Sold by: Futuralis
Your domain, in the model. Futuralis fine-tunes or trains models on proprietary data using Amazon SageMaker and Amazon Bedrock — covering model requirements assessment, governed training data preparation, experiment runs, evaluation, governance controls, and deployment architecture.
Overview
Your domain, in the model. The Futuralis Custom Model Development and Fine-Tuning service helps organisations adapt foundation models to domain-specific behaviour when off-the-shelf models are not sufficient.
Futuralis assesses model requirements, prepares governed training and fine-tuning data, selects the SageMaker or Bedrock approach, runs experiments, evaluates outputs, documents governance controls, and deploys an approved model workflow.
Core deliverables include model strategy, data preparation plan, fine-tuning and experiment outputs, evaluation report, deployment architecture, governance controls, and handover documentation. Recommended next steps: Story Completion, ComfyUI and SageMaker, AI on AWS, LLMOps. This professional service relates to Amazon Bedrock, Bedrock Agents, Knowledge Bases, Amazon SageMaker, Amazon S3, AWS Lambda, Amazon OpenSearch, AWS KMS, and Amazon CloudWatch.
Highlights
- Custom model fine-tuning or training on proprietary data using Amazon SageMaker or Bedrock — governed data preparation, experiment runs, evaluation report, and deployment architecture included.
- Model strategy, data preparation plan, fine-tuning experiment outputs, evaluation report, governance controls, and handover documentation — domain-specific AI with a clear governance trail.
- Fixed-price implementation sprint with Basic, Standard, and Advanced dimensions based on model complexity, data volume, and deployment requirements.
Details
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Delivery method
Deployed on AWS
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Support
Vendor support
Futuralis provides dedicated support for all Custom Model Development and Fine-Tuning engagements. Email: support@futuralis.com Support URL: https://www.futuralis.com/support Response time: within 1 business day.