Skan AI

10/09/2026

f you caught up with our team at Sibos (https://hubs.ly/Q04zN1yb0) Miami last week, you might have noticed another team at the booth. We've joined forces with NVIDIA so FinServ enterprises can build an AI factory they can trust.

All week, our teams were sharing how highly regulated industries like banking, insurance, and healthcare can run Al agents on infrastructure they control.

If you've tried to customize Al for regulated work, you know the catch. Agents have to learn how your business really works, which means training them on operational data you'd rather keep inside your walls.

Now that training can stay there. Skan Al captures how the work gets done, exceptions included, and compiles it into ex*****on logic for your agents.

NVIDIA Al Enterprise runs the training and ex*****on in your private environment.

The agents know the work, and every step they take is governed and auditable.

Stay tuned! More to come.

10/06/2026

Sibos & ITC at the same time, on opposite coasts? That's how our team spent last week, and the whirlwind was worth it. We spent 3+ days talking with and learning from the teams reimagining banking and insurance operations with agentic AI.

In case you missed out, here are the highlights:

1️⃣ We opened ITC with a standing-room-only fireside chat between Skan AI's Daniel Dantus and Venki Arunachalam, former Sr. Director of Technology Strategy in insurance at Equitable.

The two got deep into Venki's experience standing up and scaling AI for insurance, long before the 2020s AI boom. One of the biggest challenges (and opportunities for ROI) they discussed: automating complex decisions. From their experience, that can't happen in complex insurance workflows without rich operational context. Not only to customize AI for your business but also to serve as the guardrails in production.

2️⃣ At Sibos, we talked with attendees about how our platform helps banks build agentic AI that they can own end to end and trust with mission-critical work.

Enterprise banking teams from around the world came and asked us in-depth questions about the platform architecture. It was great to be able to just pull up a complete demo and dive deeper into how building an AI factory on private infrastructure addresses common security, compliance, governance, and reliability concerns.

3️⃣ Across both events, executives wanted to know: how can we be sure that the agentic AI systems we build are making us more competitive? And how do we know if our AI workflows will meet our compliance and security standards or pass an actual audit?

Our answer for both those questions: you need end-to-end visibility into how your processes are executed.

Until you have complete context, derived from real work, your teams and AI agents can't execute on a shared understanding, you can't reliably govern production AI agents at scale, and you can't measure the before vs the after. But once you do, you'll have the operational patterns and insights you need to accelerate AI transformation and business impact.

We've seen how this shift has helped our customers cut millions in OpEx, accelerate processes, and evolve how their teams operate with agentic AI. Stay tuned for future events and webinars so we can answer your questions and help your team do the same!

09/23/2026

Building AI roadmaps shouldn’t be a guessing game. But enterprise executives are under pressure to deliver ROI from their AI investments… so how do they justify taking a step back and examining the bigger picture first?

Jennifer Redden, Head of Technology at Definiti, wasn’t interested in risking her team’s AI budget on the wrong bets. “The faster we work, the more accurately we work, the better those outcomes are for real people. That’s why getting this right matters.” They needed to identify the right processes to automate with AI to free domain experts at Definiti from repetitive, low-impact work so they could better support their retirement services clients.

Now, with Skan AI, Definiti has a complete understanding of the work being done, where they should implement agentic AI, and how to govern and trace AI agent ex*****on. And that means confidence in their AI roadmap and a practical path to deploying and governing AI agents at scale.

Read the full story: https://hubs.ly/Q04y7snV0

09/21/2026

Working with 7 in 10 of the top US banks, our team’s seen a rapid shift in enterprise AI expectations. Banking execs aren’t measuring AI success by demos or even deployments; now, they want to reimagine how complex work happens at enterprise scale.

Join us at Sibos Miami, Sept 28 - Oct 1, where we’ll be diving into how we power the teams and AI agents transforming this industry: https://hubs.ly/Q04xYk8j0

What we've learned alongside our customers: getting AI into production isn’t the hard part anymore. Banking organizations need to give teams and AI agents a shared understanding of regulated workflows.

Closing that gap is the key to executing complex work in lockstep across the organization. In our team's experience, this holds true across payments, loan underwriting, controls monitoring, and more.

Meet us at Booth DISM 06 and see why our customers trust the Skan AI platform to accelerate complex workflows at scale.

Meet Skan AI at ITC Vegas 2026 (Booth 2227). See how insurers deploy AI agents for claims and underwriting with traceable context, governance, and real ROI.

09/15/2026

"What you think is happening is not what is happening in reality." That's how Jade Burt, Director of Business Transformation at Mitie, describes the work visibility gap that opens up when you operate at enterprise scale. So far, that's been an unavoidable part of the enterprise AI playbook, too.

But AI running complex mission critical operations on assumptions and stale documentation instead of observed reality rarely delivers the returns you expect, while also adding risk and tech debt.

Jade and Peter Woodsford, Head of Network, Infrastructure and Automation, wanted a different way to transform their facilities management operations. With Skan AI, Mitie now has near real-time visibility into how work actually flows across systems and processes.

So instead of guessing where to improve and automate, their teams can see exactly where the effort goes and fix what matters most.

Check out the full story: https://hubs.ly/Q04xz89j0

09/11/2026

Conversations so good our team’s ready to do it all over again (and again)! After 3 days at Global Fintech Fest, we’re geared up for ITC Las Vegas and Sibos Miami at the end of this month.

We’ve learned a ton about where leaders and builders are getting stuck after deploying agentic AI systems in banking and insurance.

- What do you do when your security, compliance, and data teams disagree on whether AI governance is “good enough”?

- Where’s the line between good vs. bad training data? And how often should you be retraining your agents?

- How do you set up and stick to SLAs for getting deployed agents in compliance with new regulations?

A lot of this isn’t brand new to us: 60% of top US insurers and 7 of the top 10 US banks already use Skan AI.

We’ve helped these kinds of enterprises see what happens inside large scale operations. That includes complex, highly regulated processes behind loan origination, AML/KYC checks, and fraud exception handling.

But even when you can capture the reality of work, organizational alignment and buy-in are priceless. So we’re excited to keep learning about what these problems look like from your perspective, in your industry.

Come to ITC Las Vegas or Sibos Miami this month and see how we’re building the foundation banks and insurers need to operationalize AI.

08/12/2026

We're excited to announce our $63 million Series C, led by Cathay Innovation and Dell Technologies Capital, joined by Bloomberg Beta, Wipro Ventures, Citi Ventures, and State Farm Ventures, bringing our total raised to $117M.

Together, we’re scaling the platform that brings enterprise AI the work context it’s been missing.

In the time since we launched, Skan AI has observed and analyzed more than 500,000 workflows at organizations like Definiti, Mitie, and RELX running in highly competitive, regulated industries.

And we consistently see that the most vital work context isn’t being provided to train AI agents.

That’s the context gap Skan AI is closing.

Check out the full story and see what’s possible when enterprise AI has complete work context: https://hubs.ly/Q04sPVJg0

08/12/2026

VentureBeat’s Michael Nuñez sat down with Aviniash Misra to talk about how “the industry has misdiagnosed the [enterprise AI] problem” and why Skan AI is on a mission to give agentic AI a better understanding of the business.

In the article, Avinash explains why not all context is created equal: data sources like documentation, SOPs, or even systems logs prepare agents for an incorrect version of how work gets done. Agents won't understand the work until the context that trains and governs them is built from observations of real work.

Bridging this gap is exactly why Aviniash and co-founder Manish Garg started Skan AI seven years ago. Read the full story behind our $63M Series C and what enterprise AI can do when it has the right context: https://hubs.ly/Q04sPgDr0