Ziggiz democratized enterprise-grade security for organizations ranging from Fortune 500 companies to local hospitals with one-person IT teams. Security analysts spent nearly three hours daily triaging 4,000+ alerts, with 67% going unaddressed. The team needed to reduce the operational burden of alert triage while accelerating customer onboarding and data integration. Within two weeks of outreach, Ziggiz identified and brought on Richard Abrich, a Principal AI Engineer who had led agentic AI builds for Microsoft and Cleveland Clinic. Over an 8-month engagement, he built a semantic knowledge graph to automate security data engineering work. He also delivered a natural language agent that enabled plain-language queries across the security data. Customer onboarding dropped from 9 months to 5 days. New data format integration shifted from 3–6 months to hours. The implementation automated 90% of security data engineering work, reducing manual effort required to operationalize and use security data.

Sandow’s CEO identified untapped strategic value in years of consumer research data spread across 150+ different sources. The data lived in spreadsheets, Typeform reports, and databases, and it was only linked by phone numbers. Analysis had been manual and typically took weeks. A two-phase system was designed to turn the fragmented research into a usable intelligence foundation. LLMs were implemented to intelligently structure survey responses across sources. Dynamic SQL views were created to support natural-language business questions. In 30 days, a production-ready system was delivered that transformed Sandow’s proprietary consumer intelligence into a B2B market research platform. The unified system reduced analysis time from weeks to real-time responses. This enabled faster access to insights across the previously disconnected datasets.

Traditional video ad production required days of manual work per asset, which limited the ability to test variations. Dicer.ai needed a faster way to generate and evaluate multiple ad concepts without relying on slow, manual workflows. The challenge was compounded by the complexity of visual AI systems compared to more mature text-based LLM approaches. Dicer.ai embedded an AI Engineer with expertise in visual AI systems. The engineer built an end-to-end competitive intelligence pipeline that mapped the market landscape and scraped competitor ads. The system analyzed top-performing ads scene-by-scene and generated multiple video variations. It also added AI-powered performance forecasting to guide which variants to produce. The solution transformed a multi-day manual process into an automated pipeline. It delivered multi-variate video ads in under 2 hours. This resulted in a 90% reduction in ad creation time. The faster turnaround enabled quicker iteration on ad variations.

Circle Labs set out to build the world’s largest AI NPC (non-player character) library powered by user-generated content. As the platform’s growth accelerated, scalability became a critical challenge. The team faced issues that threatened reliability and the ability to meet rising demand. Experts built key product features and implemented system architecture improvements to support scale. They also addressed crucial bug fixes that impacted performance and stability. The work focused on strengthening the platform so it could handle rapidly increasing usage. Circle Labs continued to thrive as the platform scaled more effectively to meet growing user demand. Critical scalability issues were resolved to improve reliability. System architecture was redesigned and stabilized to support ongoing growth.

Accrue Savings needed to bring an innovative consumer savings product to market. The goal was to flip the traditional BNPL model to help consumers save toward purchases rather than finance them with debt. They required a complete product built from concept to launch within a defined timeline. Accrue Savings partnered with a specialized development team to build a 'Buy Now, Pay Later for saving' application. The team delivered full product development, taking the app from initial concept through launch. The implementation focused on validating the novel approach to consumer savings and financial wellness. The team completed the product build over six months and launched the application. The app’s success contributed directly to Accrue Savings’ $30 million funding round. The funding outcome validated the product’s approach and market traction.

After D-ID went viral partnering with MyHeritage on Deep Nostalgia, they realized they needed a mobile app fast. They faced pressure to capitalize on momentum and quickly bring the experience to mobile. They needed the right expertise to ship an MVP on an accelerated timeline. An expert mobile development team was assembled and integrated to build the Creative Reality Studio mobile app. The team delivered an MVP in five months. The app enabled users to create customized digital humans that looked, sounded, and spoke like real people. The mobile app achieved 1M downloads. It earned a 4.5 App Store rating. It won Product Hunt's Golden Kitty Award for Best Marketing & Sales Tool with 2,000 upvotes. D-ID later raised $48M from tier-1 VCs.