AI DEVELOPMENT SERVICES
Private AI Model Training Services for Confidential Data
Brainscraft helps organizations fine-tune AI models for specific tasks such as classifying documents, extracting structured fields, and drafting internal reports. We start with a focused pilot using approved examples and agree how data and model outputs will be handled before work begins.
Discuss a private AI pilotChoose fine-tuning or private retrieval
Fine-tuning adapts a model to a recurring behavior, such as extracting the same fields across document formats. For answers based on internal policies that change frequently, private retrieval can supply the current documents at request time. We can compare both approaches on the same evaluation set before you commit to a build.
Agree how confidential data will be handled
We scope where training and inference can run, which examples are approved for use, and who can access datasets, logs, and model checkpoints. Hosting options and any external processing depend on your model, infrastructure, and organizational requirements. We can begin discovery with synthetic or redacted examples.
Illustrative pilot for document extraction
A team wants to extract supplier names, invoice dates, and totals into a standard record. We agree the output format, compare a baseline model with a fine-tuned model, and check both against examples held out from training. Missing or conflicting values can be sent to a reviewer before records are saved.
What a pilot can deliver
Agree the dataset and evaluation plan first. A scoped pilot can deliver a baseline comparison, results on held-out examples, checks for sensitive information exposure, and a deployment recommendation. We define approval criteria and who will operate the system before rollout.
Questions before you start
Can we start without sharing confidential records?
Yes. Start with synthetic or redacted examples that reflect the formats and decisions involved. Use approved real data only after agreeing the environment, access rules, and evaluation plan.
Can the model run in our environment?
We assess whether your infrastructure can support the selected model and workload, then scope hosting, access, monitoring, and ownership with your team.
Tell us which task the model should handle
Share the workflow, expected output, and hosting requirements so we can scope a pilot.
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