Rapt AI
Rapt AI is a private US-based software company that sells a model-defined GPU optimization platform for AI inference workloads. It dynamically allocates GPU resources across multi-cloud environments to improve utilization and reduce compute costs for enterprise AI teams.
- Company typePrivate
- Founded-
- HeadquartersSanta Clara, United States
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
What Rapt AI does
Rapt AI operates a model-defined GPU optimization platform designed to improve the economics of AI inference workloads. The platform reads the real-time resource requirements of each inference model — across prefill, decode, KV cache, and variable-length stages for LLMs, as well as vision, audio, video, and embedding workloads — and dynamically reallocates GPU compute, memory, and bandwidth to eliminate idle capacity. According to the company's reported metrics, the platform sustains 98%+ GPU utilization versus an industry baseline near 35%, enabling roughly 3.8x–10x more inference workloads on the same hardware and a 90% reduction in GPU infrastructure spend. The product portfolio includes the core Rapt.AI Platform, an Enterprise GPU Optimization module for multi-team and multi-cloud fleets, a Multi-Tenant GPU Infrastructure offering that enables cloud providers to deliver GPU-as-a-Service, and an Interactive Demo Playground. Native integration with Kubernetes, support across AWS/GCP/Azure and on-premise environments, and optimization for NVIDIA (H100, A100, L40S, B200, B300, GB10), AMD Instinct, and HPE hardware form the technical footprint.
The company sells primarily to enterprise AI and infrastructure teams running production inference at scale, with disclosed verticals spanning healthcare and pharma, financial services, aerospace and defense, enterprise technology, contact center AI, and data/AI platform providers. Revenue is generated through quote-based annual or multi-year subscriptions, optional usage-based components tied to measured GPU utilization improvements, and implementation/professional services. Go-to-market combines a product-led growth motion (interactive demos, playground tools, self-serve ROI calculator) with an enterprise field sales motion targeting Fortune 500 organizations, supported by channel partners including WWT and Cambridge Computer. The company is headquartered in the Silicon Valley area (Cupertino/Santa Clara), has 11-50 employees, and is backed by HalfCourt Capital and Aspen Capital Group with Charlie Leeming as CEO and founder Anil Ravindranath as CTO.
Rapt AI firmographics
Firmographics- Name
- Rapt AI
- Legal name
- Rapt.AI
- Website
- https://rapt.ai
- Company type
- Private
- Operating status
- Operating
- Headcount range
- 11–50 employees
- Short description
- Rapt AI is a private US-based software company that sells a model-defined GPU optimization platform for AI inference workloads. It dynamically allocates GPU resources across multi-cloud environments to improve utilization and reduce compute costs for enterprise AI teams.
- Ownership category
- akta.pro rank
Rapt AI industry classification
Industry- Product category
- AI Infrastructure / GPU Optimization
- NAICS
- Software Publishers (513210), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518)
- SIC
- Services-Prepackaged Software (7372)
- akta.pro primary industry
- AI Compute Virtualization & Scheduling (GPU virtualization, cluster schedulers) (HDAAAAAG)
- akta.pro secondary industries
- Model Deployment, Serving & Inference Platforms (HDAAABAF), Model Hosting, Serving & Inference Platforms (HDAAACAB), Model Serving, Inference & Deployment Platforms (APIs, Edge/On-Prem) (HDAEANAC), AI Compute Cloud & GPU-as-a-Service (HDAAAAAK)
Keywords
Where Rapt AI is headquartered
LocationHeadquarters
- HQ city
- Santa Clara
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
Rapt AI business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Technology or R&D, Personnel, Marketing or Sales, Operations, Infrastructure
Revenue model
- Software Platform Subscription: Annual or multi-year subscription-based pricing model for access to the Rapt AI GPU optimization platform. Pricing is quote-based and scales with GPU fleet size and utilization metrics.
- Usage-Based GPU Optimization Fees: Potential consumption-based component tied to measured GPU utilization improvements or workload throughput gains on customer infrastructure.
- Professional Services: Implementation and onboarding services for enterprise customers deploying the platform across multi-cloud GPU environments.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Subscription | Annual | Enterprise subscription with custom pricing |
| Hybrid | Pay-as-you-go | Pilot Program |
Go-to-market motion3 records
Distribution channels3 records
Marketing channels6 records
Rapt AI product offering
Product offeringCore offering
Rapt AI sells a model-defined GPU optimization platform for AI inference workloads. The platform continuously reads each AI model's compute, memory, and bandwidth requirements and dynamically reallocates GPU resources in real time across multi-cloud (AWS, GCP, Azure) and on-premise environments, achieving 98%+ utilization versus the ~35% industry baseline. It is delivered as a subscription software platform with enterprise pilots, professional services onboarding, and supporting solutions for cloud providers offering GPU-as-a-Service.
Product overview
Rapt.AI is a model-defined GPU optimization platform designed for AI inference workloads. The core platform provides dynamic GPU resource allocation based on real-time model demand, supporting prefill, decode, KV cache, and variable-length workloads. The product portfolio includes the core Rapt.AI Platform for general GPU optimization, Enterprise GPU Optimization for multi-team/multi-cloud fleet management, Multi-Tenant GPU Infrastructure for cloud providers enabling GPU-as-a-Service offerings, and an Interactive Demo Playground for hands-on demonstration. The platform integrates natively with Kubernetes and supports H100, A100, L40S, B200, B300, and AMD Instinct GPUs across AWS, GCP, Azure, and on-premise environments.
Differentiator
Problem solved
Functional benefit
Products and services
- Rapt.AI Platform Model-defined GPU optimization platform for AI inference workloads that reads each model's compute, memory, and bandwidth requirements and right-sizes GPU resources in real time. Supports prefill, decode, KV cache, and variable-length workloads across LLMs, vision, audio, video, and embedding models, with full multi-modal coverage and native Kubernetes integration. Designed for enterprise AI/ML teams and infrastructure leads running production inference at scale.
- Enterprise GPU Optimization Enterprise-focused GPU optimization solution delivering 98%+ utilization across multi-cloud and on-premise GPU infrastructure with real-time cost attribution per team and per workload, intelligent GPU configuration, and deployment in minutes alongside existing Kubernetes clusters. Built for large organizations with multi-team AI infrastructure and finance/operations cost-tracking needs.
- Multi-Tenant GPU Infrastructure for Cloud Providers GPU-as-a-Service platform enabling cloud providers to deliver multi-tenant GPU infrastructure with usage-based pricing (per token, per image, per request), dynamic resource allocation, and increased tenant density without sacrificing isolation or performance. Designed for hyperscalers, neoclouds, and specialized GPU cloud providers reselling GPU compute to end customers.
- Autonomous AI Infrastructure Platform Next-generation autonomous AI infrastructure platform integrating Massed Compute's GPU management capabilities with Rapt AI's optimization engine to create self-managing GPU environments for AI workloads with real-time self-optimization. Targeted at enterprise and cloud-provider customers seeking fully autonomous GPU fleet operations.
Quantifiable outcome
- 98%+ GPU utilization achieved versus 35% industry average
- +5 more outcomes
Companies that use Rapt AI
Customer profileNamed customers6 records
Segments4 records
Ideal customer profiles3 records
Rapt AI technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- No
- API docs
- API detail
Core technology
AI maturity
App detail
Integration1 record
AI capability8 records
Feature5 records
Rapt AI partnerships and signals
Strategic signalPartnerships
Seven partnerships are on record, tiered core, supporting and flagship.
- NVIDIAcoreRapt AI is a member of the NVIDIA Partner Network with optimization capabilities for NVIDIA GPU architectures including the GB200 NVL72 systems. The partnership enables deployment of Rapt AI's GPU optimization platform on NVIDIA infrastructure.
- HPEcoreRapt AI participates in the HPE Partner Ready program, integrating GPU optimization capabilities with HPE infrastructure solutions for enterprise AI deployments.
- WWT (World Wide Technology)coreWorld Wide Technology serves as a channel partner and systems integrator for Rapt AI's GPU optimization platform, providing implementation and deployment services for enterprise customers.
- Cambridge ComputersupportingCambridge Computer is a partner in Rapt AI's distribution ecosystem, facilitating enterprise sales and deployment of GPU optimization solutions.
- Massed ComputeflagshipStrategic partnership announced at SuperCompute 2025 to develop autonomous AI infrastructure capabilities. The collaboration integrates Massed Compute's GPU management expertise with Rapt AI's optimization platform to create self-managing GPU environments for AI workloads.
- HMCI (Human Machine Collaboration Institute)flagshipRapt AI is deploying NVIDIA GB10 systems in partnership with HMCI at their Rancho Cordova facility. This partnership supports the development of next-generation AI compute infrastructure with Rapt AI's optimization layer on advanced NVIDIA hardware.
- AMDcoreStrategic collaboration with AMD for AI workload management on AMD Instinct GPUs. Rapt AI provides optimization capabilities specifically tuned for AMD GPU architectures, enabling customers running AMD-based AI infrastructure to achieve similar utilization gains.
Scale indicators8 records
Recent moves6 records
Expansion highlights5 records
Rapt AI competitors and assessment
Company assessmentBroad incumbents
- Hugging Face Inference Endpoints: Hugging Face offers dedicated inference endpoints and managed GPU serving that competes for the same AI team budget; integrated model hub gives it an incumbent distribution advantage.
- CoreWeave: CoreWeave is a large, NVIDIA-backed GPU cloud purpose-built for AI inference and training; its own orchestration layer is competitive with Rapt AI for cloud-deployed customers, and it could expand into software.
- Paperspace (DigitalOcean): Paperspace, now part of DigitalOcean, sells GPU cloud instances and Gradient MLOps; competes for inference workloads and includes orchestration features overlapping with Rapt AI's platform.
- Lambda Labs: Lambda operates GPU clouds (1-Click Clusters, reserved instances) and inference API services; competes for the same enterprise inference workload customers Rapt AI targets.
- Anyscale: Anyscale (Ray) offers distributed compute and serving for AI workloads; competes for the same platform/infra leads and overlaps with Rapt AI's multi-cloud orchestration and inference optimization.
- Run:ai (NVIDIA): Run:ai built a GPU virtualization and orchestration platform that maps almost 1:1 to Rapt AI's dynamic allocation engine; now owned by NVIDIA, it competes head-on with co-sell advantages on NVIDIA hardware stacks.
Direct peers
- Spot by NetApp: Spot (formerly Spot.io) provides cloud infrastructure optimization including GPU autoscaling and cost intelligence—closest competitor to Rapt AI's cost intelligence and multi-cloud optimization modules.
- Modal Labs: Modal provides serverless GPU compute for AI inference with auto-scaling and developer-friendly abstractions; overlaps with Rapt AI's dynamic allocation and multi-cloud inference positioning.
- Together AI: Together AI runs an inference cloud with optimized GPU utilization and per-token pricing—directly adjacent to Rapt AI's multi-tenant, usage-based GPU optimization value proposition.
- Cast AI: Cast AI provides Kubernetes-native resource optimization and autoscaling that includes GPU workloads; overlaps directly with Rapt AI's Kubernetes-integrated GPU right-sizing and cost intelligence.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks6 records
Key highlights7 records
Customer concentration
Rapt AI social profiles
Digital presenceRapt AI financial estimates
Financial estimateRevenue estimate
Valuation estimate
Rapt AI leadership team
Management profileNumber of profiles
Profiles2 records
Rapt AI funding detail
Funding detailFunding overview
Funding rounds
Investors
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Rapt AI M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Rapt AI
What does Rapt AI do?
Rapt AI sells a model-defined GPU optimization platform for AI inference workloads. The platform continuously reads each AI model's compute, memory, and bandwidth requirements and dynamically reallocates GPU resources in real time across multi-cloud (AWS, GCP, Azure) and on-premise environments, achieving 98%+ utilization versus the ~35% industry baseline. It is delivered as a subscription software platform with enterprise pilots, professional services onboarding, and supporting solutions for cloud providers offering GPU-as-a-Service.
Is Rapt AI a public or private company?
Rapt AI is a private company. It is classified as venture growth investor backed and is currently operating.
When was Rapt AI founded?
Rapt AI was founded in -1. It employs 11 to 50 people.
Where is Rapt AI based?
Rapt AI is headquartered in Santa Clara, United States, in the North America region.
How does Rapt AI make money?
Three revenue lines are on record. Software Platform Subscription is the primary driver. The others are usage-Based GPU Optimization Fees and professional Services.
Who are Rapt AI's main competitors?
Broad incumbents on record are Hugging Face Inference Endpoints, CoreWeave, Paperspace (DigitalOcean), Lambda Labs, Anyscale and Run:ai (NVIDIA). Direct peers are Spot by NetApp, Modal Labs, Together AI and Cast AI.
Does Rapt AI have an API?
No public API is recorded for Rapt AI.
What industry is Rapt AI in?
Rapt AI's product category is AI Infrastructure / GPU Optimization. Its primary akta.pro industry code is HDAAAAAG, AI Compute Virtualization & Scheduling (GPU virtualization, cluster schedulers), with a secondary code of HDAAABAF, Model Deployment, Serving & Inference Platforms. Its NAICS code is 513210 and its SIC code is 7372.