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.
Where AI demand becomes infrastructure.
Platform and services are in development.
INTERTIE.ai · OPERATOR PARTNERSHIP · OCTOBER 2026Services determine the delivery scope
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 · OPERATOR PARTNERSHIP · OCTOBER 2026Inference, execution and compute
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 · OPERATOR PARTNERSHIP · OCTOBER 2026Responsibilities through acceptance
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 · OPERATOR PARTNERSHIP · OCTOBER 2026The proposed operating scope
Capabilities
Share relevant experience in inference, execution environments, GPUs, networking and facility operations.
Interfaces
Define software access, deployment, data handling and incident ownership.
Acceptance
Agree tests, operational handover, service objectives and maintenance responsibility.
Services are in development. Scope and acceptance are agreed for each project.
INTERTIE.ai · OPERATOR PARTNERSHIP · OCTOBER 2026Software and infrastructure responsibilities
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 · OPERATOR PARTNERSHIP · OCTOBER 2026Reliability, cost and capacity
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 · OPERATOR PARTNERSHIP · OCTOBER 2026A delivery responsibility matrix
Proposed scope
Identify the engineering or operating scope you can support.
Evidence
Provide relevant deployment experience and the conditions for service readiness.
Next result
Develop a workload-specific assessment and a responsibility matrix.
partner@intertie.ai · intertie.ai/start