Alembic Technologies today launched Version 3.0 of its Causal AI platform, introducing real-time enterprise simulation powered by NVIDIA DGX SuperPOD infrastructure with NVIDIA Grace Blackwell systems. The release marks a major advance in enterprise decision intelligence that enables global companies to simulate the financial impact of strategic decisions in real time before their investments are committed.
Alembic launches Version 3.0 of its Causal AI platform, introducing real-time enterprise simulation powered by NVIDIA DGX SuperPOD with Grace Blackwell systems.
The platform enables executives to simulate the impact of budget allocation decisions instantly across channels, markets, and operating scenarios.
Real-time causal recomputation allows causal graphs to update continuously instead of running in batch processing cycles.
The platform processes billions of signals across media exposure, pricing, macroeconomic factors, consumer behavior, and operational inputs.
Alembic operates a private AI supercomputing environment built on NVIDIA DGX SuperPOD with DGX GB200 systems for large-scale causal discovery.
The company recently raised $145 million in Series B and growth financing, with valuation increasing more than tenfold following the round.
Enterprises generate enormous volumes of data but still struggle to determine what actually drives revenue, growth, and customer behavior. Most analytics platforms identify correlations but cannot determine cause and effect.
Alembic’s Causal AI platform solves this problem by modeling verified causal relationships across complex enterprise data. The system processes billions of signals across media exposure, pricing, macroeconomic factors, consumer behavior, and operational inputs to identify what actions drive measurable business outcomes.
Version 3.0 introduces real-time causal recomputation, allowing executives to simulate the impact of budget allocation decisions instantly across channels, markets, and operating scenarios.
This capability moves enterprise analytics from retrospective reporting to forward decision simulation.
Version 3.0 introduces a real-time operating layer for enterprise Causal AI:
Real-time causal recomputation: Enterprise causal graphs now update continuously instead of running in batch processing cycles.
Instant scenario modeling: Companies can test allocation scenarios and immediately see projected impact on revenue, margin, and growth.
Dynamic capital optimization: Budget reallocations update marginal ROI, saturation curves, and incremental lift instantly.
Enterprise-scale decision simulation: Executives can simulate tradeoffs across brand investment, digital media, pricing strategies, sponsorships, and external market conditions.
Instead of analyzing what happened last quarter, enterprises can now simulate what will happen next and act immediately.
“This is a step change for enterprise decision-making,” said Tomás Puig, founder and CEO of Alembic. “For decades companies relied on analytics that describe correlations but cannot prove causality. With real-time Causal AI, enterprises can simulate the impact of strategic decisions before they commit capital. That fundamentally changes how organizations allocate resources and drive growth.”
Real-time causal modeling requires extraordinary computing infrastructure. Alembic operates a private AI supercomputing environment built on NVIDIA DGX SuperPOD with DGX GB200 systems, underpinning the most computationally advanced causal intelligence platform in the category. The architecture supports large-scale causal discovery, spatio-temporal graph modeling, and GPU-accelerated optimization across enterprise data environments.
The system processes billions of signals and simulations across global enterprise ecosystems.
Alembic’s AI infrastructure includes:
NVIDIA Grace Blackwell clusters
Massively Parallel Causal Discovery: Utilizing NVSHMEM for high-performance, multi-GPU memory management across distributed causal graphs
Accelerated data science & math: Core compute powered by NVIDIA RAPIDS for GPU-accelerated data processing and cuBLAS for high-speed matrix operations
Real-time logic layers: Patented Spiking Neural Networks and dynamic causal graphs optimized for enterprise-scale decision simulation
Dedicated private AI infrastructure: High-density, AI-ready environments located in Equinix data centers
This computing environment enables Alembic to deliver real-time causal inference across large enterprise data systems.
Alembic is already used by global enterprises, including leading airlines, household CPG companies, and financial services brands to connect marketing exposure and strategic investments directly to revenue outcomes.
These organizations use Alembic to quantify the financial impact of brand campaigns, sponsorships, digital media, and other complex business investments.
“Simulating the real-time impact of decisions with AI gives enterprises unprecedented intelligence for optimizing business plans and responding to changing market conditions,” said Charlie Boyle, vice president, DGX Platforms at NVIDIA. “By leveraging NVIDIA DGX SuperPOD with DGX GB200 systems using the Grace Blackwell architecture, Alembic customers can bring AI into their boardrooms, modelling scenarios in near real-time to drive informed decisions.”
Alembic recently raised $145 million in Series B and growth financing led by Prysm Capital and Accenture, with participation from WndrCo, NextEquity, Silver Lake Waterman, Liquid 2 Ventures, and other institutional investors.
The funding supports the expansion of Alembic’s causal AI research and deployment of one of the fastest privately operated AI supercomputing systems dedicated to enterprise intelligence.
The company’s valuation increased more than tenfold following the round, reflecting growing demand for causal AI across global enterprises.
Alembic Version 3.0 is available immediately to enterprise customers.
About Alembic
Alembic is a next-generation Causal AI platform that provides enterprises with unprecedented intelligence around the effects of their actions. While the initial focus is on helping marketers connect how every dollar spent on advertising leads to revenue, Alembic’s ambition is to provide causal inference analysis across the enterprise. Its proprietary Causal AI and graph neural-network architecture enable deterministic attribution, revenue forecasting, and insight generation across brand, performance, and omnichannel budgets.
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