Infrastructure performance
Throughput — before
Throughput — with argentic
Same pipeline. Same data. Same infrastructure.
Measured results. See the data sheet.
The more my data grows, the narrower my pipelines' windows into the data become, the less accurate my results, and the harder my data is to move. Scaling infrastructure is not the answer. Software is.
argentic runs inside the infrastructure already deployed: Spark, Hadoop, and others. No data migration. No pipeline rewrites. No new hardware. The same cluster processes significantly more data, achieving throughput beyond what stock Spark reaches— across workloads, and without the scale-out costs.
your stack
→
argentic
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Step change
Under the hood.
Data sovereignty, retained.
argentic accelerates in place. No separate cluster, no custom hardware, no migration path, no additional I/O. Retain industry compliance (FINMA, DORA), retain valuable data confidentiality.
Graph and irregular data, on one platform.
argentic is structure-agnostic: it makes no assumptions about the shape of your data. Its irregular computation engine, based on GraphBLAS, automatically parallelises and scales your workloads.
Data locality, capitalised.
argentic changes how data and work are distributed across your infrastructure. Through improved locality, nodes perform more useful work, driving the resulting step change in throughput.
Learns from usage. The advantage compounds.
argentic adapts to your data and your workloads— every run refines its partitioning and scheduling. Spark and Hadoop cluster utilisation rises, cost does not: same infrastructure, more data.
What argentic is not.
argentic is not a replacement for Spark, Hadoop, etc. It runs inside them, with no migration required.
argentic is not incremental. It claims improved infrastructure efficiency at one order of magnitude*.
argentic is not either cloud or on-premise. It scales equally well on both.
* For exact figures, baselines and cluster configuration, request the data sheet.
Rising utilisation. Falling cost.
Beyond improving your infrastructure's throughput, argentic learns from your workloads. The resulting compound gap cannot be closed by switching platforms— it can only be earned, by using argentic.
Data analysis requires regular and irregular computations, on structured and graph-shaped data. Today, this means two separate, incompatible tools— doubling infrastructure and scaling costs. argentic unifies both.
Making irregular, graph-shaped workloads run fast and scale out requires rare algorithmic and system expertise. Building custom solutions means redirecting your best engineers for years toward infrastructure, instead of the problem you set out to solve.
The compound advantage is part of why an early design partnership matters. What is shaped in the first months accrues for years.
Built for.
Financial services:
regulated data infrastructure
Data accumulating faster than infrastructure scales. Fraud and counterparty graphs requiring ever-larger clusters and narrower analytics windows. Outsourcing obligations (FINMA, DORA) make migration burdensome and in-place throughput gains valuable.
Life sciences:
sensitive data infrastructure
Genomic and clinical data accumulating faster than infrastructure scales. Drug-target networks requiring more capacity with each expansion— or narrower analysis than the research demands. Sensitive proprietary data, where on-premise scaling is the natural fit.
Retail and media:
real-time data infrastructure
Recommendation engine scaling that demands larger clusters as catalogue and user base grow. Real-time serving built on increasingly rough approximations as full-graph analysis becomes cost-prohibitive. A resource footprint that grows faster than the business justifies.
argentic is selecting a small number of enterprises as design partners— one to three, to begin.
This is not a sales process. It is an invitation to shape what gets built, from the inside, before anyone else has access to it.
We are reviewing registrations, with particular interest from financial services, life sciences, retail, and media organisations.
As an early-stage partner, you get
Early access ahead of general availability
Direct access to the team
Input into the product roadmap
Preferred terms as the platform matures
A head start on the compounding advantage.
the data sheet.
Our latest data sheet: throughput gains by workload class, with baselines and cluster configuration. Your email is all we need.