Yes, CryspIQ® can operate alongside your existing data platform, allowing you to begin realising its cost-saving benefits. As a transitional approach, you can make use of your current data layers by redirecting data into CryspIQ®. For example, you can utilise your existing 'Raw' or 'Staging' layer and map the data from there into CryspIQ® for consumption. Please refer to the architecture documentation for further details.

CryspIQ® does not necessarily replace your existing data platform — it’s designed to complement and enhance what you already have. Here’s how: Accelerates value from your current data stack by enabling natural language access to data. Reduces reliance on manual processes, SQL, or technical bottlenecks — letting business users get answers faster. Optimises costs by minimising unnecessary data movement, storage, or compute, even across legacy systems. Integrates flexibly with common data platforms like Snowflake, BigQuery, Databricks, Azure, and more. If you're starting from scratch, CryspIQ® can also act as a lightweight front-end to manage and extract insights from raw or siloed data — but in most enterprise setups, it works alongside existing investments, not in place of them.

CryspIQ® is designed to be scalable and flexible, making it suitable for both small businesses and large enterprises. For small and medium-sized businesses, CryspIQ® offers a cost-effective way to regain control of their data without needing large teams or complex infrastructure. Its simplified architecture, minimal transformation steps, and focus on business-relevant data help reduce overheads and accelerate time to value. For large enterprises, CryspIQ® scales to handle complex data environments, high volumes, and regulatory needs—while still offering cost savings and faster analytics delivery. In short, whether you're just starting to get your data under control or you're modernising an existing data estate, CryspIQ® can adapt to your needs..

Yes, CryspIQ® stores only the business-relevant data from your source systems, delivering up to 80% savings in compute and storage costs.

Yes, CryspIQ® enforces Role-Based Access Control (RBAC) across all your data and integrates with the Azure Entra ID framework to manage authentication and access rights. Access is controlled down to the field level, ensuring users can only view the data they are authorised to see, regardless of the queries they run.

CryspIQ® organises all your business data within a single database schema, clustering similar data types together to make them easy to locate and use. For example, if you're searching for financial figures such as budget amounts, invoice totals, or payment values, you'll find them all stored in one central location.

PPL represents the evolution of ETL. The key difference with PPL is that data preparation occurs directly on the incoming source data and is completed before it is loaded into CryspIQ®. This approach enables real-time, streamed data loading if needed, rather than relying on traditional batch processing methods

Yes, CryspIQ® enables you to regain control of your data swamp and gradually transition away from your existing Data Lake or Lakehouse. This allows you to deliver a seamless user experience while streamlining and cleaning up your back-end systems. CryspIQ® stores only the business-relevant data from your source systems.

Any output that can be produced in a tabular format - Databases, Rest APIs, flat files etc. Please refer to System Plug-ins Library documentation for more information.

Yes, this is a key advantage of implementing CryspIQ®. It is entirely agnostic to the source system from which the data originates. You can retain historical data from legacy systems through existing mappings, and when a new system is introduced, you simply create new mappings for the incoming messages. There's no need for major end-to-end rebuilds, and your historical data remains intact, ensuring continuity from an analytics standpoint.

CryspIQ® enforces data quality checks before data enters the model, ensuring only high-quality information is made available to consumers. By streamlining the data delivery process and removing unnecessary layers and handling steps, it minimises inconsistencies from interpretation or transformation and standardises the removal of duplicate records.

Yes, CryspIQ® is fully capable of managing the volume, velocity, and variety associated with Big Data, and can be configured to utilise industry-standard technologies such as Apache Hadoop on any cloud platform. When set up for Big Data, users can achieve results that match or exceed those of a relational storage engine, while also benefiting from optimised storage costs thanks to the underlying Big Data infrastructure. Please note that the Big Data configuration is an optional add-on to the standard CryspIQ® offering.

CryspIQ® is highly flexible and can be hosted on a range of database environments to suit your infrastructure preferences. It supports deployment on cloud-native platforms such as Microsoft Azure, AWS, and Google Cloud, and is compatible with industry-standard database engines including SQL Server, PostgreSQL, and Big Data technologies like Apache Hadoop. This ensures you can integrate CryspIQ® into your existing environment with minimal disruption while leveraging the scalability and performance of your preferred platform.

Yes, CryspIQ® is industry-agnostic and can be applied across a wide range of sectors. Whether you're in finance, healthcare, manufacturing, retail, or the public sector, CryspIQ® is designed to work with your existing systems and data structures, delivering faster insights, improved data quality, and significant cost savings. Its flexibility and scalability make it suitable for any organisation looking to unlock more value from their data.