{
  "slug": "netris",
  "name": "Netris",
  "description": "Netris provides a network automation and multi-tenancy platform purpose-built for AI cloud operators. It delivers cloud-provider-grade network automation, abstraction, and multi-tenancy across the entire AI networking stack, including Ethernet, InfiniBand, NVLink, DPUs, Virtual, and Edge Networking.",
  "url": "https://optimly.ai/brand/netris",
  "websiteUrl": "https://netris.io/",
  "logoUrl": "https://logo.clearbit.com/netris.io",
  "baiScore": 57.5,
  "bai_tier_status": "active",
  "bai_score_status": "active",
  "archetype": null,
  "archetype_status": "active",
  "category": "AI Network Optimization Platforms",
  "categorySlug": null,
  "keyFacts": [],
  "aiReadiness": [],
  "competitors": [],
  "competitorsProse": null,
  "inboundCompetitors": [],
  "aiAlternatives": [],
  "parentBrand": null,
  "subBrands": [],
  "updatedAt": "2026-09-25T04:52:28.848Z",
  "verifiedVitals": {
    "website": "https://netris.io",
    "category": "Network Automation and Multi-Tenancy Platform for AI Cloud Operators",
    "what_it_does": "Netris is a network automation and multi-tenancy platform designed for AI cloud operators to maximize GPU utilization and manage complex AI networking stacks, including Ethernet, InfiniBand, NVLink, DPUs, Virtual, and Edge Networking. It provides cloud-provider-grade network automation, abstraction, and multi-tenancy capabilities.",
    "primary_audience": "AI Cloud Operators, AI infrastructure operators, cloud providers",
    "core_product": "A platform that delivers cloud-provider-grade network automation, abstraction, and multi-tenancy for AI infrastructure, offering features such as VPCs, peering, elastic IPs, and load balancers.",
    "pricing_model": {
      "kind": "custom",
      "detail": "Pricing is determined by the number of units or nodes running the software, and is typically handled through contact sales."
    }
  },
  "intentTags": {
    "problemIntents": [
      "Difficulty in maximizing ROI of GPU infrastructure",
      "Challenges and costs of building in-house network automation solutions",
      "Fragile, expensive, and time-consuming in-house network maintenance",
      "Traditional network controllers being unfit for AI workloads (lack of NVIDIA switch/DPU support, InfiniBand/NVLink integration, cloud-provider essentials like elastic IPs/load balancers)",
      "Soft isolation methods (VMs, containers) not providing true, secure multi-tenancy",
      "Risks of software vulnerabilities and container escapes with soft isolation",
      "'All-in-one' platforms lacking the specialization and depth required for complex AI networking",
      "Delays, outages, and compliance risks stemming from inadequate networking foundations",
      "Vendor lock-in when tied to bundled compute or AIOps stacks"
    ],
    "solutionIntents": [
      "Network automation for AI clouds",
      "Multi-tenancy platforms specifically for AI cloud operators",
      "Cloud-provider-grade network automation, abstraction, and multi-tenancy capabilities",
      "Hardware-level isolation for secure and reliable multi-tenancy",
      "Accelerating AI cloud launch and streamlining operational processes",
      "Eliminating human errors in network configuration and management",
      "Delivery of AWS-style networking constructs (VPCs, peering, elastic IPs, load balancers)",
      "Equalizing AI networking across diverse and complex architectures",
      "Integration with various ecosystem platforms (IaaS, PaaS, GPU aggregators)",
      "Future-proofing AI infrastructure while avoiding vendor lock-in",
      "Maximizing GPU utilization and enhancing revenue generation potential",
      "Reducing CapEx and OpEx for AI infrastructure deployments"
    ],
    "evaluationIntents": [
      "Comparison of network automation solutions (e.g., in-house, traditional SDN, Netris)",
      "Evaluating the return on investment (ROI) for GPU infrastructure investments",
      "Assessing multi-tenancy security and isolation capabilities (hardware-level vs. software-level)",
      "Evaluating cost implications (CapEx, OpEx) of different networking solutions",
      "Measuring time to production and deployment speed for AI clouds",
      "Assessing vendor lock-in risks in AI infrastructure strategies",
      "Evaluating network performance and reliability for critical AI workloads"
    ]
  },
  "businessProfileClaims": [],
  "timestamp": 1790399219720
}