ideas. We’ve been successful in implementing some cool in-app computer vision work that anglers can use to record their catches (and brag to friends) all with one picture. It’s been a great way to apply my skills to a personal passion of mine, which has been truly rewarding. 

How can people follow your work?

I’m on LinkedIn, and try to post regularly on the practical application of AI, the future of work, and whatever else where I might have a useful take. For other social media, I can usually be found by searching @ianpcook.

Want to join Ian and the rest of the Sixfold team on our mission to transform insurance underwriting with AI? Check out our career page

Last month, the European Parliament passed the EU Artificial Intelligence Act, a sweeping regulatory framework scheduled to go into effect in 2025.

The Act categorizes AI systems into four risk tiers—Unacceptable, High, Limited, and Minimal—based on the sensitivity of the data the systems handle and the crucialness of the use case.

It specifically carves out guidelines for AI in insurance, placing “AI systems intended to be used for risk assessment and pricing in [...] life and health insurance” in the “High-risk” tier, which means they must continually satisfy specific conditions around security, transparency, auditability, and human oversight. 

The Act’s passage is reflective of an emerging acknowledgment that AI must be paired with rules guiding its impact and development—and it's far from just an EU thing. Last week, the UK and the US signed a first-of-its-kind bilateral agreement to develop “robust” methods for evaluating the safety of AI tools and the systems that underpin them. 

I fully expect to see additional frameworks following the EU, UK, and US’s lead, particularly within vital sectors such as life insurance. Safety, governance, and transparency are no longer lofty, optional aspirations for AI providers, they are inherent—and increasingly enforceable—facets of the emerging business landscape.

Please be skeptical of your tech vendors

When a carrier integrates a vendor into their tech stack, they’re outsourcing a certain amount of risk management to that vendor. That’s no small responsibility and one we at Sixfold take very seriously. 

We’ve taken on the continuous work of keeping our technology compliant with evolving rules and expectations, so you don’t have to. That message, I’ve found, doesn’t always land immediately. Tech leaders have an inherent “filter” for vendor claims that is appropriate and understandable (I too have years of experience overseeing sprawling enterprise tech stacks and attempting to separate marketing from “the meat”). We expect—indeed, we want—customers to question our claims and check our work. As my co-founder and COO Jane Tran put it during a panel discussion at ITI EU 2024:

“As a carrier, you should be skeptical towards new technology solutions. Our work as a vendor is to make you confident that we have thought about all the risks for you already.” 

Today, confidence-building has extended to ensuring customers and partners that our platform complies with emerging AI rules around the world—including ones that are still being written.

Balancing AI underwriting and transparency 

When we launched last year, there was lots of buzz about the potential of AI, along with lots of talk about its potential downside. We didn’t need to hire pricey consultants to know that AI regulations would be coming soon. 

Early on, we actively engaged with US regulators to understand their thinking and offer our insights to them as AI experts. From these conversations, we learned that the chief issue was the scaling out of bias and the impact of AI hallucinations on consequential decisions.

Sixfold CEO Alex Schmelkin (right) joined a panel discussion about AI in underwriting at the National Association of Insurance Commissioners (NAIC)’s national meeting in Seattle, WA.

With these concerns in mind, we proactively designed our platform with baked-in transparency to mitigate the influence of human bias, while also installing mechanisms to eliminate hallucinations and elevate privacy. Each Sixfold customer operates within an isolated, single-tenant environment, and end-user data is never persisted in the LLM-powered Gen AI layer so information remains protected and secure. We were implementing enterprise AI guardrails before it was cool.

I’ve often found customers and prospects are surprised when I share with them how prepared our platform is for the evolving patchwork of global AI regulations. I’m not sure what their conversations with other companies are like, but I sense the relief when they learn how Sixfold was built from the get-go to comply with the new way of things–even before they were a thing.

I’m beyond excited to announce that Sixfold has been officially selected to take part in the 12th cohort of Lloyd’s InsurTech accelerator program, Lloyd’s Lab. 

Lloyd’s Lab was recently recognized as a top-25 European start-up hub by the Financial Times and Statista and ranked the very top insurance-focused accelerator out of 19 countries and +2,000 organizations.

The program will give our team the opportunity to collaborate with Lloyd’s mentors to develop innovative solutions for the world’s leading insurance and reinsurance marketplace. Over the course of the 10-week “fast-track, fast fail” program kicking off in late April, our team will build, test, and iterate innovative solutions that “challenge how we do things and help the Lloyd’s market better serve its customers.”

Sixfold was one of just 22 insurtechs invited to travel to London to take part in Lloyd’s pitch day event.

Sixfold was one of just 22 insurtechs invited to travel to London to take part in Lloyd’s “Pitch Day” event. This year saw the largest-ever application pool for the program—Pitch Day invitees had to be culled down from more than 250 applications submitted by insurtechs spanning 33 different counties. 

For our pitch, I showcased how much we have built to serve underwriters in the past 10 months to 1,000-plus virtual and in-person attendees from across the Lloyd’s market ecosystem. We were selected into the program as one of only 12 teams by a panel of market leaders, mentors, and the Lab team, and we were the only underwriting solution to be accepted into the program! 

Members of Sixfold’s product and design teams will spend 10 weeks working out of the iconic Lloyd’s building in London. We will focus our efforts on accelerating and optimizing triage and risk appetite match capabilities within the scale of Lloyd’s markets. 

We’ll demo the fruits of our accelerator labor to the entire Lloyd’s market in early July—stay tuned for details!

Lloyd’s Lab unique approach to fostering global innovation is helping to tackle some of the world’s biggest insurance challenges. Progressing the Lab’s mission of supporting innovative insurance solutions across the globe, this latest cohort focuses on developing solutions to some of the biggest risks faced by businesses and communities in the Americas such as challenges arising from natural hazard prediction to risks associated with cybersecurity.

Thank you to Lloyd’s for believing in our vision and helping us bring it to fruition. We can’t wait to show the entire Lloyd’s market—and the rest of the world—what we have in store.

This article was originally posted on Linkedin

Today, life & disability carriers have access to more data from more data sources than ever, but the processing of all that data has paradoxically decreased efficiency and limited underwriting capacity. The industry has wisely turned to gen AI to help it reap the rewards of the modern data abundance while minimizing the cost.

In our view, gen-AI-powered underwriting isn’t about conversing with chatbots, it’s about collaborating with a platform that understands exactly what you need and exactly how to get it. But how should a platform like that function? What would it even look like? We started the process of answering those questions by interviewing dozens of underwriters to understand their frustrations, goals, and how other tools have failed them in the past. This input has guided our approach to design built around simplicity, context, trust, and fun


Many L&D carriers rely on automated extraction tools and/or offshore teams for their data-processing needs. These result in long multi-page reports, which are typically just ordered lists of data. Underwriters are left to rifle through these tomes to pull out relevant info. Sixfold eliminates these overly manual tasks by injecting AI throughout the underwriting process.

We use cutting-edge AI to independently build a virtual model of carriers’ unique risk appetites, so the platform can understand what constitutes negative or positive risk signals for that carrier. The platform taps a different set of purpose-built AI models to process ingested data and gracefully surface precisely what information underwriters need — and nothing else.

How does this AI wonder translate into design? We’ve leaned hard into “inconspicuously helpful.” The best AI is one that doesn’t make a show of itself, but can be depended upon to solve problems when called into action. More old-school British butler, and less Robin Williams’ genie from Aladdin. From a design perspective, that means elevating minimalism and simplicity.

Underwriters never see the AI hard at work ingesting data from disparate sources (APS files, MIB reports, labs, etc.). And they shouldn’t have to. All they want to see are easily scannable bits of appetite-aligned information in a unified dashboard experience. Leave the sausage-making to us, enjoy your hotdog.

Our design emphasizes minimalism and simplicity, making sure underwriters get a straightforward and brief overview of a case at the first glance.

This effortless minimalism extends to every part of the platform. On the case list page, underwriters can peruse a list of applicants with clear visual cues signifying which cases are closely aligned with underwriting criteria and which aren’t. In a previous technological era, underwriters had to invest time in scrutinizing each and every applicant with limited ability to triage, leading to reduced productivity. With Sixfold, they can focus their efforts on the biggest impact.

Underwriters can peruse a list of applicants with clear visual cues signifying which cases are closely aligned with underwriting criteria and which aren’t.


Traditional data processing & ingestion treats all information equally. Taking a daily multivitamin is, for example, given with the same “weight” as immunosuppressants taken after an organ transplant. “Flattened” data reports, no matter how thorough, require underwriter intermediation to pick out the relevant through lines. 

We can do better in 2024.

Sixfold taps a medley of nine AI models to identify relevant data points from disparate sources and “connect the dots” between them. It’s the difference between, say, mentioning an applicant has diabetes versus summarizing how it’s being managed, e.g., “applicant was diagnosed with diabetes in 2015, but it is being adequately managed through diet and insulin.”

We haven’t merely replaced one form of summarization with an AI-powered one. We use gen AI prudently and solely in service of accelerating decision-making. Our goal is to present underwriters with as little information as possible (or, rather, just the right information) so they can focus their energies on making informed decisions. 

Concise auto-generated explanations are placed front and center, but underwriters can always dive deeper into specific information as needed (e.g., the platform may let you know that recent cholesterol readings were acceptable, but you have the option to dive into the readings from the last few labs).

Our goal is to present underwriters with as little information as possible (or, rather, just the right information) so they can focus on making informed decisions.


The best underwriters are detail-oriented, and they deserve tools that meet (or better yet, exceed) their standards of thoroughness. Underwriters using Sixfold should be confident that everything has been scrutinized as thoroughly as if they did it themselves—if not more!

We accomplish this by showing our work. Transparency is baked into the Sixfold UX. We provide sourcing of all surfaced risk factors and conclusions, right down to the source and page so underwriters know precisely where a conclusion came from, and why it was arrived at.

And a little bit of fun

We want engagements with our platform to feel like working with your favorite coworker. You know the one we’re talking about right? The one that gets things done, but throws in a little light-hearted banter and joking around to improve your day just a bit.

Going through medical records isn’t what most people consider enjoyable. So we injected some moments of surprise and delight that can bring the joy back to underwriting. Our platform includes small flourishes that we hope provide a little levity.

Across the site, we’ve included illustrations of friendly robots collaborating with humans and empowering the humans to do more.

Throughout the site, we’ve included illustrations of friendly robots collaborating with humans and empowering the humans to do more. The overriding theme of this aesthetic? Clay. Why clay? It feels deeply human, handmade with little imperfections that add character. We believe that AI can liberate humans from rote work (which is better handled by machines anyway) so they can emphasize their uniquely human qualities. The machines aren’t going to take over our jobs – they’re going to free us to bring humanity back to the work we do.

Want to see the platform in action? Watch our on-demand product demo for a live walkthrough of Sixfold’s Life & Disability offerings.

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