Fixing Inaccurate Multi-Domain Answers with RAG and Multi-Agentic Workflows
The Problem
Teams handling complex enquiries—spanning legal, pricing, product, and operational domains—were limited by the accuracy and reliability of single-agent AI systems. Nuanced questions required synthesis across multiple knowledge areas, but single-model responses often produced brittle, incomplete, or contradictory guidance. This forced lengthy back-and-forth reviews with subject-matter experts, slowing output and increasing the risk of incorrect advice being circulated.
The Solution
One of our digital squads implemented a multi-agent orchestration framework built on top of retrieval-augmented generation. The system decomposed each query into domain-specific subtasks, routed them to specialist agents (Legal, Product, Pricing, Summariser), and used a coordinator agent to reconcile outputs, enforce contradiction checks, and return a verified composite answer.
The delivery included domain mapping, design of each agent with tailored prompt templates and retrieval parameters, and a governance layer featuring confidence scoring, source traceability, and human validation for high-risk or sensitive outputs. This created an auditable, reliable workflow for handling complex, multi-domain queries at speed.
The Impact
- 30–50% reduction in research time for complex, multi-domain enquiries
- Noticeable uplift in factual accuracy compared with single-agent systems
- Faster, standardised deliverables with far fewer stakeholder review loops
- Full audit trail of agent decisions and source provenance for governance
More Case Studies on
Implementing AI
Executive reports were slow to produce, often outdated, and required heavy manual assembly.
Manual outreach didn’t scale, while templated blasts delivered poor engagement and compliance risk.
Manual contract review was slow, inconsistent, and prone to missed obligations and risks.
More than an agency.
Your digital partner.
Define Your Mission Brief
Assemble Your Delivery Squad
Launch Your Product
