Haast Automates Compliance Approvals, Saving Over 500 Hours of Manual Review Time

Haast is a marketing compliance software designed for enterprises in highly regulated industries such as insurance and banking that are looking to automate compliance review. Its core offering helps legal and marketing teams review public-facing content—documents, websites, and multimedia—against evolving laws and risk frameworks.

As marketing teams adopt generative AI to accelerate content creation, legal and compliance teams are finding it increasingly difficult to keep pace. Haast identified a growing need for a scalable, intelligent system that could replicate the contextual judgment of legal reviewers, adapt to regulatory changes, and operate reliably across varied formats like long-form video and podcast audio.

Traditional manual review processes were already time-consuming, often requiring more than 10 back-and-forth iterations between marketers and compliance officers. However, the influx of AI-generated campaigns made those review cycles even more unsustainable, limiting output and delaying campaign launches.

To address these pressures, Haast set out to build a scalable, secure AI platform to automate these complex content workflows across regulated compliance environments. Jack Tizzard, chief of staff at Haast, says, “Our customers want to move fast, but legal and compliance requirements slow things down. We automate the end-to-end review process so they can operate with more confidence and speed.”

Haast’s development team already had previous experience using AWS and valued its speed, security posture, and alignment with enterprise customer expectations. The company deploys its frontend using AWS Amplify, while its backend APIs and services run on Amazon Elastic Kubernetes Service (Amazon EKS). Large-scale data pipelines that ingest regulatory information from third-party sources are powered by Amazon EKS Auto Mode, fully automating Kubernetes cluster management for compute, storage, and networking on AWS.

For generative AI workloads, Haast uses Amazon Bedrock to access foundation models such as Claude, Llama, and Mixtral. These models help power a series of custom-built AI agents that simulate how legal and compliance professionals review documents. Each agent analyzes content, identifies risks, classifies them by severity, and recommends changes. Liam King, co-founder and chief technology officer at Haast, says, “Amazon Bedrock gives us fast access to models, reduces latency, and helps us run securely in customer-specific environments.”

The company also set up private access on its AWS account to access Amazon Bedrock APIs through virtual private cloud (VPC) endpoints, helping it to build generative AI applications securely using its own data. Jack adds, “Amazon Bedrock has helped us to meet the compliance and security expectations of our most regulated customers.”

Since deploying on AWS, Haast has improved productivity for legal and marketing teams by over 80 percent. Compliance reviews now take minutes instead of hours, significantly reducing the manual effort needed to check content for compliance risks. The platform flags potential issues by timestamp and location on the document or video and provides contextual explanations with suggested remediations. Previously, legal reviewers had to watch or read long-form content in full, cross-reference regulations, and manually mark up changes before routing them back to marketing. Now, marketers can jump straight to flagged sections and take action with full visibility into the risk and rationale. In some cases, Haast’s customers have reported saving more than 500 hours in content review alone.

Haast has also expanded its ability to process videos up to four times in length compared to what it could manage prior to deploying on AWS, empowering customers to conduct risk reviews on hour-long videos and podcasts—formats that were once too time-intensive to address. Its agentic pipeline supports cross-frame inspection, spoken word analysis, and onscreen content evaluation for legibility and compliance.

In addition, the company notes a 10 percent uplift on its internal video evaluation dataset, indicating improved model accuracy and platform intelligence. These results have contributed to increased customer usage, account growth, and broader platform adoption. Several of its customers have also reported up to three times faster campaign launches.

Building on this foundation, Haast has launched a new capability for near-real-time digital compliance. Using the same agentic infrastructure, its platform now reviews live websites and social media content to identify risks as soon as they appear. “Bringing contextual AI analysis to live digital content is a massive unlocker,” says Jack. “It means enterprises can catch complex risks buried amongst tens of thousands of live touchpoints, something that simply wasn’t possible before with pure human resourcing.”

Haast is now operating in the United States, with a growing library of U.S.-specific rules and regulations pre-loaded into its platform, covering industries from insurance and banking to retail and technology. The company is building a team in New York to support its rapid expansion and scale the solution across the U.S. enterprise market.