An operating layer for generating, scheduling, validating, storing and replaying agentic-AI workloads across CPU/GPU infrastructure.
Discuss AgentForgeTHE PRODUCT, IN PRACTICE
An agent workload has to move beyond generation into execution, validation and a record that can be revisited. AgentForge connects those stages for a supported CPU/GPU environment. It focuses on the operation of agent work—not simply the model that generated the task, and not a promise that every external action becomes safe or correct automatically.
A proposed action still needs to be prepared and scheduled on the appropriate supported infrastructure.
AgentForge brings generation and scheduling into an operating workflow so the customer can define how agent work reaches execution.
The team needs to distinguish produced output from output that passed the relevant task checks.
Validation is a separate stage of the operating layer, with checks and acceptance requirements defined for the workload.
Unretained work makes it harder to understand what was generated, executed and checked.
AgentForge includes storage and replay responsibilities for the qualified workload, supporting review of retained runs.
The product scope below describes the capability and outputs to confirm for your release. Custom integration, operated delivery and additional engineering are separately agreed.
Preparation of agentic workloads within the supported operating scope.
Defined placement of work across the agreed CPU/GPU environment.
Workload-specific checks that separate execution from acceptance.
Records and replay functionality within the supported runtime contract.
AgentForge is fully available with CLI, MCP and headless access. Use the interface that fits your terminal, your agents or your automated workflow.
Run the product from a terminal or script, alongside the tools your team already uses.
Get CLI accessConnect MCP-compatible clients and agents to the product’s exposed capabilities.
Get MCP accessOperate without a graphical interface in unattended, scheduled or pipeline-driven work.
Set up headless accessProduct-specific inputs, hardware requirements and result guarantees still apply. An access mode does not change your license or deployment scope.
Explore all product interfacesA platform team needs to run and review an agent-generated computational task rather than only record a conversation.
Illustrative use of the supported scope, not a customer case study or a measured result.Define the task format, authorized execution and acceptance checks.
Generate, schedule and validate the work through the supported operating path.
Retain the record and exercise the agreed replay behavior for review.
A product workflow illustration, not a live execution or deployment test. Choose a stage to explore its role.
Prepare the workload and its declared requirements.
Agent-platform, AI-operations and infrastructure teams that need a defined execution and replay workflow.
CLI, MCP and headless access are all available. Run from a terminal or script, connect an MCP-compatible client, or use the product without a graphical interface. Choose the mode during onboarding and receive its setup instructions. Runtime requirements and supported operations remain product-specific.
The supplied description does not establish a universal autonomous agent, unlimited tool permissions or deterministic replay of every external system. Authorized actions, failure handling and operational support must be specified for the actual deployment.
The agreed AgentForge release, its supported interfaces and outputs, the applicable checks and the support stated in your order. The plan defines users, workflow, environment and capacity. Source-code transfer, unrestricted redistribution and bespoke engineering are not automatically included.
Request a scoped engineering or operated-service proposal. It identifies what our team delivers, where the workload runs, infrastructure costs, acceptance requirements and ongoing support. Your software subscription alone does not activate a hosted runtime.
Explore engineeringAgree the model or workload, current baseline, environment, required output and acceptance tests. Evaluate the selected release against those conditions. A product description or a test count does not establish a gain on a different customer workload.
Plan an integrationCustomer-hosted access and a service operated by SpinForge are different scopes. Confirm the release, deployment and included support before activation.
Plans & deliveryBring a representative workload and the result your team needs. We’ll define the product, deployment and engineering scope around that task.
Activate this capability inside a qualified compute & data operations workflow. Compatible methods and required shared checking are included once within that workflow; the product remains independently purchasable.
Capacity, release, environment, result contract and operating responsibilities are specified before activation. Choosing an additional method is not permission to add an unrelated workload or unqualified deployment.
Explore Compute & Data Operations Choose workflow capacityCommission the model, integration and acceptance work needed for your task. Existing products stay independently available.
Commission a revision-aware workflow that keeps models, assumptions, results and evidence connected as inputs change.
03 / Scoped customer programCommission a bounded performance improvement with source identity, numerical acceptance and the appropriate checking evidence.
Use the software directly or ask us to scope the implementation.
One capability. A connected workflow.
A team to put it into practice.