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Design and deploy domain-tuned LLMs, multimodal models, and efficient on-edge variants thatalign with measurable business KPIs using Alpha AI’s research-to-production loop. Our teamscombine instruction-tuning, retrieval augmentation, safety alignment, and rigorous evaluation todeliver reliable models that perform under real operational constraints.
What we do
Build custom conversational and task-oriented models, fine-tune compact localdeployments, and ship evaluation harnesses with bias, reliability, and latency criteria tied totarget workflows. Deliver models with clear documentation, observability, refresh cadence,and ownership clarity for long-term maintainability.
Capabilities
LLM fine-tuning, RAG architectures, vectorization strategies, prompt program management,and multi-agent orchestration for complex tasks. Performance tuning includes quantizationand GGUF packaging for local or edge inference where privacy, latency, or cost efficiency isparamount.
Methods
We employ SFT, DPO, custom techniques and task-specific adapters, backed by governance gates and red-teaming for safe behavior and predictable failure modes. Data pipelines integrate domain corpora with curated public datasets, enabling grounded outputs and better retrieval coverage.
Deployment
Offer on-device, VPC, and hybrid targets with CI for prompts and models, canary rollouts,and post-deployment monitoring for drift and regressions. Integrate with existing systems through APIs, event buses, or SDKs with audit logs and privacy-preserving patterns.
Direct Links
Link to our Hugging Face Organization Page - https://huggingface.co/alpha-ai
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