RAG-as-a-Service

Empowering Organisations with Responsible AI

In today’s data-rich environment, knowledge is often trapped in silos across documents, systems, and repositories.

Straits Interactive’s RAG-as-a-Service enables organisations to securely harness this information through Retrieval-Augmented Generation (RAG) – transforming internal data into reliable, explainable AI assistants.

Built on the Capabara® Platform, this service helps you turn your own policies, manuals, and institutional knowledge into AI-driven capabilities that improve productivity, governance, and decision-making while maintaining data privacy and compliance.

Solution Overview

RAG-as-a-Service is a managed and enablement offering that helps organisations create their own Retrieval-Augmented AI applications using their internal data.

It combines the power of Large Language Models (LLMs) with secure Capabara^® Knowledge Systems (CKS) to provide accurate, context-aware, and fully governed AI assistants.

Each project includes:

• End-to-end consulting following the ISO 5338 AI Lifecycle — from inception and scoping to deployment and capability transfer.
• Custom RAG app design integrated directly into business workflows.
• Optimised model selection based on use case, data type, and token cost tiers (low, mid, high).
• Built-in governance through Straits’ AI Lifecycle Optimiser and documentation toolkit.

Together, these deliver a trusted, explainable AI ecosystem tailored to your organisation’s knowledge assets.

Deliverables

• 1 to 2 RAG-enabled AI Assistants aligned to your defined use cases.
• Workflow Design integrating the Assistants into daily business processes.
• Governance Dashboard for usage, performance, and compliance visibility.
• Documentation Pack
      – Risk Analysis Report
      – Model Card
      – Business Case Blueprint
      – Privacy Policy & Terms of Use
• Editable Prompt Instructions – full client access (no vendor lock-in).
• Capability Transfer & Training for sustained internal ownership.
• Ongoing Advisory on model updates, risk, and governance practices.

In short, you receive both the AI solution and the capability to manage and evolve it responsibly.

Example Applications

• HR & Internal Comms – HR Policy FAQ Assistant answers questions on benefits, leave, and company policies.
• Legal & Compliance – Regulatory Advisor retrieves relevant clauses and frameworks for DPOs or compliance officers.
• Customer Support – Product Knowledge Bot provides accurate product and service responses to staff or clients.
• L&D – Course Reference Assistant indexes training materials for instant retrieval during instruction.

LLM Model Selection

Every RAG implementation includes evaluation and configuration of the most suitable Large Language Model (LLM) based on:

• Use case type and data domain.
• Accuracy, latency, and explainability performance.
• Client budget and token cost management (low, mid, or high-tier options).