Enterprise resources
Browse the published product documentation, solution architectures, and commercial paths for enterprise evaluation.
Product and technical documentation
- DocsBrowse practical documentation for FusionPointAI AI Hosting, Model Transformation, and Blockchain services.
- Unlimited API documentationUse every published model with OpenAI-compatible Chat Completions or Claude Messages. Find exact identifiers, client examples, authentication and protocol-specific guidance.
- Open API referenceConnect an application using the documented inference API or model-training API, scoped credentials, and current usage and API references.
- Model Training API & SDKFollow the complete TrainingProject workflow, explore the backward-compatible Python client and API, and build a reproducible local training run.
- Architecture resourcesReview the existing solution architecture outlines alongside the product and operational guides they reference.
Solution areas
Explore the solution pages and their linked product references.
- Modernize financial workflows with institution-owned controlsEvaluate a banking blockchain environment for institutions that need explicit asset policies, transaction controls, governance responsibilities, and a planned path from a non-production evaluation to an agreed operating model.
- Plan token services around asset lifecycle and controlConnect token product choices with issuance, administration, user access, operational support, and the systems around an asset. Begin with defined responsibilities rather than assuming a token name implies a complete operating service.
- Connect AI workloads to a deliberate operating modelPlan model selection, training or transformation, compute, delivery, and ongoing operations as connected decisions. Existing AI products cover distinct needs; choose them from the workload and deployment boundary, not from a generic promise.
- Adapt model releases to a documented production targetAssess model transformation options against release evidence, target hardware, runtime compatibility, language needs, and delivery mode. Work from a specific source model and acceptance criteria rather than assuming every transformation is available.
- Choose compute from workload and verified availabilityEvaluate GPU infrastructure using a concrete model, memory profile, runtime, concurrency, and delivery target. Browse current hardware and hosting catalogues instead of relying on generic capacity or performance assumptions.
- Operate network services with defined responsibility boundariesAssess managed network, infrastructure, and operational product options while keeping protocol choices, validator duties, access, upgrades, incident handling, and customer responsibilities explicit.
Planning and procurement
Continue to the existing enterprise and procurement information, or request an architecture review.