Notch Recognized as One of Tomorrow's Growth Companies for 2026

Building the AI Operating System for Regulated Industries

We’re proud to share that Notch has been selected as one of Qumra Capital’s Tomorrow’s Growth Companies 2026, and will be joining the cohort at Calcalist’s Mind the Tech conference in New York.

Recognition like this is exciting, but for us, it is also a reminder of what we are really building toward.

The next wave of AI will not be defined by better chatbots. It will be defined by systems that can operate inside complex, regulated, high-volume industries - safely, reliably, and at scale.

That is where Notch is focused.

Across financial services, insurance, and telecom, customer operations are no longer simple support flows. They involve sensitive data, strict policies, identity verification, fragmented systems, compliance requirements, and workflows that often continue long after the first customer interaction.

In these industries, answering a question is not enough. The AI needs to understand context, follow policy, connect to core systems, take action, escalate when needed, and leave a clear audit trail behind.

That is the standard we believe enterprise AI must meet.

‍

Why regulated industries need a different kind of AI

Most companies today are experimenting with AI in one of two ways: either as a customer-facing assistant that answers common questions, or as a point solution that automates a narrow task.

Both can create value. But in regulated industries, they are not enough.

An insurance carrier does not need another disconnected tool that summarizes a claim file but cannot update the claim system. A financial institution does not need an AI assistant that sounds helpful but cannot explain why it made a recommendation. A telecom provider does not need another chatbot that deflects tickets without resolving the underlying operational issue.

These industries need AI agents that can execute real workflows end-to-end.

That means combining conversation, reasoning, authentication, integrations, business rules, compliance controls, and back-office execution into one governed system.

This is the difference between AI that replies and AI that resolves.

‍

Insurance is where the problem becomes impossible to ignore

Insurance is one of the clearest examples of why this matters.

A claim is not a single task. It is a long-running operational process involving intake, coverage validation, documentation, routing, reserving, adjuster work, customer communication, fraud indicators, payments, and compliance obligations.

If the first interaction is incomplete, inconsistent, or poorly structured, the damage compounds downstream. Rework increases. Cycle times stretch. Adjusters spend more time fixing intake quality. Customers wait longer. Leakage risk grows.

That is why we see insurance not just as a vertical, but as a proving ground for enterprise AI.

At Notch, our agents are designed to operate across the full lifecycle: collecting information, structuring data, applying policy logic, integrating with systems like claims platforms and CRMs, and supporting both external customer interactions and internal operational teams. Notch’s own positioning describes this as AI agents that automate operational workflows across conversational and back-office processes, with governance and auditability built for regulated environments.

The goal is not to add AI around the edges of the process. The goal is to make AI part of the operating layer itself.

‍

The same pattern applies across FSI and telecom

Financial services and telecom face a similar structural challenge.

They serve massive customer bases. They operate under strict rules. They depend on legacy systems. They handle sensitive customer data. And their frontline teams are often forced to bridge the gap between what customers expect and what internal systems can actually support.

Customers expect instant, natural, personalized service.

Enterprises need every action to be secure, compliant, traceable, and aligned with policy.

That gap is exactly where AI agents can create meaningful value - but only if they are built for production from day one.

For FSI, that means supporting workflows like account servicing, document collection, customer verification, complaints, policy-bound decisions, and operational follow-up.

For telecom, it means handling high-volume service interactions, plan changes, billing questions, technical troubleshooting, retention workflows, and escalations across multiple systems and channels.

In both cases, the challenge is not conversation alone. It is execution.

‍

Trust is the product

In regulated industries, trust is not a marketing message. It is architecture.

Every AI-driven action needs guardrails. Every sensitive workflow needs authentication. Every decision needs traceability. Every deployment needs monitoring, evaluation, and a way to improve safely over time.

That is why Notch has been built around production readiness: secure integrations, policy-aware execution, human oversight, auditability, and the ability to adapt to each enterprise’s infrastructure. A Notch engineering article describes this approach as AI agents that “authenticate, integrate, and act” inside regulated environments, not just answer questions.

This is what separates enterprise AI from demos.

A demo can be impressive in five minutes. A production system has to be reliable every day.

‍

What growth means to us

Being recognized as one of Tomorrow’s Growth Companies 2026 is an honor. It reflects the work of the entire Notch team, our customers, our partners, and the investors who believe that regulated industries are ready for a new operating model.

But growth is not only about company momentum.

For us, growth means proving that AI can safely take on more responsibility in the industries where accuracy matters most.

It means helping insurers resolve claims faster and with better data.

It means helping financial institutions improve service without compromising compliance.

It means helping telecom providers move from ticket deflection to real resolution.

And it means building AI agents that do not just sound intelligent, but operate with the control, reliability, and accountability that enterprises require.

That is the future we are building at Notch.

And we are just getting started.

‍