Design agents

Design Agents

What is the Offering? This service delivers a suite of Design Agents powered by Agentic AI, purpose-built to streamline and accelerate the design and engineering phases of data platform modernisation. These agents act as intelligent assistants capable of performing automated source-to-target mapping, applying transformation logic, and generating data models aligned to enterprise methodologies including Data Vault, Kimball, Inmon, and custom frameworks. Design Agents operate with contextual awareness of business rules, metadata, and architectural patterns, allowing them to: Automate complex source-to-target mappings across structured, semi-structured, and unstructured data. Apply transformation logic dynamically and document it in business-readable and developer-ready formats. Generate scalable and methodologically consistent data models for different database tiers (e.g. staging, raw, curated, warehouse, semantic). Deliver artefacts and specifications suitable for automation into code-generation pipelines. The solution is designed to run entirely on AWS utilising the following AWS services:

Amazon S3 Amazon Bedrock Amazon DynamoDB Amazon OpenSearch Service Amazon ECR Amazon ECS / AWS Fargate Who is it for? The Design Agents service is tailored for enterprise-scale transformation teams tasked with accelerating design timelines and improving architectural fidelity. Target personas include: Data Architects / Modellers: Looking to ensure adherence to design patterns while reducing manual modelling efforts. Engineering Leads / Platform Owners: Needing rapid, consistent design artefacts across diverse data sources. Data Governance & Quality Teams: Seeking transparent and traceable mappings and rule applications. Transformation Program Leaders: Driving large-scale modernisation or migration programs with aggressive timelines.

How Does It Work? Design Agents: Core Capabilities Leverages a wide range of inputs such as: Source metadata (schemas, catalogs, dictionaries) Target platform specs and modelling standards Business rule repositories and transformation specs (or KPI Matrix from the Discovery Agent) Target methodology templates Design Agents use LLMs and domain-specific reasoning engines to: Perform attribute-level source-to-target mapping with context-aware transformations. Identify canonical vs non-canonical mapping opportunities. Generate semantic and physical data models aligned to nominated methodologies. Suggest optimal model design for scalability, auditability, and compliance. Output mappings in both human-readable and machine-ingestible formats.

Value Proposition Source-to-Target Automation – Cuts down weeks of manual mapping effort with traceable, rules-aware output. Pattern-Driven Modelling – Aligns model generation with enterprise architecture frameworks and standards. Business-Logic Alignment – Ensures transformation rules are both technically correct and contextually explainable. Code-Ready Artefacts – Produces outputs ready for ingestion into data pipelines and model deployment workflows. Change-Aware Design – Responds dynamically to changes in business logic, source systems, or transformation scope.