روز: آذر 23, 1403

How Sudolabs brings practical AI solutions to multiple industriesHow Sudolabs brings practical AI solutions to multiple industries

Can you give us a short intro about Sudolabs? 

Sudolabs started as a digital product agency serving startups, guiding them through idea validation, product discovery, UX/UI design, and software development; we’ve covered the full spectrum.

Currently, we are focusing on enterprise solutions, specializing in AI and Digital Transformation. We help clients identify impactful use cases and ensure the seamless execution of those solutions. 

What inspired Sudolabs to dive into the world of Enterprise AI and Digital Transformation? Can you tell us a bit about the journey so far? 

When we started Sudolabs, we focused on the startup space and had a lot of success there.

Since 2018, we’ve helped start-ups and scale-ups launch over 50 products with a combined valuation of $1.5 billion. These products have raised $200 million across multiple rounds, with backing from top investors like Andreessen Horowitz, SignalFire, and Salesforce Ventures.

Working alongside some of the brightest minds in tech has been incredible.  

The transition to the enterprise segment happened quite naturally. As we grew and brought on some amazing talent, we started working with top Silicon Valley startups, which helped us build a strong reputation. This led to our first enterprise clients from the region reaching out, and we began working on larger, more complex projects.  

Ultimately, we started to explore enterprise verticals in more depth. We have delivered multiple projects, and our clients were quite impressed with our iterative process of building digital

products. We were used to fast-paced environments and quick iterative cycles when it comes to developing products. Our approach was appreciated a lot by our new enterprise clients. 

We also enjoyed the challenges they brought—they pushed us to think bigger and innovate more. Over time, this passion made it clear that diving deeper into Enterprise AI and digital transformation was the right path for us.  

Your transition toward AI and Digital Transformation has surely expanded your playing field — which new verticals have become priorities for you? 

We are, first and foremost, technology pioneers, not confined to any specific vertical. Sudolabs’ expertise lies in understanding emerging technologies, AI trends, and how users interact with these innovations.

Over time, this has naturally led us to have more expertise in certain industries, for instance we have long track-record working with banking institutions, or manufacturing companies. However, our tech expertise is applicable across different segments. 

From finance to manufacturing, how does Sudolabs tailor its approach to meet the unique needs of each industry it serves? 

At Sudolabs, we know that each industry—whether it’s finance, manufacturing, or healthcare— comes with its own unique needs. That’s why we don’t take a one-size-fits-all approach. Instead, we start with a tailored product discovery process that lets us dive deep into each client’s specific challenges and goals before any development begins. 

This discovery phase is crucial because it allows us to understand the ins and outs of their business, identify what’s working well, and spot areas where we can make the biggest impact. For example, in finance, we’re especially mindful of data security and regulatory demands, whereas in manufacturing, we might focus more on optimizing processes through predictive maintenance and AI-powered automation. 

By engaging closely with stakeholders early on, we ensure our solutions are not only technically robust but also genuinely aligned with what matters most to them. This way, we’re creating value that’s practical and meaningful for each industry we serve.

Could you share a behind-the-scenes look at some of the results Sudolabs has achieved for its clients? 

Certainly, we’ve had the chance to work with some amazing clients over the years, but let me share a few of our favorite collaborations. 

For a global steel manufacturer, we developed an AI-driven system to optimize their storage and furnace operations, which reduced their energy and emissions costs by 5%. Hitting ROI within a year, this project has been a great example of how AI can make heavy industry more efficient and sustainable. 

In the customer service, we worked with a major US-based outsourcing company, processing over 1.4 million call transcripts to help automate insights on metrics like handle time and customer satisfaction. By implementing advanced language models, we gave them a powerful tool to pull actionable insights, making their decision-making faster and more data-driven across all their call centers. 

For a major European insurance company, we developed a digital tool for better risk prediction and hazard assessment. It automates geospatial data processing and now supports over 1 million policies across 15 countries, helping more than 700 risk engineers focus on higher-value work and enabling faster, more accurate risk evaluations. It’s also been a big time-saver, freeing up over 20% of underwriting agents’ time. 

And for a marketing client with multiple agencies, we created an AI-powered lead-generation tool that personalizes reports for over 100 marketing use cases. This tool has not only streamlined their MQL process but also boosted engagement by matching customers with the right AI solutions, making lead generation much more efficient. 

AI is a very general term – what technologies do you work with and do you create success for your clients? 

We have expertise working across all key AI domains, as well as data infrastructure setup. In terms of infrastructure, that is a very interesting topic. A lot of people do not realize that in order to utilize

AI tools, you need to set up the right infrastructure to collect and process your data. Without this, you cannot train your Large Language Models or your Machine Learning Models. 

In terms of specific verticals within what people call AI today, we have experience working with LLMs and Gen AI, Traditional Machine Learning and Big Data, and other specialty AI domains, such as Computer Vision. There are multiple use-cases how to utilize all of the aforementioned technologies. 

Numbers speak louder than words—what are some key metrics that illustrate the transformative power of Sudolabs’s work? 

There are individual metrics or KPIs that each our client looks at, however ROI is definitely something what we take into consideration where we try to help our clients define the right business use-cases. For many, the improvements we bring are paying off quickly, and hitting that ROI target shows just how impactful our solutions can be. 

For companies new to AI, adapting can be a big leap. How does Sudolabs guide clients through the transition smoothly? 

We start by getting to know their business inside and out. Our team conducts in-depth assessments to understand their objectives, challenges, and existing processes. This helps us identify where AI can add the most value to their operations. Based on our findings, we develop a tailored AI strategy that aligns with their business goals. This roadmap outlines clear steps, timelines, and measurable milestones, ensuring everyone is on the same page. 

Our experts collaborate closely with our clients’ teams during the implementation phase, ensuring knowledge transfer and addressing any concerns promptly. We design AI systems that grow with our clients’ business. Our solutions are scalable and flexible, allowing them to expand AI capabilities as their needs evolve. Post-implementation, we don’t just walk away. We offer continuous support and maintenance services to ensure the newly adapted technology will be successful. On top of that, we prioritize data security and ethical AI use. 

Beyond delivering solutions, how does Sudolabs engage with communities to foster a broader understanding and excitement around AI? 

We’ve always believed that building a strong community is key, especially in the startup world where having a solid network really matters. So, we started hosting events under the SF Founders Collective, which kicked off in San Francisco and pretty quickly spread to other cities like NYC, Austin, and Salt Lake City. 

These events bring together founders and connect them with top VC experts, so they get practical insights that they can actually use. Lately, we’ve been focusing a lot on AI, diving into real-life applications and making the tech feel more accessible. 

For us, it’s not just about delivering solutions; it’s about creating a community that’s genuinely interested in learning and growing together in this space. We’re building places where founders can connect, share ideas, and hopefully get inspired about where AI can take them next.

In an increasingly competitive field, what do you think truly sets Sudolabs apart as a leader in Enterprise AI? 

What sets us apart as a leader in Enterprise AI Transformation is our personalized and practical approach. We focus on truly understanding each client’s unique challenges and goals, and we tailor our AI solutions to meet those specific needs.

Our team combines deep industry knowledge with advanced AI expertise, ensuring that our strategies are both innovative and grounded in real-world applicability. By emphasizing measurable results and fostering close collaboration, we help our clients successfully navigate AI adoption and achieve meaningful business outcomes. 

If you’re interested in exploring tailored solutions for your business, don’t hesitate to reach out to us: https://sudolabs.com/contact.

AI regulation and hallucinations: Lessons from Generative AI LondonAI regulation and hallucinations: Lessons from Generative AI London

This article brings together highlights from one of our exclusive events, you can catch all the best moments from our summits OnDemand right here.

The Generative AI Summit in London brought together some of the brightest minds in the industry to explore the challenges, breakthroughs, and potential of this game-changing technology. One standout moment was the panel discussion featuring Tom Mason, Chief Technology Officer at Unlikely AI.

We caught up with Tom after his session to dig deeper into the insights from his panel and hear more about the exciting work Unlikely AI is doing. Here are the key highlights from our conversation. Check out the full interview here:

Just looking for a quick read? We compiled the key highlights from Tom’s expert panel below.

1. The complex world of AI regulation

AI regulation is a hot topic, and Tom’s panel tackled it head-on. He shed light on how different regions—like the US, EU, UK, and China—are approaching regulation and what that means for AI innovation.

Finding common ground: Tom emphasized the importance of building trust between AI creators and users. Regulations that strike the right balance can create a solid foundation for scalable and responsible AI adoption.Innovation vs. red tape: While strict regulation can hold back innovation, a lack of oversight risks eroding trust. Tom’s takeaway? It’s all about finding that sweet spot.

Every region has its own approach, and while it’s still early days, the discussions happening now are setting the stage for the future of AI.

2. Solving the hallucination problem in generative AI

One of the biggest challenges for generative AI today is managing “hallucination”—when AI confidently generates inaccurate or outright fabricated information. Tom shared how Unlikely AI is tackling this head-on with a unique approach.

A new kind of architecture: Unlikely AI combines symbolic world models with large language models (LLMs) to create what Tom calls a “compound system.” This setup allows for greater control over hallucination, so the AI can switch between creative and hyper-accurate modes depending on the use case.Grounded in facts: By rooting their models in trusted data sources like Wikipedia, they’re working to ensure accuracy without sacrificing the flexibility generative AI is known for.

Tom explained that this issue is a major barrier to scaling AI solutions in high-trust environments like enterprise applications, but Unlikely AI is on a mission to fix it.

3. Why London is an AI hotspot

As a London-based company, Unlikely AI is putting the city on the generative AI map. Tom highlighted what makes London (and the UK) such a great place for AI innovation.

Pro-innovation vibes: The UK is in a unique position—still light on regulation but heavy on support for experimentation, making it an ideal environment for cutting-edge AI development.Talent galore: With a deep pool of diverse expertise not just in London but across the UK, it’s the perfect breeding ground for cross-functional, collaborative teams.

It’s clear that London isn’t just keeping up with global AI hubs—it’s carving out a space at the forefront.

4. What’s next for Unlikely AI?

Unlikely AI is gearing up for some big moves, and Tom gave us a sneak peek at what’s coming in the next year:

Early-stage validation: In Q1 2025, the team plans to roll out initial Proof-of-Concepts (PoCs) with companies in different sectors to test their technology in high-throughput environments.Full launch: By mid-2025, Unlikely AI is set to bring its solutions to market, offering businesses a way to deploy generative AI with accuracy and confidence.

If your business is looking to leverage the next generation of generative AI, Tom is more than open to having a conversation.

Why community events like this matter

Wrapping things up, Tom spoke passionately about the role of community in driving AI forward. Events like the Generative AI Summit bring together builders, engineers, and executives to share ideas, build connections, and foster innovation.

“It’s all about bringing different skill sets together,” Tom said. “Communities like AI AI are doing an incredible job at creating the spaces we need to collaborate and push the industry forward.”