Company
Ziggiz is a security operations platform that helps organizations detect and respond to cybersecurity threats. The platform processes security data from multiple sources automatically and translates technical alerts into plain language, serving organizations from Fortune 500s to local hospitals with one-person IT teams.
The Challenge
Ziggiz's platform had a critical bottleneck: onboarding new customers took nine months, and integrating new data formats required three to six months of manual effort. The root cause was that 90% of security work is just data engineering—every new data source or format change demanded intensive manual configuration that kept the platform accessible only to organizations with dedicated security teams. This prevented Ziggiz from democratizing enterprise-grade security to a broader market, including healthcare facilities under constant ransomware attack where staff needed to understand alerts and respond without technical security backgrounds. To break through these bottlenecks, Ziggiz needed someone who understood which AI tools to use for specific problems rather than chasing trends, brought healthcare domain knowledge to translate technical concepts for practitioners, and could deliver fast while the startup conserved runway.
The Solution
Within two weeks of Ziggiz's outreach, A.Team identified Richard Abrich—a Principal AI Engineer who had led agentic AI builds for Microsoft and Cleveland Clinic. Abrich integrated into Ziggiz's team from day one, joining standups and collaborating directly with leadership without the lengthy onboarding typical contractors require. Over eight months, he built two interconnected systems that automated Ziggiz's manual data engineering burden and made security accessible to non-technical users.
He created a semantic knowledge graph that understands what security data actually means—building relationships between data sources, processing only what's being used through sparse field extraction, and optimizing for massive scale. He then built a natural language agent that lets users ask questions like "What does this alert mean and what should I do?" or "Show me the top five users with the highest risk" in plain language, applying sophisticated context engineering to prevent hallucinations and ensure teams could trust the guidance. What set Abrich apart wasn't using the newest AI models—it was knowing exactly which tool to use when, from SVMs for clustering to Gaussian curves for analysis, selecting the right technique to achieve specific business outcomes.
Technologies Used
Natural Language Processing: Built an AI agent enabling non-technical users to query security systems and understand alerts in plain language
Context Engineering: Applied advanced techniques to manage information flow across conversation threads, preventing model hallucinations
Semantic Knowledge Graphs: Created an intelligent layer that understands data relationships and determines what's worth processing
SVMs and Gaussian Curves: Employed for data clustering and statistical analysis within the processing pipeline
Sparse Field Extraction: Processed only actively-used data to dramatically reduce computational costs and improve efficiency
LLMs: Integrated large language models as part of a carefully selected toolkit matched to specific challenges
"How do you get access to exceptional talent that understands it's not about the tool, but how you use it? A.Team can get the right person for the job to help you get to your next stage of growth."
— George Webster, Founder & CEO, Ziggiz
The Results
Ziggiz transformed from a platform requiring nine months to onboard customers into one that delivers enterprise-grade security in days, making sophisticated threat detection accessible to organizations that previously couldn't afford the expertise or infrastructure.
Customer Onboarding
Accelerated from 9+ months to 5 days—a 99% reduction—by automating complex data processing and semantic understanding.
Data Integration Speed
Reduced new format integration from 3-6 months to hours through automated processing and intelligent data orchestration.
User Accessibility
Expanded from technical experts only to non-technical users including hospital IT members who can now understand and act on security alerts.
Competitive Positioning
Strengthened core intellectual property with a scalable, automated pipeline that formalized previously manual processes in ways difficult for competitors to replicate..
