Asset Management Digital Solutions

Modernize your investment engine.

Data-driven success for asset managers

Intellias supports financial institutions with asset management technology consulting services and digital solutions. Today’s investors are savvier about selecting asset management services. Achieving their trust raises the value of assets under management (AUM), and it starts with a strong data strategy. Yet AI-driven asset management solutions at asset management investment firms often operate in silos. Each has different settlement cycles and varying data quality levels. Moreover, without advanced data governance and real-time analytics, compliance continues to erode margins. Our high-performance asset management digital solutions and modern data platforms help asset managers achieve data-driven success.

Trusted by leading companies worldwide

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Our capabilities

Our asset management technology consulting services will unshackle legacy constraints. Intellias designs and builds AI-driven data and analytics solutions to meet the needs of financial asset managers.

Modern data platform engineering

We offer AI-enabled data platform services as the backbone of investment operations. This includes the transition from rigid architectures to flexible data lakes and data lakehouses. Using a modern data platform, Intellias ensures that your data is accessible and scalable for high-performance computing. Our engineering work focuses on modernizing data pipelines to handle the high-volume, high-frequency requirements of modern markets.

AI and machine learning development

Our AI/ML development services include automation, but much more. We build predictive models that help investment analysts and portfolio managers identify details in alternative data sets. We specialize in AI and data integration, ensuring that your models are trained with high-quality, well-governed information. This includes the deployment of AI agents and agentic AI systems. Among its benefits, agentic AI can perform complex research tasks and middle-office reconciliations without manual intervention.

Comprehensive data management

Effective data management is the prerequisite for any successful AI initiative. We provide data and analytics frameworks that cover the entire data lifecycle. Intellias implements data governance and advanced protocols to ensure data integrity. We also focus on data quality by deploying automated observability tools that catch errors before they impact your trading or reporting.

Cloud and solution migration

For firms using on-premise environments, we provide end-to-end cloud migration and data solution migration services. We move your workloads to secure, compliant cloud environments that offer the elasticity needed for advanced analytics. Whether you are moving a legacy security master or a complex risk engine, our migration strategies minimize downtime and ensure data consistency.

Analytics and consultation

We provide many analytics services, including analytics implementation, that turn data into actionable intelligence. Our solutions include real-time analytics for monitoring market exposure and data clustering for sophisticated risk modeling. We help financial institutions build intelligent dashboards that provide a 360-degree view of their portfolios and client behaviors.

Data strategy

Modern asset management requires a strong data strategy. At Intellias, we build data frameworks that align with your business goals. Our approach involves defining data governance policies. By focusing on scalable data architectures, we help financial institutions make the most of their data assets and improve efficiency.

AI strategy

Our AI strategy focuses on integrating systems that enhance decision-making and operational efficiency. Intellias develops AI solutions customized to the unique needs of asset management firms, from predictive analytics to automated workflows. We focus on creating AI models that are not only accurate but also adaptable to changing market conditions. By embedding AI into your processes, we help you stay ahead of the curve and deliver smarter investment strategies.

Case studies

Smart data management

A Tier-1 US bank client faced many data management challenges that led to slow and inefficient onboarding of new data, limited access to real-time data, and weak data governance. Intellias developed a unified platform on AWS. The modern, cloud-based platform offered:

  • 60% faster onboarding of new data sources.
  • 40% faster time-to-market for analytics and reporting products.
  • 70% less time spent searching for data.
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Case studies

Operational data exchange platform

Travis Perkins was using a legacy eCommerce platform that was restricting its ability to adapt to market changes. It also could not offer personalization. Intellias developed a headless eCommerce system that improved customer experience. The platform:

  • Had a 99.9% uptime availability.
  • Provided more efficient, scalable deployment.
  • Achieved a 30% cost reduction and a 50% decrease in maintenance expenses.
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Case studies

‘Lift and shift’ migration

A global payment products developer and services provider was using an outdated, on-premises PostgreSQL data warehouse that was inefficient and risky. Intellias migrated the company to a cloud-based database on AWS capable of withstanding peak data loads. The AWS solutions:

  • Automated security controls and centralized logging.
  • Reduced business continuity risks with a data recovery strategy.
  • Achieved a 50% cost reduction in infrastructure spending.
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Case studies

Data technology assistance

An expensive technology decision at a private aviation company resulted in data management policies that were inefficient. Intellias developed a new data warehouse and migration plan for the company, which files 350 charter aircraft worldwide. The data migration:

  • Saved about $24 million by avoiding excess commodity purchases.
  • Improved operational efficiency, optimized resources, and enhanced scalability.
  • Reduced data management costs
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Our approach

Intellias believes that a data strategy is a prerequisite for competitive relevance. Our approach is rooted in the principles of Data Mesh, focusing on domain ownership and data as a product.

Domain decomposition and strategy

We begin by defining a sensible data strategy that aligns with your business outcomes. Intellias categorizes your data into logical domains—such as market data and trade data—and assigns ownership. This phase includes implementing data governance standards that will scale with your organization.

Federated delivery and platform build

Instead of a monolithic “big bang” approach, we use federated delivery. We build a modern data platform on cloud infrastructure, using data lakes or data lakehouses to centralize access while allowing individual groups to manage their own data products. This stage involves modernizing data pipelines to ensure a steady flow of high-quality information.

Automation and AI readiness

Intellias focuses on automating data quality and lineage. This creates an agentic AI-ready environment. We deploy AI agents to handle reconciliation data-cleansing routines.

Value iteration and scaling

We deliver value in short, measurable cycles, whether it is improving real-time analytics for a specific desk or completing the migration for a legacy system.

Why Intellias?

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Deep domain expertise

We understand the complexities of asset management investment firms, from different settlement cycles to the nuances of ESG data.

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Technical sophistication

Our team is at the forefront of AI and machine learning, specifically as it applies to financial markets and financial institutions.

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Outcome-focused

Our success is measured by your ability to manage assets and reduce operational overhead, not just by the delivery of code.

FAQs

The first step is defining a data strategy. This assesses your current data management maturity level and identifies the business outcomes that will drive the most value. We then create a roadmap for modernizing legacy systems.

We use data clustering, AI, and machine learning to harmonize data from multiple vendors. By implementing data governance at the source, we ensure that your ESG disclosures are accurate and fully traceable.

Traditional automation follows fixed rules. AI agents and agentic AI use predictive logic to handle ambiguity and make decisions. For example, an AI agent can identify a data mismatch, investigate the source, and propose a fix, rather than just flagging an error.

We implement automated data quality checks within your modernized data platform. This includes real-time observability and alerts, ensuring that real-time analytics are always based on accurate information.

Yes. Intellias ensures that all data platforms meet or exceed regulatory security standards.

Let’s talk

Looking for clarity, strategy, and hands-on delivery? Our experts are ready to help you get results. Whether you’re planning your next big initiative or looking for a trusted tech partner, we’re here to help you move forward with confidence.

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