How Viktor Raised $75M to Build an AI Coworker Inside Slack and Microsoft Teams

The round also attracted a high‑profile list of angel investors. Among them were Slack co‑founders Stewart Butterfield and Cal Henderson, along with executives and founders connected to companies such as Google DeepMind, Figma, ElevenLabs, and Synthesia.

Such strategic investors are notable because Viktor’s product sits directly in collaboration tools like Slack and Teams—platforms that increasingly serve as the central operating layer for modern companies.

Founders and Company Origins

Viktor was founded in 2023 by former Meta engineers Fryderyk Wiatrowski and Peter Albert.

The company operates across Warsaw and Munich, with a team drawing engineering experience from companies including Meta, Google, Amazon, and Tesla.

Their goal was to build an AI system that works alongside teams inside the communication tools they already use, rather than forcing employees to switch to separate AI applications.

What Viktor’s “AI Coworker” Actually Does

Unlike traditional chatbots or single‑user AI assistants, Viktor is designed as a team‑level AI coworker embedded directly into Slack and Microsoft Teams.

Instead of opening another app, employees interact with the AI inside normal workplace chat channels. The agent can:

• Answer questions using company data
• Retrieve information from connected systems
• Perform operational tasks across multiple apps
• Run automated workflows triggered by chat instructions

Because it operates where conversations already happen, the system aims to become part of day‑to‑day team workflows rather than a separate productivity tool.

Connecting to 3,000+ Tools and Running Autonomous Workflows

A key technical component of Viktor’s approach is its integration layer. The AI agent connects with more than 3,000 workplace tools, giving it access to the systems companies already use for operations.

These integrations allow the agent to:

• Pull data from internal tools and databases
• Update records in CRM or project systems
• Trigger actions in other software
• Coordinate multi‑step workflows across platforms

Reports describe the system as an agentic AI platform capable of autonomous multi‑step workflows, rather than just generating text responses.

Another core concept is organizational memory. By observing conversations and connected systems, the AI builds persistent context about how a company works, allowing it to answer questions and support ongoing projects with historical knowledge.

The Growth That Attracted Investors

Investors were particularly drawn to Viktor’s early traction.

According to company statements and reporting, the product reached:

• More than 2,000 organizations using the platform
• Around $15 million in annualized recurring revenue
• Approximately 10 weeks after public launch

That speed of adoption is unusual even by fast‑growing SaaS standards and reflects growing enterprise interest in AI agents capable of executing tasks rather than just assisting with writing or search.

What Viktor Plans to Do With the Funding

The new capital is expected to accelerate several areas of growth.

First, Viktor plans to expand globally, aiming to bring its AI coworker to more teams beyond its initial customer base.

Second, the company intends to scale enterprise adoption, improving governance, integrations, and operational workflows needed for larger organizations.

Finally, Viktor plans to continue expanding the agent’s capabilities so it can automate a wider range of workplace processes across the tools companies already rely on.

The Bigger Trend: AI Employees in the Workplace

Viktor’s rapid funding round reflects a broader shift in enterprise AI. Instead of standalone chatbots or copilots used by individuals, many startups are now building AI agents that operate across entire teams and software stacks.

By embedding automation directly inside communication platforms like Slack and Microsoft Teams, these systems aim to become a persistent operational layer for businesses.

Viktor’s early growth suggests investors believe that model—an AI coworker working alongside human teams—could become a major category in enterprise software.