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Who we help

Who we help

The companies and industries we work with most, and what we usually end up doing for each. If yours isn't here, the problems probably still sound familiar.

01 / Company types

By company type

  • A small cluster growing by one nodeA Kubernetes cluster runs two nodes with a few pods each. As traffic grows, a third node is added and new pods are scheduled onto it.CLUSTERNODE 1NODE 2NODE 3AUTOSCALING

    Startups & scale-ups

    On-call, security and cost work sized for a small team.

  • A shared pool of GPUs kept busyEight GPUs in a shared pool each show a utilization bar near full, because jobs are queued and scheduled fairly instead of GPUs sitting idle.GPU 0GPU 1GPU 2GPU 3GPU 4GPU 5GPU 6GPU 7GPU POOL · QUEUED JOBS

    AI & ML companies

    Busy GPUs, resumable training and inference that scales.

  • A data center and three clouds joined by one platformAn on-premises data center and workloads on AWS, Microsoft Azure and Google Cloud connect through a shared platform layer that applies the same controls everywhere.DATA CENTERPLATFORMAWSAZUREGOOGLEHYBRID · MULTI-CLOUD

    Mid-market & enterprise

    Migrations and Kubernetes that respect your change process.

  • Several client projects deployed to one platformThree client applications, each once hosted its own way, now deploy to a single shared platform with common pipelines, monitoring and on-call.CLIENT ACLIENT BCLIENT CONE PLATFORMCI/CDMONITORINGON-CALL

    Agencies & ISVs

    Hosting, pipelines and on-call for your client projects.

02 / Industries

By industry

  • Weekly booking demand with capacity following itBars show booking demand across a week, rising sharply on Saturday and Sunday. A capacity line follows demand up for the weekend peak and back down on weekdays.DEMAND AND CAPACITYMONTUEWEDTHUFRISATSUN

    Hospitality & travel

    Peak-season traffic, payment security and quieter off-season bills.

  • Validated and research environments kept apart, with an audit trailA locked, validated environment for regulated systems sits beside a separate research environment with GPU compute. Below them an audit log records each approved change with its author.VALIDATEDRESEARCHCHG-1041 · APPROVED · J.R.CHG-1042 · APPROVED · A.K.

    Pharma & life sciences

    Controlled change for regulated systems, room to explore for research.

  • Two availability zones with a replicated ledgerThe platform runs in two availability zones at once, each with its own application instances. A replication link keeps the ledger in step, so either zone can take all the traffic.ZONE AZONE BSYNCLEDGER

    Fintech

    Uptime, audit trails and answers for due diligence.

  • Patient data redacted from logs before storageApplication log lines pass through a log pipeline where fields containing patient data, such as identifiers, dates of birth and diagnoses, are replaced with redaction blocks before the logs are stored.LOG PIPELINEpatient_id:dob:diagnosis:PHI REDACTED BEFORE STORAGE

    Healthcare

    Patient data protected, clinical systems kept available.

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