Amberd.ai Launches Private AI Decision Platform for Enterprises, Redefining Business Decision Making

Founded by serial entrepreneurs with successful exits to Cisco, Procore Technologies, Experian, and VMware

LOS ANGELES, March 11, 2026 /PRNewswire/ -- Amberd.ai, an AI platform built for data-intensive organizations, today announced the launch of its private, LLM‑native decision system that lets enterprises ask plain‑language questions and receive clear, sourced answers from their own data while protecting privacy and compliance. For the first time, multiple databases and documents can be queried in the context of industry‑specific laws and regulations, providing a single, decision‑ready answer organizations can trust.

This launch follows more than two years of product development and real-world testing with enterprise customers. The company was co‑founded and is fully self‑funded by Co-CEOs Mazda Marvasti and Zaré Baghdasarian, both veteran technology executives who have decades of experience building and operating large‑scale enterprise systems.

Enterprise leaders increasingly recognize the power of AI but struggle to integrate it into real operational workflows. Building AI internally is often slow and costly due to legacy systems and limited IT capacity, while off‑the‑shelf tools frequently fail to integrate deeply with an organization's full data ecosystem. Amberd.ai's solution architecture team works with enterprise stakeholders to deploy AI‑driven decision engines that connect directly to existing systems, workflows, and data sources, delivering real‑time, decision‑ready insights tailored to each organization.

Early customers like CDS (Connected Dealer Services) are already using Amberd to bridge connected‑car data and dealer‑management systems (DMS) and help grow dealer businesses.

"Public LLMs were never an option for CDS due to the sensitivity of our customer and vehicle data," said Shane Wilson, President of CDS. "Amberd gave us a secure AI platform that integrates directly with both our connected car data and dealer management systems. For the first time, we have an immediate, unified view of this data, allowing us to make better decisions and deliver stronger outcomes for our dealer partners."

Amberd.ai's platform is deployed in a private, enterprise‑grade environment, ensuring that data remains under the customer's control and is protected by strict governance and security controls. Amberd.ai was built on the idea that enterprises shouldn't have to choose between the power of cloud‑based AI and the safety of a locked‑down data environment. The company ensures that sensitive information stays within the customer's control, while still giving leaders fast, conversational access to the insights they need.

"Enterprises have more data than ever, but AI stalls because data is fragmented and siloed, the risks around privacy and compliance are unclear, and leaders don't fully trust the answers," said Baghdasarian. "With Amberd, we're excited to launch a private AI decision platform that brings together live data, industry context, and a transparent, auditable workflow so organizations can finally treat AI‑driven business intelligence as decision‑grade."

Amberd.ai is currently available to enterprise customers and is designed to scale alongside existing data infrastructure without disrupting current systems.

About Amberd.ai

Amberd is a private, LLM-native platform that gives executives a single, decision-ready answer from across all their structured and unstructured enterprise data—without sacrificing privacy, governance, or control. Built on a modular, agentic architecture that combines specialized knowledge banks, intelligent information access, and compliance-first workflows, Amberd helps data-intensive organizations replace slow, manual reporting cycles with real-time, explainable insights they can trust in the boardroom. Amberd was founded by AI and data-infrastructure veterans Zaré Baghdasarian and Mazda Marvasti, is fully self-funded, and is headquartered in Los Angeles, CA. For more information, visit https://amberd.ai.

SOURCE Amberd