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Turn proprietary data into proprietary advantage.

Build specialist models on the knowledge, decisions, and operating data that make your organization unique. SF Tensor makes private-data post-training repeatable, affordable, and production-ready.

Design your first training runSee the training lifecycle

Input

Private data
Base model
Evaluation suite
01

Inject

Train on domain knowledge

02

Align

Post-train for the task

03

Repeat

Keep models current

Outcome

Specialist model
Private deployment
Continuous updates

01. Lower training cost

Up to0%

Optimize utilization and placement across available hardware.

02. Time to a specialist model

0h

From a production-ready dataset and base checkpoint.

03. Faster iteration cadence

0×

With repeatable data, evaluation, and retraining pipelines.

The enterprise opportunity

Your edge is what public models never saw.

A frontier model can reason, but it does not know your underwriting history, clinical protocols, factory telemetry, or internal decisions. Data-injection training integrates that knowledge into the model itself—then keeps it current as the business changes.

Domain data
Base reasoning
Human feedback
Specialist model

01

Connect private knowledge

Prepare proprietary and specialist data inside the boundary you control.

02

Inject and post-train

Start from the right base model, integrate domain data, align, and evaluate.

03

Deploy under your controls

Ship the resulting weights in your cloud, our cloud, or an edge environment.

04

Keep the model current

Repeat the pipeline as policies, data, and business conditions evolve.

What you get

A model-building function, without an infrastructure detour.

Your domain team owns the objective and data. We bring the training system and forward-deployed engineers needed to turn both into a model.

System layer 01

Data-injection training

Integrate private knowledge during training instead of attaching it only at inference time.

Specialist model fleets

Train smaller models for specific tasks, customers, devices, and modalities.

System layer 02

Formal kernel verification

Prove optimized kernels implement the intended mathematical function before production.

Bring your environment

Run inside existing cloud accounts, private networks, and operational controls.

System layer 03

Outcome-based optimization

Choose hardware and topology for cost, time, memory, or deployment constraints.

Forward-deployed engineering

Work with the engineers who build the compiler, runtime, and training platform.

Private by design

Your data teaches your model. Nothing else.

Your cloud

Run inside your existing accounts, networks, and controls.

Your weights

Keep complete ownership of checkpoints and resulting models.

Your policy

Bring retention, access, audit, and regional requirements.

Our operators

Work directly with engineers who own the training stack.

Where it starts

Build the model your industry has been waiting for.

01

Financial services

Train on decades of underwriting, research, risk, and operational decisions.

A model that understands how your institution decides.
02

Healthcare and life sciences

Combine domain literature with private protocols, outcomes, and new modalities.

Specialist systems built for clinical and discovery workflows.
03

Industrial and government

Turn telemetry, reports, procedures, and institutional knowledge into capability.

Smaller, deployable models that work where the data is created.
Also building for frontier AI labs

Your model is the advantage. Infrastructure shouldn’t be the constraint.

Bring the model, data, and ambition. We’ll optimize the kernels, orchestrate the fleet, and deliver the training outcome.

Plan a training runTalk to an engineer

Train the models only you can build. One stack for enterprise post-training and frontier pre-training.

All System Operational

© 2026 San Francisco Tensor Company

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