Your expertise. Your model. Your edge.
Turn your company’s data, decisions and processes into a specialist model. Train for your workflow, deploy within your boundaries, and measure what improves.
+Private training. Specific benchmarks. Measurable value.
Domain-ready training
Enterprise-contained deployment
Proof on the work that matters
Your decisions, telemetry and process knowledge are the starting point for a model trained to do your work.
Training starts with a domain-ready blueprint: approved data mappings, exact input and output schemas, expert examples, and a held-out evaluation set.
Telemetry, event and market-depth logs become structured examples. Synthetic KYC-style fixtures can support formatting and testing, with expert validation and agreed data rights. Expert-reviewed traces and verified model-generated examples can be distilled into a smaller specialist model.
See the training processDomain-ready preparation adapts your approved sources to the task, schema and decisions your team needs.
Select a licensed base model, agree the deployment boundary, and define rights to the resulting artifacts.
Judge performance on your detection scores, citation quality, execution predictions, latency and cost.
Start with a valuable workflow.
Train for the decisions inside it.
Review this transaction against our risk policy. Explain the signals and recommend a next step.
Recommendation: escalate for review.
New device, unusual transfer pattern, and a mismatch with verified account history.
Train on expert-reviewed decisions and verified outcomes. Evaluate precision, recall and escalation quality.
Explore your use caseOne focused workflow. A measurable baseline.
A model that earns its place in production.
We map a high-value workflow with your domain experts, establish today's quality and cost, and agree on a success threshold before training begins.
Business case + evaluation planTwo industry reference cases.
Customer names redacted; findings preserved.
A post-trained open-weight model improved a specific fraud workload against a frontier-model baseline.
Task-specific training improved cited document answers while reducing the cost of every review-table cell.
Anonymized adaptations of public research, not Finetuned customer engagements. Results are workload-specific; comparison details and original sources are included in each case.
Browse the case studiesExplore time returned, inference savings
and the economics of specialization.
Annual gross business value
Sensitivity range $272,160 – $453,600
Capacity value represents time released, not necessarily cash savings. Estimates are illustrative and depend on pilot results.
Scope this opportunityScope an enterprise-contained engagement in which preparation, training, evaluation and inference run in your environment. Raw training data stays within the approved boundary.
Security approval depends on your controls, requirements and selected infrastructure.
Plan a private pilotServe repeatable, high-volume tasks with a smaller specialist model. Keep frontier models available for harder cases and approved escalations. External model calls use only separately approved context and data routes.
The reference cases show gains on specific workloads. Your economics are established through a pilot.
Calculate the opportunityAgree rights to weights, adapters and outputs. License a model or API only where data rights, the base-model license and your agreement allow it.
Package and license datasets through datahub. With Finetuned, train a specialist model around your company’s expertise. Use it internally or explore licensing a model or API under agreed rights.
We scope the workflow, prepare approved training examples, select a suitable base model, train and evaluate a specialist model, then plan deployment and ongoing improvement with your team.
Useful, expert-verified examples matter more than raw volume. Discovery establishes whether your data is sufficient, whether synthetic examples are appropriate, and whether model training is the right approach.
The engagement defines permitted use of your data. Cross-customer use or external licensing requires a separate agreement; it is not part of a private training engagement.
Yes, where your data rights, base-model license and engagement agreement permit it. We can scope packaging, an API or model distribution as a separate commercialization workstream.
We compare the trained model with an agreed baseline on held-out examples, including difficult cases. Quality, evidence, escalation behavior, latency and cost are measured before production rollout.
Pricing follows a scoped discovery and proposal. The calculator uses editable budget assumptions, not published service prices or a binding quote.
Bring us a workflow worth improving.
We’ll help define the model worth building.