Decision intelligence solutions: What is an alternative to Quantexa?

The most successful organizations today are not simply data-centric. They are decision-centric.

Across industries, the key to reducing risk, optimizing operations, and outperforming competitors lies in intelligently leveraging data for faster, more informed decision making. 

To achieve this, it’s not only about bringing together data sources, it’s also about accessing powerful analytics and using AI to augment - or even automate - decision making. For many use cases, these capabilities go beyond just being beneficial; they are essential. 

Take, for example, sanctions screening or environmental, social, and governance (ESG) compliance. These areas require organizations to integrate and analyze data from various sources, tracking and monitoring complex networks of information - be it related to risky entities or supply chains - to effectively manage global risks, meet regulatory requirements, and avoid fines for non-compliance.

As businesses seek to harness the power of their data for smarter decisions, they're turning to advanced decision intelligence solutions. Decision intelligence is an emerging field that combines multiple technologies to support and enhance decision-making processes within organizations. This innovative approach integrates traditional business intelligence with advanced disciplines such as entity resolution, predictive analytics, network analytics, and collaborative technologies.

The rapid expansion of the decision intelligence market is no surprise, given the increasing complexity of business decisions. According to Gartner, 76% of IT and CIO leaders agree that decision-making has become more complex in recent years, highlighting the need for sophisticated solutions.

One of the key players in this growing market is Quantexa. Their contextual decision intelligence platform combines technologies like AI, entity resolution, and network analytics and visualization to empower decision-makers with comprehensive insights.

While Quantexa remains a robust solution for the largest enterprises, alternative solutions like Linkurious’ graph native decision intelligence platform have emerged to overcome the shortcomings of Quantexa and open new avenues for intelligent decision making. 

In this article, we'll explore how these platforms compare, focusing on key factors such as total cost of ownership, scalability, and adaptability—all crucial considerations for organizations looking to enhance their decision-making capabilities.

Total cost of ownership (TCO) is going to be a key consideration when adopting a decision intelligence system. You’re adding a new type of system on top of what is likely an already complex tech stack, so it’s important to be able to control the budget and the cost to benefit ratio over time.

The decision intelligence market is also still emerging. In this context, there are various approaches to decision intelligence systems that may not be completely streamlined, generating hidden costs that can impact the TCO.

In the case of Quantexa, the TCO is notably high. While Quantexa’s license itself comes with a significant price tag, there are additional hidden costs that organizations must consider. Not included in the initial price are the underlying technologies necessary to run Quantexa. These include licenses for Elastic, Spark - or a cloud native alternative - and your database of choice, all of which add to the overall expense.

Furthermore, organizations must factor in data costs, professional services for implementation and training, and support services not only for Quantexa but also for the other underlying technologies.

There are also operations costs - to support and maintain the environments - as well as compute and storage costs to take into account. When all these elements are combined, the total cost becomes substantial.

As an alternative to Quantexa, the Linkurious integrated solution offers a more cost-effective approach.

To deliver powerful contextual decision intelligence capabilities, the open and modular infrastructure consists of 3 main standalone, off-the-shelf components: an entity resolution AI, a native graph database, and a graph visualization and analytics user interface. All come with transparent and predictable license costs. An organization can also capitalize on its existing graph database. 

This streamlined architecture also means the Linkurious solution consumes fewer resources and is faster and easier to deploy, support, and maintain.

Overall, Linkurious provides organizations with a clearer understanding of their investment and potentially lower and more manageable expenses so they can keep control of their budget over time.

Quantexa's platform seems to be well-suited for very large projects. However, given its high TCO, the cost becomes a significant burden - and may even be prohibitive - for smaller projects or organizations looking to rationalize the value for money of their investments.

This lack of flexibility in scaling down can be a major drawback for many organizations.

But what if you need to start small before scaling up or expanding? In such scenarios, the ability to adjust your decision intelligence solution to fit your current needs becomes crucial.

The Linkurious decision intelligence solution offers this flexibility. It's designed to accommodate both large and small projects efficiently.

For instance, it's possible to leverage your existing graph database or replace certain paid licenses with free ones or community editions, allowing you to optimize your investments or quickly reduce costs if necessary.

At the same time, Linkurious decision intelligence can comfortably handle projects involving hundreds of users and a large scale dataset unifying data from a large number of sources. This scalability ensures that organizations can start small, grow at their own pace, and adjust their decision intelligence capabilities according to their evolving needs and resources.

Entity resolution is a crucial functionality in combining disparate data sources, identifying duplicates, and enabling accurate analysis. It's a key component in decision intelligence platforms, allowing organizations to create a unified view of their data and ensure a solid data foundation.

Entity resolution is a core part of the Quantexa platform. Quantexa employs dynamic entity resolution. Firstly, users create ETL jobs to standardize and transform their data which is then mapped to common properties used in the entity resolution process (such as name, address, DOB). These are stored in a search index. Quantexa uses pre-built compound rules to perform probabilistic entity resolution against data stored in the search index to generate dynamic networks (sub-graphs) which can be exported to files or queried dynamically in the Quantexa UI.

However, this approach presents several challenges.

Firstly, the creation of these small sub-graphs makes it difficult or even impossible to query the whole graph together. Quantexa does provide the ability to resolve and generate larger networks but these are computationally expensive and persisted in large files which are difficult to query. This limitation can hinder comprehensive analysis and restrict the ability to uncover complex relationships across the entire dataset.

Additionally, the requirement to standardize the data pre-entity resolution also adds overhead and complexity to the engineering process.

In contrast, Linkurious takes a different approach to entity resolution. Similar to Quantexa, the data is mapped to a configurable entity specification. However, there is no requirement to standardize the data itself. Data such as addresses, countries, names, DOBs and even the language of the source data are automatically standardized by the process, significantly reducing integration time and data engineering effort. 

This data is then passed in real-time through the principle-based entity resolution process. Principles are essentially rules which define the behavior of an attribute e.g. a name can be shared by many people but a social security number should belong to one person. The entity resolution results are persisted in real-time into a native graph database.

Crucially, this process is AI-powered and automatically assesses the impact of any data change on previously resolved data, providing the ability to unresolve previously resolved entities based on new information. 

Maintaining data in a fully entity-resolved native graph database significantly improves the analytical performance on the resulting graph. By avoiding the creation of multiple sub-graphs, Linkurious allows for more efficient querying and analysis of the entire dataset as a whole. Linkurious can also leverage native graph algorithms which are proven to be more performant on well modeled, native graph data. 

This scalability in graph analysis enables organizations to gain deeper insights from their data, uncovering patterns and relationships that might be missed when working with fragmented sub-graphs.

As soon as you decide to adopt a decision intelligence solution, you’re pouring resources into getting it up and running. Besides that, if you’ve decided your organization needs decision intelligence, the sooner your tool is operational the sooner you’ll be able to reap the benefits - and start getting a return on your investment. The time to operationalization, then, is a key point of consideration.

Operationalizing Quantexa can be a complex process. As we mentioned in previous sections, there are underlying technologies such as Elastic and Spark that must be set up and configured, in addition to the Quantexa software itself. It’s also complex to build on the Quantexa platform, meaning any customization can add significant time to the setup. Finally, training users on the platform is also time consuming.

As an alternative to Quantexa, Linkurious decision intelligence can be deployed faster, since the platform is built on off-the-shelf, fully configurable modules. Organizations relying on Linkurious benefit from a truly open platform that is easy to integrate into existing tech stacks via built-in connectors, APIs, and webhooks. And, a user-friendly interface and on-demand trainings help accelerate the adoption of the platform by users without a technical background.

An important consideration when choosing a decision intelligence solution is how well it can grow and adapt to meet the evolving needs of your organization. Will you need to change the data model, add new data sources, introduce a new use case or create new integrations as your requirements shift? What if you need to change a core component (like a database), integrate new third-party systems, or need to take into consideration new IT security requirements?

Quantexa features a low-code ETL (Extract, Transform, Load) layer that reduces the amount of minor detail work required when creating simple integrations.

However, creating a new integration in Quantexa may still require substantial effort and can take many months to complete if the level of standardization and transformation of the data is complex and will require coding skills in supported languages.

Additionally, the tight integration between Quantexa and the underlying database, index and compute layers makes it difficult to change these components should the need arise. 

Finally, the Quantexa architecture supports multiple use-cases where both data and infrastructure can be reused. However, users are constrained by the Quantexa license model which is aligned to use-case. This makes it more costly to unlock enterprise-wide benefits and promote reusability from your intelligence platform.

The exceptional openness and configurability of Linkurious decision intelligence solution, on the other hand, offers significantly more flexibility in this regard.

Linkurious integrates with several leading native graph databases, can be deployed on any cloud or on-premise infrastructure and offers complete flexibility on how data should be integrated and modeled. New integrations can typically be deployed in a matter of weeks, making it much easier to adapt the solution in a timely manner. This agility allows organizations to respond quickly to new requirements or opportunities.

The Linkurious solution also offers a fully scalable and flexible licensing model which is based on the number of users and data volumes, meaning organizations can start small and scale up. For more complex requirements, with no licensing restrictions a single deployment can be used for multiple use cases.

With Linkurious, you run less risk of falling behind as your needs evolve. The ability to implement changes and integrations rapidly ensures that your decision intelligence capabilities remain aligned with your current business objectives and data landscape.

While both Quantexa and Linkurious offer powerful decision intelligence solutions, we've seen that Linkurious provides distinct advantages in terms of cost-effectiveness, scalability, and adaptability. Its flexible architecture, transparent pricing, and rapid integration capabilities make it an attractive option for organizations of all sizes, from those just starting their decision intelligence journey to large enterprises seeking a more agile solution.

To discover how the Linkurious decision intelligence solution can transform your organization's decision-making processes and help you stay ahead in an increasingly complex world, check out our product page.