HEAVY.AI (formerly OmniSci) Strengths, Domain Expertise, and Key Differentiators
HEAVY.AI excels with its GPU-accelerated analytics platform, delivering unmatched data processing speed and insights. By leveraging the immense parallel computing power of GPUs and CPUs, the platform enables organizations to maximize their data potential. Its availability across both cloud and on-premise environments ensures exceptional flexibility, allowing users to deploy and scale analytics solutions seamlessly to meet their specific needs.
HEAVY.AI (formerly OmniSci) Recent Developments
In January 2025, HEAVY.AI announced the general availability of its analytics platform powered by the NVIDIA GH200 Grace Hopper Superchip. This advanced hardware architecture integrates an NVIDIA-designed Arm-based CPU with an ultra-fast NVIDIA Hopper GPU, enhancing performance and efficiency. The launch is part of the broader 8.2 release of the HEAVY.AI accelerated analytics platform, further advancing its capabilities in high-performance data analytics.
In March 2024, HEAVY.AI announced the launch of HeavyIQ, introducing Large Language Model (LLM) capabilities to its GPU-accelerated analytics platform. HeavyIQ enables organizations to interact with their data using conversational analytics, allowing users to explore datasets through natural language queries and generate advanced visualizations with ease. This innovation streamlines the business analytics process, reducing complexity and making data-driven insights more accessible and efficient for a broader range of users.
HEAVY.AI has broadened its collaboration with NVIDIA, welcoming Bain & Company and Maxar to enhance tools for communication service providers (CSPs). This extended partnership aims to streamline antenna placements, optimize signal coverage, and improve network deployment efficiency. Additionally, the release of version HEAVY 7.0, introduces cutting-edge machine learning capabilities empowering telecommunication and utility sectors. This latest release enables in-database predictive modeling and diverse scenario simulations for valuable insights.
HEAVY.AI (formerly OmniSci) Mergers and Acquisitions (M&A) Activities
HEAVY.AI has attracted substantial funding from prominent venture capital firms and strategic investors, contributing significantly to its growth trajectory. Notable investors like Google Ventures, In-Q-Tel, NEA, NVIDIA, Tiger Global Management, Vanedge Capital, and Verizon Ventures have actively supported the company. These investments have facilitated innovation drives, the expansion of the product portfolio, and accelerated overall growth for HEAVY.AI.
HEAVY.AI (formerly OmniSci) Customers in ARTW Customer Database
Leveraging a rigorous data-centric research methodology, APPS RUN THE WORLD asks the simple question: Who’s buying HEAVY.AI (formerly OmniSci) applications and why? And we provide the answers – supported by decades of research – to our clients around the world. Our Customer database has over 100 data fields that detail company usage of HEAVY.AI (formerly OmniSci) and other enterprise apps by function, customer size, industry, location, implementation status, partner involvement, Line of Business Key Stakeholders and IT decision makers contact details. List of Verified HEAVY.AI platform, HeavyIQ customers.
HEAVY.AI (formerly OmniSci) Overview
100 Montgomery St, Fifth floor
San Francisco, CA, 94104, United States
1 415-851-4787
Ownership: - x
Number of Employees: 105
Functional Markets: Analytics and BI,
Key Verticals: Aerospace and Defense, Automotive, Banking and Financial Services, Communication, CPG, Distribution, Government, Healthcare, Insurance, Leisure and Hospitality, Life Sciences, Manufacturing, Media, Oil Gas Chemicals, Professional Services, Retail, Transportation, Utility,
HEAVY.AI (formerly OmniSci) Key Enterprise and Cloud Applications
HEAVY.AI platform, HeavyIQ
HEAVY.AI (formerly OmniSci) Revenues, $M:
| Type/Year | 2023 | 2024 | YoY Growth, % |
|---|---|---|---|
| Total Revenues, $M | Subscribe | Subscribe | Subscribe |
| Enterprise Applications Revenues, $M | Subscribe | Subscribe | Subscribe |
| Cloud Applications Revenues, $M | Subscribe | Subscribe | Subscribe |
* Enterprise Applications Revenues = License + Support & Maintenance + SaaS
** All revenue figures are estimates based on public records, Cloud and Non-Cloud business models in Apps Run The World's vendor database, and annual survey results including vendor feedback.
HEAVY.AI (formerly OmniSci) Revenue Breakdown By Type, $M:
HEAVY.AI (formerly OmniSci) Enterprise Applications Revenues By Functional Markets, $M:
HEAVY.AI (formerly OmniSci) Enterprise Applications Revenues By Verticals, $M:
HEAVY.AI (formerly OmniSci) Revenues By Region, $M
| Region | % of Total Revenues | 2024 Total Revenues, $M | 2024 Enterprise Applications Revenues, $M | 2024 Cloud Applications Revenues, $M |
|---|---|---|---|---|
| Americas | Subscribe | Subscribe | Subscribe | Subscribe |
| EMEA | Subscribe | Subscribe | Subscribe | Subscribe |
| APAC | Subscribe | Subscribe | Subscribe | Subscribe |
| Total | Subscribe | Subscribe | Subscribe | Subscribe |
HEAVY.AI (formerly OmniSci) Direct vs Indirect sales
| Type | Direct Sales | Indirect Sales | Total |
|---|---|---|---|
| Type % | Subscribe | Subscribe | Subscribe |
| Revenues, $M | Subscribe | Subscribe | Subscribe |
HEAVY.AI (formerly OmniSci) Customers - Breakdown by Geo, Size, Vertical and Product
List of Verified HEAVY.AI (formerly OmniSci) Customers
No. of HEAVY.AI (formerly OmniSci) Customers: x
No. of HEAVY.AI (formerly OmniSci) Enterprise Applications Customers: x
No. of HEAVY.AI (formerly OmniSci) Cloud Customers: x
No. of HEAVY.AI (formerly OmniSci) Cloud Subscribers: 4000
With nearly 4,000 users spanning corporate, academic, governmental, and scientific domains globally, HEAVY.AI has gained substantial traction across industries such as oil & gas, automotive, retail, utilities, and governments worldwide. Notable customers include Global Telco, Tutela, Skyhook, Charter, Pfizer, and Pactriglo, showcasing its broad industry applicability.
HEAVY.AI (formerly OmniSci) Market Opportunities, M&A and Geo Expansions
The expansion of HEAVY.AI's offerings through the introduction of HEAVY.AI Free, a no-cost version of its analytics platform, represents a strategic move to broaden accessibility.
HEAVY.AI (formerly OmniSci) Risks and Challenges
The recent leadership transition, with new appointments in the CEO and CTO roles, presents both opportunities and challenges. While it offers a chance to revamp market strategy, it also introduces potential risks in aligning leadership goals with the company’s long-term objectives. Ensuring a seamless transition and maintaining strategic consistency will be critical to sustaining growth and innovation.
HEAVY.AI (formerly OmniSci) Ecosystem, Partners, Resellers and SI
HEAVY.AI fosters a strong ecosystem through strategic technology integrations and partnerships, enhancing its platform's performance and reach. Collaborations with industry leaders such as Google Cloud, NVIDIA, AWS, IBM, and Microsoft, along with alliances with system integrators and value-added resellers, expand the accessibility of its GPU-accelerated analytics platform. These partnerships drive innovation, strengthen market presence, and ensure that HEAVY.AI continues to deliver cutting-edge analytics solutions to a broader customer base.
Research Methodology
Data used in research reports are derived from publicly available documents, continuous surveys of applications vendors, customers, resellers, Independent Software Vendors, systems integrators and other verifiable sources.
Vendor shares and market forecast results are based on a combination of existing databases as well as demand side and supply side research conducted throughout the year with validation from vendors, customers, channel partners and documentations such as earnings releases and 10Q and 10K filings, vertical industry studies, regional and country-level statistics from public and private institutions(i.e. colleges, universities, government agencies and trade associations).
For additional information on our methodologies, here's the link:
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