Integrating Multiple AI Agents with a Central Orchestrator
Unifying AI agents with a central orchestrator to streamline operations.
The Opportunity
Our client faced significant inefficiencies in retrieving insights from structured and unstructured data sources. Their workflows required pulling data from diverse repositories, such as SQL and vector databases, and coordinating niche operations reliant on complex business logic. The primary challenge was integrating these isolated, specialised processes into a unified system. The client aimed to deploy an intelligent orchestrator to coordinate AI agents, automate workflows, reduce inefficiencies, and increase accuracy.
What we did
✔︎ Developed a central AI orchestrator capable of overseeing and coordinating multiple agents, each dedicated to specific workflows. ✔︎ Built agents for structured data queries (SQL databases), retrieval from vector databases, and other specialised data processing tasks. ✔︎ Enabled the orchestrator to reason through tasks, dynamically invoking the right agents in the correct sequence and merging their outputs to solve complex problems. ✔︎ Rigorously tested the system to ensure seamless agent collaboration and achieved a 96% decision-making accuracy in task sequencing and orchestration.
96%
accuracy
How we did it
We began by collaborating with stakeholders to map key workflows and identify operational bottlenecks that caused inefficiencies and increased costs. To maximise the system’s impact, agents were prioritised for quick development and strong alignment with business objectives, balancing speed of delivery with strategic scalability. The central AI orchestrator was built to coordinate diverse agents, each tailored for a specific task. For example, the SQL agent handled structured data extraction, while the vector database agent processed numerical data and qualitative insights. These agents were brought together under the orchestrator, which utilised Large Language Models (LLMs) for reasoning and dynamic task routing. The orchestrator automated complex multi-step workflows by invoking agents in the appropriate order, ensuring outputs were merged seamlessly and aligned with business logic. To validate its performance, a robust evaluation framework measured the orchestrator’s ability to invoke the correct agents and execute workflows accurately. Consistently achieving a 96% accuracy, the system delivered exceptional reliability and precision. By reducing inefficiencies and automating manual processes, the client experienced significant increases in productivity and operational cost savings.
