Autohive Accelerates No-Code AI Agent Creation using Amazon Bedrock

New Zealand software company Raygun has provided error and performance monitoring for thousands of global enterprises since 2007. In 2023, Raygun co-founder and CEO John-Daniel Trask identified a new opportunity to help small and medium-sized businesses take advantage of generative AI to boost productivity. “Generative AI has exploded in popularity in software engineering in New Zealand and across the globe,” he explains, “but it’s technically complex, and small to medium businesses often lack the internal resources to build and deploy solutions. Custom AI development is also expensive, and most existing AI tools aren’t integrated with business systems and workflows.”

Raygun aimed to help businesses overcome these challenges by providing much-needed solutions. “We wanted to figure out how to democratize agentic AI development so customers could put new solutions in place quickly and easily,” says Trask.

To achieve this goal, Raygun launched Autohive, a spinoff that provides an AI-powered platform which helps small and medium-sized businesses create and manage AI agents for automating business workflows. The Autohive platform runs entirely on AWS. “Raygun has been on AWS from day one, and we’ve ridden the wave of AWS technology innovation since then,” Trask says. “It was natural for us to take the same path with Autohive and continue to evolve along with AWS.”

Autohive uses Amazon Bedrock, which offers a wide range of foundation models from leading providers such as Anthropic’s Claude, supporting multi-model AI access. The platform also relies on Amazon RDS and serverless technologies including AWS Lambda to power the execution engine for custom AI tools. “AWS Lambda is integral to how Autohive works,” says Trask. “Whenever an agent invokes a tool, it runs securely within AWS Lambda.” Autohive also uses Amazon EC2 for web hosting and background task processing, Amazon Simple Storage Service (Amazon S3) for secure and scalable storage of data and agent artifacts, and AWS Auto Scaling and Application Load Balancer to manage traffic distribution and scaling.

The platform features a no-code interface designed to streamline operations such as customer support, marketing, and analytics by integrating AI agents with popular business tools including Slack, HubSpot, and Gmail. With its agentic AI flow, users can define an agent through a system prompt and attach tools and capabilities to that agent. “We could build an agent that talks to Slack or HubSpot,” Trask explains. “Our platform even supports the idea that another agent can be a tool, so you can assemble teams of specialist agents that have their own context and can achieve more.”

Early adoption has been strong across a variety of use cases. Customers already use the platform for community management, with agents monitoring online channels and publishing activity summaries so managers can focus on one-to-one engagement. One customer uses it for sales prospecting, enriching contact information from multiple sources. Another customer, an AI education firm, plans to adopt the platform as its primary tool for teaching agent development. The platform already has more than 800 active users, with 1,000 organizations and 10,000 users targeted by March 2026.

With Autohive, non-technical business users can deploy sophisticated AI workflows in minutes, eliminating the need for extensive development resources and time. “Small and medium-sized businesses are often constrained by capacity and need to try and do more with what they have,” Trask says. “The Autohive platform on AWS saves time and increases productivity by removing the barriers to agentic AI workflow creation—workflows where AI agents are designed to take initiative, interact with tools, and complete tasks independently. This ultimately helps teams achieve more.” David ten Have, vice president of commercial strategy and partnerships at Autohive, adds, “At a technical level, Autohive provides an abstraction layer that removes all the noise in the field and gives people the confidence to build systems on their own.”

Running on AWS means Autohive can scale on demand to support its growth. “We process billions of inbound API calls every month,” says Trask, “and AWS gives us the enterprise-level technology to help Autohive scale to where we want to go.” Additionally, the platform supports multi-team collaboration without per-user licensing costs and includes built-in privacy controls, encryption, and content management. This secure foundation—underpinned by AWS—helps Autohive earn customer trust, a critical factor in driving adoption of AI solutions.

To support continued adoption, Autohive is expanding its reach through online “cooking” classes that teach users how to build AI agents in practical, non-technical settings. David ten Have explains: “With our cooking classes, we’re taking the technology and putting it into an everyday context where a group of people can learn in a computer lab setting.” The company also plans to add multi-region deployment for data sovereignty compliance through the upcoming AWS Asia Pacific (Auckland) Region and offer private cloud deployments via AWS Marketplace. “We’re excited to see how we can keep scaling our business alongside AWS,” Trask concludes.