Service · MODEL + EDGE
Lower cost, lower latency, data stays where it must.
Model & Edge Engineering. Fine-tuning, distillation and small models deployed on-device or on-prem when frontier APIs don't fit.
Who this is for
Built for teams like yours.
- Teams with AI spend growing faster than revenue
- Latency-sensitive products
- Data that cannot leave a region or a device
What the FDE team does
Inside your stack, not around it.
- Fine-tuning and distillation
- Small language models
- On-device and on-prem deployment
- Inference optimisation
The outcomes you get
Scored, not promised.
−[X]%
Cost per 1K requests
Illustrative · placeholder
−[X]ms
p95 latency
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[X]%
Quality retained vs frontier model
Illustrative · placeholder
Frameworks & tools we bring
Model-agnostic by design.
LlamavLLMGroqONNXLoRAVertex AI
Related case study
Raising AI accuracy for an enterprise running AI in production
ReadPut an FDE pod on model & edge engineering.
Start with an outcome audit. We’ll map the systems, measures and FDE pod needed to move from AI ambition to production impact.