An Interview With Chad Silverstein
Streamlining Patent Research: Patlytics is reinventing the patent landscape, an industry that’s historically relied on fragmented and outdated tools. By using AI to analyze patent data, litigation history, draft claim charts, and examiner behavior, the team is creating a unified, intelligent workflow for patents.
In today’s tech-driven world, artificial intelligence has become a key enabler of business success. But the question remains — how can businesses effectively harness AI to address their unique challenges while staying true to ethical principles? To explore this topic further, we are interviewing Chris Fisher.
Chris Fisher is the Founder and Managing Partner of Myriad Venture Partners. Prior to Myriad, Chris was the Founder and Managing Partner of Xerox Ventures and the Senior Vice President and Chief Strategy Officer of Xerox Corporation. Chris was also a member of Xerox’s Executive Committee and responsible for global M&A, Strategy and Ventures. Chris began his professional career with over a decade of experience in banking and big law.
Thank you so much for joining us in this interview series. Before we dive into our discussion, our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path in AI?
My career path has largely been defined by solving complex business issues for large corporations as an operator, or on behalf of large corporations and institutional investors in complex transactions. AI offers a tremendous opportunity to drive efficiencies across every aspect of business, including solving complex problems in a faster and more economical way.
Can you share the most interesting story that happened to you since you started working with artificial intelligence?
One of the most rewarding parts of venture capital is when a long-standing thesis finally clicks into place with the right founder and solution. It can often take a very long time, having to speak with dozens and dozens of startups until you find the one that feels just right. But when you do, you almost know instantly.
For years, we’d been exploring the patent space, believing AI could unlock a more dynamic and accessible way to navigate the complex patent landscape. We talked to dozens of companies, but none truly aligned with our vision until we met Paul and Arthur at Patlytics. From the first conversation, there was instant alignment. They not only understood the technical landscape but also the broader market needs and the nuances in delivering real value.
That was a great moment for us. Not only did we find an incredible founding team, but we also found what we believe is the best solution — and team — to solve a problem we had been chasing an answer to for years.
Let’s jump to the primary focus of our interview. Can you share a specific example of how you or your organization used AI to solve a major business challenge? What was the problem, and how did AI help address it?
Rather than diving into how Myriad specifically uses AI, I think it’s more interesting to talk about a broader trend we’re seeing: the rapid adoption of AI by businesses, both big and small. Today, enterprises are more willing than ever to partner with early-stage AI startups to tackle critical pain points.
At Myriad, we’re fortunate to have a deep corporate network that helps exceptional founders and innovative startups navigate this opportunity. Thanks to our corporate network, we’re often able to help early-stage startups land their first significant enterprise relationship with a Fortune 1000 company. These intros are not just about accelerating growth and fine-tuning product roadmap and development, though that’s obviously key. It’s also a sign of how eager large businesses are to engage with emerging AI companies.
Across industries, AI is helping businesses structure what was previously unstructured and provide real-time insights that drive smarter decision-making. It’s streamlining processes across departments like legal, HR, and supply chain, and directly contributing to higher revenue, better customer retention, and more opportunities for go-to-market teams to grow their businesses.
What are some of the common misconceptions you’ve encountered about using AI in business? How do you address those misconceptions?
One of the most persistent misconceptions is that AI is either too complex to implement or only suitable for large tech-forward companies. The truth is, we’re seeing meaningful applications of AI across a wide range of industries, from logistics and manufacturing to legal and HR. AI isn’t just replacing humans, but serves as a force multiplier, enhancing decision-making, streamlining repetitive tasks, and opening up new opportunities for innovation, including more meaningful and impactful work from employees leveraging AI.
Our portfolio is demonstrating this wide-reaching potential. Companies like Wexler are transforming legal fact analysis by automating the extraction, verification, and analysis of case facts. This enables legal teams to more efficiently build stronger case strategies. For instance, Wexler’s AI Agent assists in dispute resolution by providing fast, fact-based insights, making the litigation process faster than ever before. Meanwhile, Cascade AI is transforming enterprise HR departments by turning static data into actionable insights, allowing smaller HR teams to operate like larger ones. The misconception that AI is only for tech giants misses the innovation happening in these targeted, highly specialized applications.
In our enterprise network, we’re seeing organizations that succeed with enterprise AI tend to take a task-centric approach, breaking operations into core units of work to identify where AI can add the most value. Achieving true, scalable adoption demands not just robust infrastructure, but also a clear strategy for targeting common, adaptable tasks — combined with a commitment to rethinking processes and orchestrating change across the entire enterprise.
In your opinion, what is the most significant way AI can make a positive impact on businesses today?
AI’s most significant impact today lies in its ability to unlock previously inaccessible insights from messy, unstructured data, and to do so at unparalleled speed and scale. Whether the technology is driving revenue, saving costs, or unlocking operational value depends on the use case.
AI will play a key driving force for industrial digital transformation, automating manual workflows and unlocking insights from unstructured or previously untapped data. This enables smarter, faster decision-making and more efficient, resilient operations across physical industries like manufacturing, supply chain, and healthcare.
Based on your experience and research, can you please share “5 Ways AI Can Solve Complex Business Problems”? These can be strategies, insights, or tools that companies can use to make the most of AI in addressing their challenges.
Sure, here are five practical ways we’ve seen AI tackle tough problems, with real-world examples from the Myriad portfolio:
- Streamlining Patent Research: Patlytics is reinventing the patent landscape, an industry that’s historically relied on fragmented and outdated tools. By using AI to analyze patent data, litigation history, draft claim charts, and examiner behavior, the team is creating a unified, intelligent workflow for patents.
- Enhancing Contract Management: LinkSquares offers an AI-powered contract lifecycle management platform that automates contract creation, review, and management. Its AI engine, LinkAI, is specifically trained on legal documents to extract key data, summarize agreements, and suggest redlines.
- AI Model Routing: Not Diamond is a powerful AI model routing platform that intelligently selects the best-suited large language model (LLM) for a given query. Whether used for customer service, content creation, or data analysis, Not Diamond ensures that tasks are handled by the most appropriate model, streamlining workflows.
- Physical AI for the Process Industry: Novity, for example. Novity is using AI to transform heavy industry by predicting equipment failures before they happen, even in environments with limited historical data or manual maintenance processes. Their TruPrognostics™ platform combines physics-based models with machine learning to deliver early, accurate insights that reduce unplanned downtime and optimize operations.”
- AI Processors for the Edge: Quadric is providing a unified edge AI platform that integrates high-performance computing and artificial intelligence into a single, programmable architecture, and allows industries such as autonomous driving, robotics, and agriculture to deploy advanced AI capabilities directly at the edge
How can smaller businesses or startups, with limited budgets, begin to integrate AI into their operations effectively?
What’s great about AI is that even small businesses with limited budgets can benefit. A lot of AI companies are consumption or outcome-based, meaning startups can start small and scale usage as they grow. More importantly, the right AI application can actually help a small business avoid additional hiring by increasing the productivity of the team they already have.
It’s this ability to drive real bottom-line results that’s fueling investor interest in industry-specific software, even in markets that were once considered too niche or too small for venture-scale outcomes.
What advice would you give to business leaders who are hesitant to adopt AI because of fear, misconceptions, or lack of understanding?
It’s smart to be cautious, but you don’t want to be so cautious that you get behind your competitors, or worse, become obsolete. The companies that hesitate too long may soon find themselves outpaced by faster-moving competitors. My advice is to run a few small, low-risk experiments on your most critical pain points. Do a proof of concept. Compare a few vendors. Measure the outcomes. You’ll often be surprised by how quickly the ROI shows up.
Also, don’t be afraid to ask for help. Finding the right partners can make all the difference. Firms like Myriad not only help founders navigate this space, not just with capital, but with strategic guidance, but also provide strategic guidance to businesses and corporate partners as well. Tapping into the startup ecosystem can give companies a major edge, helping them not just stay relevant but get ahead.
In your opinion, how will AI continue to shape the business world over the next 5–10 years? Are there any trends or emerging innovations you’re particularly excited about?
Over the next decade, AI will become so deeply embedded in enterprise infrastructure that we’ll stop thinking of it as a standalone function. It will power everything from procurement to personalization. One area I’m particularly excited about is legal tech, and we’re just scratching the surface of what’s possible.
Tools like Patlytics are showing how AI can bring clarity and speed to a traditionally slow-moving sector. In addition to Patlytics, LinkSquares and Wexler, Syntracts is solving knowledge management for law firms, and Callidus is building the litigation operating system for small and mid-sized law firms, just to name a few. I expect to see massive shifts in how legal research, contract review, and IP strategy are handled. And as AI gets better at understanding nuance and context, we’ll see it tackle even more complex judgment-based tasks. It’s going to change how businesses evaluate risk, make decisions, and move faster with confidence.
How do you think the use of AI to solve business problems influences relationships with customers, employees, and the broader community?
When companies use AI in the right way, it can actually bring people closer together. For customers, it means things like quicker help when they need it, or products and services that feel more tailored to them. For employees, AI can take some of the tedious work off their plates, so they have more time to focus on creative and meaningful projects. That kind of shift can really boost job satisfaction and enhance and accelerate training.
At a broader level, communities can also benefit when companies use AI to work more efficiently or come up with new ideas that make life better. Of course, AI also raises important questions around trust and transparency. So the companies that build AI with security and human impact in mind are the ones that will build the most lasting relationships with all of their stakeholders.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people through AI, what would that be? You never know what your idea can trigger. 🙂
That is a tough one. I think tackling the biggest human challenges, like conflict (including war), climate change, hunger, housing, and access/receiving healthcare, is the long game for AI. These are complex, deeply rooted issues that impact people all over the world.
But in the near term, I’d love to see AI build better personal finance, helping people save money (including through more efficient spending), plan for retirement, and build long-term wealth in a simple, meaningful way.
How can our readers further follow you online?
Connect with me on LinkedIn! You can also follow Myriad’s Twitter handle @MyriadVC to stay updated on our latest news and updates.
This was great. Thank you so much for the time you spent sharing with us.
About the Interviewer: Chad Silverstein is a seasoned entrepreneur with 25+ years of experience as a Founder and CEO. While attending Ohio State University, he launched his first company, Choice Recovery, Inc., a nationally recognized healthcare collection agency — twice ranked the #1 workplace in Ohio. In 2013, he founded [re]start, helping thousands of people find meaningful career opportunities. After selling both companies, Chad shifted his focus to his true passion — leadership. Today, he coaches founders and CEOs at Built to Lead, advises Authority Magazine’s Thought Leader Incubator.
Chris Fisher Of Myriad Venture Partners On How Artificial Intelligence Can Solve Business Problems was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.