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Arango Appoints Jakki Geiger as CMO to Accelerate Growth and Educate the Market on Enterprise-Grade GenAI Data Infrastructure
News Update
SAN FRANCISCO, CA — September 23, 2025 — Arango, the trusted data platform for enterprise-grade GenAI applications and solutions, today announced the appointment of Jakki Geiger as Chief Marketing Officer. A three-time CMO and veteran data and analytics leader, Geiger will lead global marketing as Arango builds on its multi-model database capabilities to give AI innovators and builders a trusted data foundation for building enterprise-grade GenAI applications, making it easier to extend today’s solutions with future-ready AI capabilities.
The Barriers to GenAI Project Success
Most enterprise GenAI applications and solutions never reach production. According to Fortune, citing an MIT study, 95% fail. The reasons are clear: fragmented data starves AI models of relationships, leading to answers you can’t trust. Legacy stacks collapse under enterprise-scale loads, stalling pilots before they scale. Spiraling GPU and infrastructure costs drain budgets and derail initiatives.
At the root of all these issues is fragmentation. Data is scattered across silos and formats, forcing developers to integrate multiple databases, pipelines, and technologies just to get started. Each piece brings its own complexity, brittleness, and cost. The result is a data infrastructure nightmare that creates a fragile foundation, undermines accuracy, blocks scalability, and makes ROI almost impossible.
Arango eliminates the complexity and costs of integrating fragmented tools and technologies with a trusted data foundation for the next wave of enterprise-grade GenAI applications – delivering accurate answers, limitless scalability, and cost-efficiency.
Leadership Perspective
“We’re thrilled to welcome Jakki to Arango at a pivotal moment,” said Shekhar Iyer, CEO of Arango. “Market demand for trusted GenAI data infrastructure has never been greater, and Jakki brings the experience of a growth CMO who knows how to meet it. She has a rare ability to build awareness, educate the market, and help organizations understand how to overcome the barriers standing in the way of enterprise-grade GenAI success: trust deficits, scalability bottlenecks, and high infrastructure costs. With Jakki’s leadership, Arango is well-positioned to guide enterprises and innovators as they move from pilots to production with confidence, and unlock what’s possible with GenAI.”
Why Jakki Joined
“I joined Arango because it’s rare to find a mission-driven team, breakthrough technology, and customers doing groundbreaking work, all aligned at the right moment,” said Jakki Geiger, CMO of Arango. “What excites me is how Arango solves the data infrastructure nightmare of building GenAI apps that hold companies back from delivering the ROI and business value. By providing the trusted data foundation for the next wave of enterprise-grade GenAI applications – delivering accurate answers, limitless scalability, and cost-efficiency in a single platform – Arango is a game changer for the future of enterprise AI.”
Jakki’s Background
Geiger has spent two decades shaping go-to-market strategies for data and analytics innovators. She has served as CMO for three B2B SaaS companies, Reltio, Pyramid Analytics, and Hazelcast, where she drove brand transformation, scaled pipeline contribution, and accelerated growth. Earlier, she spent almost 10 years at Informatica, where she held senior marketing and sales enablement leadership roles and played a pivotal role in the company’s transformation and go-to-market strategy, helping drive double-digit growth as the company prepared for re-IPO.
Key facts:
Company: Arango provides the trusted data foundation for the next wave of GenAI applications – delivering accurate answers, limitless scalability, and cost-efficiency. (Formerly named ArangoDB, creator of the much-loved ArangoDB multi-model database, is highly rated on G2, where customers consistently praise its performance, scalability, and ease of use.)
Vision: To help companies of all sizes build GenAI applications on a massively scalable data infrastructure defined by trust, scale, and cost-efficiency.
Funding: Backed by investors including Bow Capital, Target Partners, Iris Capital, New Forge, and ORIX USA’s Growth Capital, with $58+ million raised to date.
Technology: The Arango GenAI Data Platform enables developers to build enterprise-grade GenAI applications and solutions, eliminating the complexity and costs of integrating fragmented tools and technologies, in a single development environment. It delivers ready-to-use ingestion pipelines, BYO LLM integrations, MLOps, and agentic frameworks for building GraphRAG / HybridRAG and enterprise context management solutions. At its core is a massively scalable multi-model database – combining graph, vector, document, key-value, and search data, trusted by thousands of developers.
Customers: Thousands of developers at 200+ companies, including NVIDIA, HPE, London Stock Exchange, US Air Force, National Institutes of Health, Ministry de Defense France, Synopsys, and innovative GenAI startups like Articul8, trust Arango as their enterprise-grade GenAI data infrastructure powering critical applications, reaching billions of consumers.
About Arango
Arango provides the trusted data foundation for the next wave of GenAI applications – delivering accurate answers, limitless scalability, and cost-efficiency. The Arango GenAI Data Platform enables developers to build enterprise-grade GenAI applications and solutions, eliminating the complexity and costs of integrating fragmented tools and technologies, within a single integrated environment. It delivers ready-to-use ingestion pipelines, BYO LLM integrations, MLOps, and agentic frameworks for building GraphRAG / HybridRAG and enterprise context management solutions. At its core is a massively scalable multi-model database – combining graph, vector, document, key-value, and search data. Trusted by thousands of developers at companies including NVIDIA, HPE, London Stock Exchange, US Air Force, National Institutes of Health, Ministry de Defense France, Synopsys, and innovative GenAI startups like Articul8. Learn more at arangodb.com, LinkedIn, YouTube, and G2.
Media Contact
marketing@arangodb.com
Legal and Compliance challenges in modern finance and how ArangoDB plus GraphRAG solves them
Estimated reading time: 4 minutes
In today’s financial sector, staying compliant isn’t just about keeping up - it’s about keeping your organization safe, agile, and ahead of the competition. Every week new sanction headlines, revised regulations, and internal policy updates flood your compliance teams. These aren’t just bulletins; they’re pressure points. Buried inside government websites, legal PDFs, third-party data feeds, and dusty internal repositories are potential threats and obligations. And somewhere in those scattered silos, an analyst - likely under time pressure - is trying to connect the dots.
The traditional methods? Far too slow. A compliance question that should take 15 minutes might take 15 hours or even 15 days. Manual review, keyword search, endless cross-checking with policies and past decisions - this is the norm. But with the pace of change today, it’s also a serious liability.
That’s where this new combination of ArangoDB and something called GraphRAG quietly changes the game.
Imagine every policy, regulation, clause, and committee decision represented in a living graph - a database where your data is truly connected, making it easy to understand, navigate, and use. ArangoDB doesn’t just store information - it models the relationships in your data, effortlessly handling large and complex data sets. So instead of flipping through spreadsheets, documents, and inboxes, you see the structure of your compliance landscape as a whole. You see how a new AML directive links to your operations in Hong Kong, and which internal policies are suddenly out of sync. You don’t need a dozen emails. You don’t need a war room.
Here’s where it gets even more interesting. When you pair this graph with GraphRAG - combining your connected data with GenAI and Large Language Models - your compliance team can actually ask questions in plain language. “What recent regulations affect our private banking division in Asia?” doesn’t lead to a Google search. It initiates a graph search in ArangoDB. The system finds the most relevant links across your data - regulations, business units, geographies, policies - and pulls together contextual information. Then it uses a language model to respond. Not with guesswork, but with facts: citations, context, and a clear lineage from question to answer.
Unlike black-box AI tools that produce poetic but unverifiable text, the combination of ArangoDB and GraphRAG is built for audit trails. You can trace every insight back to its source. You know why the answer is what it is. And more importantly, you can show it to someone else - regulators included - and trust that it holds up.
The result? Analysts spend less time digging and more time advising. Legal teams move faster. Risk becomes something you proactively manage, not just something you react to. It’s not about removing humans from the loop. It’s about clearing the noise so they can actually do what they were trained to do.
You can feel the difference. Instead of fragmented alerts and inbox chaos, you get clarity. One connected brain that holds your institutional knowledge and links it to the wider world of regulation. It’s a leap forward, not just for compliance, but for how financial institutions think about information itself.
There’s no silver bullet in this space. But a system that combines structured knowledge, flexible querying, and natural language explanation - backed by a graph that evolves with your business - might be as close as it gets. Compliance doesn’t need to feel like a burden. With the right tools, it can become a strategic asset.
Update: Evolving ArangoDB’s Licensing Model for a Sustainable Future
Estimated reading time: 7 minutes
Updated 3/28/25 for accuracy.
Last October the first iteration of this blog post explained an update to ArangoDB’s 10-year-old license model. Thank you for providing feedback and suggestions. As mentioned, we will always remain committed to our community and hence today, we are happy to announce yet another update that integrates your feedback.
Your ArangoDB Team
ArangoDB as a company is firmly grounded in Open Source. The first commit was made in October 2011, and today we're very proud of having over 13,000 stargazers on GitHub. The ArangoDB community should be able to enjoy all of the benefits of using ArangoDB, and we have always offered a completely free community edition in addition to our paid enterprise offering.
With the evolving landscape of database technologies and the imperative to ensure ArangoDB remains sustainable, innovative, and competitive, we’re introducing some changes to our licensing model. These alterations will help us continue our commitment to the community, fuel further cutting-edge innovations and development, and assist businesses in obtaining the best from our platform. These alterations are based on changes in the broader database market.
Upcoming Changes
The changes to the licensing are in two primary areas:
- Distribution and Managed Services
- Commercial Use of Community Edition
Distribution and Managed Services
Effective version 3.12 of ArangoDB, the source code will replace its existing Apache 2.0 license with the BSL 1.1 for 3.12 and future versions.
BSL 1.1 is a source-available license that has three core tenets, some of which are customizable and specified by each licensor:
- BSL v.1.1 will always allow copying, modification, redistribution, non-commercial use.
- By default, BSL does not allow for production use unless the licensor provides a limited right as an “Additional Use Grant”; this piece is customizable and explained below.
- BSL provides a Change Date usually between one to four years in which the BSL license converts to a Change License that is open source, which can be GNU General Public License (GPL), GNU Affero General Public License (AGPL), or Apache, etc.
ArangoDB has defined our Additional Use Grant to allow BSL-licensed ArangoDB source code to be deployed for any purpose (e.g. production) as long as you are not (i) creating a commercial derivative work or (ii) offering or including it in a commercial product, application, or service (e.g. commercial DBaaS, SaaS, Embedded or Packaged Distribution/OEM). We have set the Change Date to four (4) years, and the Change License to Apache 2.0.
These changes will not impact the majority of those currently using the ArangoDB source code but will protect ArangoDB against larger companies from providing a competing service using our source code or monetizing ArangoDB by embedding/distributing the ArangoDB software.
As an example, If you use the ArangoDB source code and create derivative works of software based on ArangoDB and build/package the binaries yourself, you are free to use the software for commercial purposes as long as it is not a SaaS, DBaaS, or OEM distribution. You cannot use the Community Edition prepackaged binaries for any of the purposes mentioned above.
What should Community users do?
The license changes will roll out and be effective with the release of 3.12 slated for the end of Q1 2024, and there will be no immediate impact to any releases prior to 3.12. Once the license changes are fully applied, there will be a few impacts:
- If you are using Community Edition or Source Code for your managed service (DBaaS, SaaS), you will be unable to do so for future versions of ArangoDB starting with version 3.12.
- If you are using Community Edition or Source Code and distributing it to your customers along with your software, you will be unable to do so for future versions of ArangoDB starting with version 3.12.
- If you are using the Community Edition for commercial purposes you are required to have a commercial agreement with ArangoDB starting with version 3.12.
If any of these apply to you and you want to avoid future disruption, we encourage you to contact us so that we can work with you to find a commercially acceptable solution for your business.
How is ArangoDB easing the transition for community users with this change?
ArangoDB is willing to make concessions for community users to help them with the transition and the license change. Our joint shared goal is to both enable ArangoDB to continue commercially as the primary developer of the CE edition and still allow our CE users to have successful deployments that meet their business and commercial goals. Support from Arango and help with ongoing help with your deployments (Our Customer Success Team) allows us to maintain the quality of deployments and, ultimately, a more satisfying experience for users.
We do not intend to create hardship for the community users and are willing to discuss reasonable terms and conditions for commercial use.
ArangoDB can offer two solutions to meet your commercial use needs:
- Enterprise License: Provide a full-fledged enterprise license for your commercial use with all the enterprise features along with Enterprise SLA and Support.
- Community Transition We do not intend to create hardship for the community users and hence created a 'CE Transition Fund', which can be allocated by mutual discussion to ease the transition. This will allow us to balance the value that CE brings to an organization and the Support/Features available.
Summary
Adjusting our model is essential to ensure ArangoDB’s longevity and to provide you with the cutting-edge features you expect from us. We continue to uphold our vision of an inclusive, collaborative, and innovative community. This change ensures we can keep investing in our products and you, our valued community.
Frequently Asked Questions
1. Does this affect the commercially packaged editions of your software such as Arango Enterprise Edition, and ArangoGraph Insights Platform?
No, this only affects ArangoDB source code and ArangoDB Community Edition.
2. Whom does this change primarily impact?
This has no effect on most paying customers, as they already license ArangoDB under a commercial license. This change also has no effect on users who use ArangoDB for non-commercial purposes. This change affects community edition users who are using ArangoDB for commercial purposes and/or distributing and monetizing ArangoDB with their software.
3.Why change now?
ArangoDB 3.12 is a breakthrough release that includes improved performance, resilience, and memory management. These highly appealing design changes may motivate third parties to fork ArangoDB source code in order to create their own commercial derivative works without giving back to the developer community. We feel it is in the best interest of the community and our customers to avoid that outcome.
4. Is ArangoDB still an Open Source company?
Yes. While the BSL 1.1 is not an official open source license approved by the Open Source Initiative (OSI), we still license a large amount of source code under an open source license such as our Drivers, Kube-Arango Operator, Tools/Utilities, and we continue to host ArangoDB-related open source projects. Furthermore, the BSL only restricts the use of our source code if you are trying to commercialize it. Finally, after four years, the source code automatically converts to an OSI-approved license (Apache 2.0).
5. How does the license change impact other products, specifically the kube-arango operator?
There are two versions of the kube-arango operator: the Community and the Enterprise versions. At this time there are no plans to change licensing terms for the operator. The operator will, however, automatically enforce the licensing depending upon the ArangoDB version under management (enterprise or community).
How ArangGraphML Leverages Intel’s PyG Optimizations
ArangoGraphML + Intel: Next-level Machine Learning Accelerated
ArangoDB and Intel have announced a groundbreaking partnership to enhance Graph Machine Learning (GraphML) using Intel's high-performance processors. This collaboration, part of the Intel Disruptor Program, will seek to integrate ArangoDB's graph database solutions with Intel's Xeon CPU. This synergy promises to revolutionize data analytics and pattern recognition in complex graph structures, marking a new era in database technology and GraphML advancements.
ArangoGraphML
ArangoGraphML, part of ArangoDB's suite, is an advanced graph machine learning platform designed for efficient data analysis and pattern recognition in complex graph structures, leveraging graph database technology to drive innovation in data intelligence and analytics.
Machine Learning Performance Challenge
The quest for speed in machine learning platforms is unending. By delving into Intel’s PyG optimizations, we aim to harness the power of CPU performance enhancements specifically tailored for Graph Neural Network and PyG workloads. As ArangoGraphML is leveraging PyG, any performance improvement is relevant for us and our customers. This exploration is not only about benchmarking Intel’s PyG optimizations but also about internal testing to measure their impact on our platform.
PyG benchmark
Our focus lies on gauging the performance of GraphML algorithms within our platform using torch.compile. This method allows us to assess the efficiency gains brought about by Intel’s PyG optimizations during the training and inference time, providing insights into the tangible benefits for our users.
Benchmark methodology
To ensure a robust evaluation, we conducted tests under controlled conditions:
- System Specifications: We have used an AWS EC2 instance specifically t2.2xlarge with 8 vCPUs and 32 GiB RAM.
- Dataset: We have used ogb-products dataset which is a large-scale undirected and unweighted graph, representing an Amazon product co-purchasing network. The task is to predict the category of a product in a multi-class classification setup, where the 47 top-level categories are used for target labels. This dataset highlights its relevance to real-world scenarios.
- Batch Size, Hidden Layers, and Number of Layers: We have experimented with different essential hyper-parameters in evaluating the performance of GraphML algorithms.
The outcomes
In our preliminary assessments, we observed a noteworthy increase in performance, achieving a speedup of up to 20%. The gains were evident when comparing the execution times of GraphML algorithms with and without Intel’s PyG optimizations. The results are presented graphically in the chart below and summarized in the accompanying table.
| Batch Size | Hidden Channels | Layers | Mode | Median Time per Epoch (in seconds) | Speed up |
|---|---|---|---|---|---|
| 1024 | 256 | 2 | Eager | 153.803 | |
| 1024 | 256 | 2 | Compile | 134.106 | |
| 1.15x | |||||
| 512 | 64 | 2 | Eager | 89.039 | |
| 512 | 64 | 2 | Compile | 98.714 | |
| 1.11x | |||||
| 512 | 128 | 3 | Eager | ||
| 512 | 128 | 3 | Compile | ||
| 1.12x |
Conclusion
With a demonstrated performance boost, we are now leveraging Intel’s PyG optimizations across our platform. This commitment aligns with our dedication to providing users with cutting-edge technology and optimized algorithms for their Graph Neural Network workflows.
As the field of machine learning continues to evolve, ArangoGraphML remains at the forefront, leveraging Intel’s PyTorch Geometric optimizations to ensure our users experience the fastest and most efficient ML platform available.
Stay tuned for further updates on our journey toward excellence in Graph Machine Learning!