Logic

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Logic is building autonomous agents for enterprise workflows. Its system lets users deploy agents that can handle tasks like research and operations by working with the tools companies use, whether that is Slack and Notion for internal coordination, customer platforms for support workflows, or engineering tools and internal databases for technical tasks. Unlike a chatbot or copilot that mainly answers questions or helps with one-off tasks, Logic’s agents are built to handle multi-step workflows and operate with less human input over time. The platform fits into the broader shift toward AI infrastructure that helps companies automate internal work and improve efficiency.

Check it out: logic.inc

One prompt gets you a working app.

Not a wireframe, not a prototype. A live product.

Founders are skipping the backlog entirely and shipping what they need, when they need it.

No dev team required. No waiting. Just results.

Start building at bolt.new.

This is sponsored content.

Logic uses a usage-based SaaS model with team and API pricing. Team plans range from a free trial to $20 and $200 per user per month, with higher tiers offering more executions, longer log retention, added security, and enterprise controls. Logic also offers teams a free trial with limited executions. API usage is priced separately at $0.05 per execution.

• Raised a $4.3 million seed round in October 2025 from institutional investors, including Audacious Ventures, Founders’ Co-op, and Convoy co-founder Dan Lewis, along with individual backers such as Neo CEO Ali Partovi

• Became generally available in December 2025, removing its waitlist and opening the platform to users

• Had more than 2 million automations run at the time and has since shifted toward a stronger focus on engineering and technical users

• Built a platform supporting 200+ AI agents with a team of around six people

If you’d like to explore opportunities with Logic, feel free to reach out to us by replying directly to this email!

Steve Krenzel’s path to founding Logic was shaped by experience across both large tech companies and startups. He started his career as a software engineer at Microsoft before co-founding Thinkfuse, a workplace communication startup that helped teams streamline internal status reporting. It was later acquired by Salesforce, where he met his future co-founder, Jess Garms. After Salesforce, Krenzel worked at Twitter and later joined companies including Convoy and Brex.

Across all of these roles, he kept seeing internal teams struggling with clunky tools and inefficient, hard-to-scale workflows. Logic came directly from that recurring problem. Instead of adding yet another tool for teams to manage, Krenzel wanted to build a platform where AI agents could carry out standard operating procedures on their own, including testing, execution, and recurring workflows that typically take a lot of human time. That idea became the foundation for Logic’s vision of helping small teams operate with far more leverage.

If a task takes more than 30 seconds, Logic believes it’s time for an AI agent to take over. This idea pushes AI beyond just assisting with work and into fully executing it, one of the biggest shifts in software today. McKinsey highlights how AI-driven development is transforming programming, moving from simple task-based support to AI agents running entire workflows and applications.

What makes Logic interesting is its focus on recurring work. Many AI tools still depend on people to prompt them at every step of the way. Logic is trying to move past that by building agents that can recognize recurring tasks and handle them more independently over time. That means the product becomes more valuable the longer it is used, building a moat for the company, and transforming it into a complete operating layer inside a company rather than just another productivity tool.

This vision is reflected in the product, too. Using Logic seems to be less about chatting with a single assistant and more about setting up a system for repeated execution. Users can turn standard operating procedures into agents that handle recurring tasks, run tests, and carry out workflows across the tools they already use. This makes the case for scalability very compelling.

The team itself is optimized for scalability, too. Logic has a team of around six people and already supports more than 200 agents. It suggests a future where smaller teams can get much more done without having to keep adding headcount, which creates the potential for a highly scalable business with strong revenue leverage.

There are still risks. The AI agent space is unquestionably getting crowded with agents becoming a core part of enterprise operations that could generate up to $450 billion in economic value by 2028. That kind of momentum will likely attract even more startups and larger incumbents into the category. Logic will need to stand out through product quality, reliability, and by minimizing adoption friction. 

Still, the company’s thesis is strong. Work is clearly moving toward more automation and more leverage per employee. If Logic can keep improving its agents and deliver on its vision of more autonomous systems, it has a real shot at becoming an important company in enterprise AI infrastructure.

• Logic website [Logic]

• How to build an AI agent: from phototype to production [Logic]

• Logic Raises $4.3M in Seed Funding  [Finsmes]

• Anthropic launches new push for enterprise agents with plugins for finance, engineering, and design [TechCrunch]

• Create an Onboarding Plan for AI Agents [Harvard Business Review]

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