AI
Foundation Models & Transfer Learning
Adapt foundation models with efficient fine-tuning, safety, and evaluation pipelines.
Service snapshot
We select and adapt foundation models with transfer learning, applying efficient fine-tuning and evaluation to balance quality, latency, and cost.
- Model selection against latency, cost, and license constraints.
- Parameter-efficient fine-tuning and domain adaptation.
- Evaluation harnesses with qualitative and quantitative metrics.
Where we focus
What we deliver
- Model selection against latency, cost, and license constraints.
- Parameter-efficient fine-tuning and domain adaptation.
- Evaluation harnesses with qualitative and quantitative metrics.
- Safety, privacy, and IP controls for enterprise deployment.
Proof of value
Outcomes you can expect
- Higher-quality outputs tuned to your domain.
- Reduced training cost with efficient fine-tuning methods.
- Transparent performance with reproducible evaluation.
- Deployment patterns that satisfy security and compliance.
How we work
Engagement building blocks
Each engagement combines strategy, build, and adoption. We leave your teams with the assets, playbooks, and operating rhythms needed to keep improving after launch.
Foundation Models & Transfer Learning
Model selection
Benchmarking models against business and technical constraints.
Foundation Models & Transfer Learning
Efficient adaptation
PEFT, adapters, and distillation to tune models without runaway cost.
Foundation Models & Transfer Learning
Evaluation & safety
Automated and human evaluation with safety, privacy, and IP checks.
Ready to explore how Foundation Models & Transfer Learning can move the needle?
We’ll align on the outcomes that matter, assemble the right team, and start with a fast, low-risk path to value.