30 Trillion offers a convergence layer that ingests data from IoT sensors, transactions, logs, APIs, and enterprise systems, then unifies, normalizes, and extracts signals at scale for real‑time analytics. The platform provides tool‑agnostic SDKs and REST APIs, enabling any AI model—whether internal generative AI, third‑party analytics, or custom algorithms—to consume clean, AI‑ready data. Built on a security‑first, cloud‑agnostic architecture, it supports infinite scaling and regulatory compliance for enterprise workloads.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises often struggle to collect, unify, and preprocess high‑velocity data from diverse sources such as IoT sensors, transaction logs, APIs, and legacy systems. Without a scalable, real‑time pipeline, the data remains fragmented, noisy, and unsuitable for immediate AI or analytics consumption, leading to delayed insights and operational risk.
Solution
30 Trillion offers a cloud‑agnostic convergence layer that ingests up to 500,000 events per second from heterogeneous data streams. The platform normalizes, unifies, and extracts signal features in real time, delivering clean, AI‑ready intelligence through tool‑agnostic SDKs and REST APIs. Its security‑first, regulatory‑compliant architecture supports infinite scaling, allowing any generative AI model, third‑party analytics engine, or custom algorithm to consume consistent, high‑quality data without additional preprocessing. By providing a unified data fabric, 30 Trillion enables organizations to make real‑time decisions and accelerate AI initiatives across cyber security, financial risk, and other data‑intensive domains.
Target Audience
Primary customers are data‑intensive enterprises in sectors such as cybersecurity, financial services, and IoT‑driven operations that require real‑time, unified data pipelines for AI and analytics workloads.
Features
- Real‑time ingestion of IoT, transaction, log, API, and enterprise system data at up to 500 k events/second
- Cloud‑agnostic deployment model that works across public, private, or hybrid environments
- Automatic data unification, normalization, and signal extraction with built‑in feature engineering
- Tool‑agnostic integration via comprehensive SDKs and OpenAPI‑compatible REST endpoints
- Security‑first, regulatory‑compliant infrastructure designed for enterprise data protection
- Infinite horizontal scaling to accommodate growing data volumes and AI model complexity