An AI-native
infrastructure
company.
Building a cloud for AI agents in production. Production inference and agents, enterprise post-training, and model access and routing.
INTERTIE.ai · COMPANY OVERVIEW · OCTOBER 2026
A cloud for agents in production
The customer
For product and engineering teams putting AI agents into production, improving performance on their tasks or simplifying model access. Current outreach focuses on US customers. Data, model and deployment-location requirements are assessed for each project.
The platform
Building cloud services for production inference and agents, enterprise post-training, and model access and routing.
The delivery model
Real customer workloads guide product development, engineering and delivery. The company may own, operate and renew GPUs or use third-party supply where appropriate. Facility, equipment and service rights are established separately for each project.
Services are in development. Scope and acceptance are agreed for each project.
INTERTIE.ai · COMPANY OVERVIEW · OCTOBER 2026
Services around the customer workload
Production inference and agents
Run models and tools within customer authorization. Manage execution isolation, state, recovery and observability. Evaluate quality, latency and cost for the complete task.
Enterprise post-training
Improve task performance with authorized models and data. Establish a baseline and held-out evaluations, then deploy validated versions with rollback available.
Model access and routing
Manage model and provider choices, usage records and billing through a common interface. Deploy open models under their licences and access closed models through authorized APIs.
Services are in development. Scope and acceptance are agreed for each project.
INTERTIE.ai · COMPANY OVERVIEW · OCTOBER 2026
Inference and agent operations
Inference
Model deployment and APIs, scheduling and quality evaluation support the customer task.
Execution
Isolated tools, state, orchestration and recovery keep an authorized workflow running.
Compute
GPU capacity and networking follow the workload. Company-owned and third-party supply are assessed separately.
Services are in development. Scope and acceptance are agreed for each project.
INTERTIE.ai · COMPANY OVERVIEW · OCTOBER 2026
Improvement on a specific task
Task baseline
Identify the task and compare model choice, prompts and routing before committing training resources.
Authorized inputs
Use models, data and environments with appropriate rights. Keep customer data within its agreed scope.
Evaluation and release
Use held-out evaluation. Record the improvement and full cost, then release a version with rollback.
Services are in development. Scope and acceptance are agreed for each project.
INTERTIE.ai · COMPANY OVERVIEW · OCTOBER 2026
Model access and routing
A common interface
Choose models and providers around the workload. Maintain usage records and billing visibility.
Open and closed models
Deploy open models under their licences. Access closed models through authorized provider APIs.
Evidence of support
Confirm the supported model matrix, contract terms and billing responsibility for each customer.
Services are in development. Scope and acceptance are agreed for each project.
INTERTIE.ai · COMPANY OVERVIEW · OCTOBER 2026
Workload validation and delivery
Validate the workload
Select the service scope, task and data rights. Agree acceptance criteria for quality, latency, reliability and cost.
Integrate and accept
Verify model access, execution and training boundaries. Check isolation, recovery, version management and operating responsibilities.
Scale and operate
Select supply and dedicated GPUs against validated demand. Manage utilization, maintenance, service cost and equipment renewal over time.
Services are in development. Scope and acceptance are agreed for each project.
INTERTIE.ai · COMPANY OVERVIEW · OCTOBER 2026
Software, equipment and service rights
Models and data
Open models follow their licences. Closed models use authorized provider APIs. Training requires separate model and data rights.
Equipment and facilities
Confirm the GPU owner, location and operating scope for each deployment. Facility and equipment rights are established separately.
Service responsibility
Agree support, incident response, data handling and acceptance criteria with the customer and delivery partners.
Services are in development. Scope and acceptance are agreed for each project.
INTERTIE.ai · COMPANY OVERVIEW · OCTOBER 2026
Three service revenue paths
Production operations
Meter inference, execution and operating support against the agreed service scope.
Post-training
Price authorized compute, evaluation and adaptation against task-specific acceptance criteria.
Model access
Separate third-party API spend from platform fees and enterprise services. Contracts determine revenue treatment.
Services are in development. Scope and acceptance are agreed for each project.
INTERTIE.ai · COMPANY OVERVIEW · OCTOBER 2026
Customer value and operating evidence
Customer outcome
Measure task acceptance, reliability and quality against the customer’s baseline.
Full service cost
Include third-party APIs, compute, engineering support and operating effort.
Capacity decision
Use measured demand to select supply and GPU capacity. Separate new usage from migrated traffic.
Services are in development. Scope and acceptance are agreed for each project.
INTERTIE.ai · COMPANY OVERVIEW · OCTOBER 2026
GPU operations and renewal
Capacity
Select dedicated GPUs or third-party supply from measured workload requirements.
Operations
Account for utilization, energy, networking, support and maintenance.
Renewal
Plan equipment renewal and service continuity across the operating life.
Services are in development. Scope and acceptance are agreed for each project.
INTERTIE.ai · COMPANY OVERVIEW · OCTOBER 2026
A workload brief and validation plan
Required service
Choose production operations, post-training or model access. Describe the task and authorized users.
Workload and rights
Share models, tools, data rights, region and targets for quality, latency, reliability and cost.
Validation plan
Agree the test workload, baseline and acceptance criteria before committing capacity or dates.
partner@intertie.ai · intertie.ai/start