Your data boundary
Your source data, prepared datasets, and retrieval indexes are organized for your company’s approved access rules and deployment requirements.
Train · Private AI models as a service
Your company’s data.A model built for your company alone.
Super Amplify connects your approved systems, builds a clean and governed company data lake, then develops and operates a private model service around the work your team needs to do.
Private service
One governed path from company data to company intelligence.
Approved company systemsYour selected sources
Clean, governed data lakeOrganized and traceable
Private model serviceConfigured for your team
Isolation, hosting, and access are set to your company’s requirements before implementation.
Make the company’s knowledge useful, trusted, and private.
A strong company model starts with the right data foundation and operating boundaries. We build the whole path with your team, from first connection through ongoing improvement.
Your model assets
The resulting model configuration and company-specific assets are designed for exclusive use by your organization, with the hosting and isolation model agreed before buildout.
Your operating controls
Define who can use the service, what sources it can reach, when people must review its work, and how results are measured.
Four steps from scattered systems to a model your team can use.
We work from your use cases and access policies, so each technical decision serves the business and each result can be reviewed.
Connect the systems you trust
Start with your data owners and the work the model should improve. We map approved sources across documents, databases, cloud platforms, CRM, ERP, and the tools your teams already use.
Scoped access, source owners, and a clear purpose for every connection.
Build and prepare the company data lake
Bring approved data into a governed foundation. We catalog it, map its structure, remove duplicates, normalize formats, check quality, and keep lineage back to the source.
Cleaner, traceable data with freshness and quality checks built in.
Shape a model around your work
We evaluate retrieval, fine-tuning, and custom model training against representative tasks. The right approach is the one that performs measurably on your use cases and fits your operating constraints.
A company-specific model experience, validated before it reaches the team.
Operate it for your company
Deploy the service within the agreed company boundary, connect it to approved workflows, and monitor quality, access, and changes as your data and business evolve.
Authorized users, reviewable activity, and a managed improvement loop.
Train what needs training. Connect the rest with care.
Not every business problem needs a new foundation model. We compare retrieval, fine-tuning, and custom training on your real tasks, then recommend the simplest approach that meets your quality, privacy, and operating goals.
Retrieve trusted knowledge
Use your governed data lake as current, traceable context.
Fine-tune for your work
Align model behavior to proven patterns and company language.
Train a private model
Develop company-specific model assets when the evidence supports it.
A private model is an operating service, not a one-time handoff.
As sources change and teams learn, the data foundation and model need care. We help monitor quality, review access, track versions, and improve against agreed measures.
Set the company boundary, source permissions, and user roles
Validate the model against representative, approved company tasks
Keep model and data changes traceable for review
Monitor answer quality, source freshness, and human escalations
Use evidence from real operation to decide what to improve next
Put your company’s knowledge to work for your company.
Bring a use case, a few data sources, and the people who own them. We’ll map the data foundation, private model approach, and a practical first milestone together.