The Fastest Data Delivery Solution for Financial Services
Bringing financial teams a low latency, high performance, and scalable storage infrastructure has never been easier
Every Microsecond Saved Translates to Profitability
Financial markets do not wait for anything. Infrastructure failures, slow data access, idle GPUs, metadata bottlenecks and checkpoint surges, mixed training and inference workloads, and overall operational complexity pose immediate and lasting financial consequences. As time to trade expands with slow responding storage, legacy systems fail.
NeuralMesh™ offers consistent and predictable performance during peak market activity
Axon™ provides parallel data access across thousands of compute cores and GPUs
Augmented Memory Grid™ gives the ability to run hundreds of models concurrently on a single data set
When everyone has access to the same historical and real-time data, to gain an edge over the competition, AI financial models require an approach to make training and inference faster, more scalable, and resilient.
NeuralMesh Offers a Modern Storage System for Data Driven Financial Modeling
NeuralMesh delivers an adaptive, unified system that eliminates the data bottlenecks to improve the economics of storage infrastructure.
Run Research Jobs Faster and Make More Money
- The ability to act before markets move
- Instant access to large datasets equals shorter trading windows
- Extreme concurrency to support faster model iteration
- Consistent across peak market conditions using burst-driven approach
Scalable Growth Without Expanding Footprint
- Stronger performance per petabyte, watt, node, and rack
- Power all GPUs and CPUs instead of sitting underutilized
- Lowest cost for exabyte-sized data sets
- Reduce physical footprint with lower power consumption and cooling expenses
Operational Stability and Security Builds Trust
- Built-in resilience with transparent failure handling
- Functions on-premises, in the cloud and in hybrid environments
- Reduced manual burden on infrastructure teams
- Simplified backup, DR and audit trails
Across Financial Services Workloads, NeuralMesh Delivers the Speed to Rise Above the Competition
Across the financial services spectrum, the winners are the companies that can run more models with more complex algorithms, faster. NeuralMesh offers ultra-low latency access for time-sensitive data pipelines, meaning AI teams make decisions faster than the competition.
Quantitative Trading
When 90% of all public market trading leverages quantitative trading algorithms, latency is no longer technical debt, it is lost profitability
High Frequency Trading
Reducing wall clock time with WEKA’s NeuralMesh is guaranteed, allowing organizations to perform large-scale scenario analysis and back-testing that is easier to manage
Fraud Detection & Payments Analytics
Rapid access to transaction data enables financial organizations to detect and respond to financial threats in seconds
Banking Solutions
NeuralMesh with Augmented Memory Grid offers elastic scale for seasonal demand, regulatory requirements, and complex data models
Choose NeuralMesh and Act Before Markets Move
NeuralMesh was built to offer performance that can directly impact algorithmic and high frequency trading (HFT), quantitative research, risk modeling, fraud detection, and other scenarios where infrastructure delays impact financial outcomes. Ready to see what’s possible?
How WEKA Customers are Beating Their Competition
Financial organizations trust NeuralMesh to gain a market advantage. High performance FinServ organizations need real-time access to data to expedite checkpointing, improve high-throughput I/O, and lower total costs, both on-prem and in the cloud. Real world results include:
- 66% reduction in database run time compared to Local NVMe
- 86% reduction in infrastructure cost without giving up performance
- 10x faster than legacy all-flash NAS
“Our existing Network Attached Storage (NAS) was too slow to effectively cover analytics workloads. WEKA proved to be 10× faster and allowed for seamless backup to our object store.”
Common Questions, Straight Answers
Use cases such as high frequency and quantitative trading, risk modeling and simulation, fraud detection, payments analytics, credit and lending platforms, and insurance analytics all require fast, scalable, and reliable access to data.
Storage bottlenecks increase wall-clock times for back-testing, model training, and analytics workflows. In trading environments, this can create latency variability during peak demand times, resulting in reduced GPU and CPU utilization, increased infrastructure costs, and increased AI token costs.
WEKA can accelerate AI inferencing with ultra-low latency, high IOPS, and seamless GPU optimization with infrastructure designed for analytics and AI workloads and optimized for parallel access. This is where WEKA’s Augmented Memory Grid brings significant value.
Financial data growth is exponential, driven by market data, simulations, AI modeling, regulatory retention requirements. Scalable infrastructure platforms like WEKA’s NeuralMesh allow performance and capacity to grow independently and support on-premises, cloud, and hybrid deployments without requiring major re-architecting.
Modern platforms are designed to support encryption and governance requirements common in highly regulated financial services environments. With the WEKApod deployment strategy, it is easy to deploy and scale NeuralMesh with industry-leading price-performance, exceptional density, and turnkey simplicity, all while simplifying the regulatory compliance process for infrastructure management teams.
GPU workloads depend on fast, consistent data access. When storage cannot keep up, expensive GPUs sit idle waiting for input. Enter NeuralMesh Axon and unlock the full potential of your GPUs.
Financial analytics, trading platforms, and AI workloads consume significant power due to GPU-heavy compute environments. To reduce power consumption and deliver higher throughput and IOPS per watt, solutions that spread the load across multiple servers can provide a significant advantage over siloed solutions.
Legacy systems require many nodes, network sports, and rack space. This takes up physical space and increases hardware costs. Deploying a storage platform based on a storage architecture designed for the entire AI lifecycle can reduce storage stalls during both generative AI training and inference cycles.
At scale, hardware failures are unavoidable. Utilizing a distributed platform can help maintain application performance and reduce downtime during hardware failures by removing prolonged degraded states and offering deterministic behaviors under large loads.
Resources
Analytics for Financial Modelling: Fast Wall Clock Time for Better Trading
Want to Accelerate Data and Eliminate Compromise?
Get an inside look at how the NeuralMesh ecosystem can help eliminate latency, maximize GPU and CPU utilization, and cut infrastructure costs so quantitative traders, bankers, and payments organizations can make more money and improve financial outcomes.