Agentic AI Solutions
Engineered for the Pacific Context

General cloud models from OpenAI, Google and Anthropic (Generative AI) are suitable for broad creative tasks, general-purpose assistance and quick, broad-knowledge solutions without specialised data. Agentic Pacific solutions are built on custom-developed Fine-Tuned Models (SFT, LoRA, QLoRA). These are specialised, high-accuracy AI models adapted from a general base model using specific, often proprietary, datasets to excel at niche tasks (e.g. legal or financial analysis) or company-specific behaviour and knowledge. Our models have long-term contextual memory, can not only recall, but reflect and draw insights and observations from prior conversations, further enhancing institutional knowledge grounding and consistency across interactions.

General models are broad, pre-trained and versatile but lack specific expertise. Fine-tuning offers greater precision and behavioural control but is more expensive to develop. Additionally, Agentic Pacific solutions implement Retrieval-Augmented Generation (RAG), which is essential for enterprise AI applications. RAG bridges the gap between the static, generalised knowledge of large language models (LLMs) and the need for accurate, up-to-date and private information. Our solutions, compared to generic AI assistants, can access and retrieve information from specific, often proprietary, datasets (e.g. internal databases, records, documents) to provide contextually relevant and accurate responses grounded in the most current and relevant data. They can adapt to different or changing situations and have "agency" to make decisions based on context.