Custom Agent Development
We build AI agents for content creation - helping companies connect with customers and powering the intelligence hubs strategic sectors need to make better decisions and move faster.
From Prompts to Production-Grade Agent Systems
AI agents are no longer prompt wrappers with a tool call. They are long-running, goal-driven systems that plan, reason, retrieve, and act - autonomously and at scale.
We design and build custom agent architectures that solve real business problems: content pipelines that publish themselves, intelligence hubs that surface what matters, and multi-agent workflows that coordinate like high-performing teams.
What We Build
Multi-Agent Systems
Orchestrated specialist agents that collaborate under a coordinator - a researcher gathers data, a writer drafts content, an analyst validates output, and a publisher pushes to production. Built on LangGraph and CrewAI.
Agentic RAG Pipelines
Beyond basic retrieval. Our agentic RAG systems plan retrieval strategies, route queries across multiple knowledge bases, track context across sessions, and refine answers iteratively - turning static document stores into dynamic intelligence engines.
MCP-Connected Agents
The Model Context Protocol (MCP) is the industry standard for agent-tool communication. We build MCP-native agents that plug into your enterprise stack - CRM, ERP, analytics - through standardised, auditable interfaces. No glue code. No brittle integrations.
Content Creation Agents
AI agents that generate, curate, review, and publish content across channels. Built to understand brand voice, audience intent, and editorial workflows - with human oversight where it matters most.
Enterprise Intelligence Hubs
End-to-end platforms that aggregate, process, and present data for decision-makers. Multiple AI agents working with enterprise data sources - internal metrics, market signals, competitive intelligence - to deliver real-time strategic insights.
Our Approach
- Architecture first. Every agent system starts with a clear architecture - defined roles, tool boundaries, memory strategy, and failure handling. We design for production from day one.
- Security by design. Agents interacting with external tools introduce new attack surfaces. We scope permissions, audit tool access, and monitor agent behaviour as rigorously as any production system.
- Enterprise integration. Our EAI roots mean we understand how enterprise systems talk. We connect agent workflows to your platforms through APIs, middleware, event buses, and MCP servers.
- Human-in-the-loop. Full autonomy is not always the goal. We design agent systems with configurable checkpoints - review gates, approval flows, and override mechanisms.
Use Cases
- Automated Content Pipelines - Multi-agent workflows that research, draft, review, optimise, and publish content - reducing editorial cycles from days to hours while maintaining brand consistency.
- Customer Intelligence - Agents that analyse interactions across channels, surface patterns, and trigger personalised engagement at scale - turning conversation data into revenue signals.
- Strategic Decision Support - Intelligence hubs that aggregate market data, internal KPIs, and external signals into dashboards and briefs leadership teams can act on immediately.
- Knowledge Management - Agentic RAG systems that make institutional knowledge searchable, contextual, and actionable - replacing static wikis with intelligent assistants.
Technologies We Use
- LangGraph
- CrewAI
- Model Context Protocol (MCP)
- Agentic RAG
- LLM Orchestration
- Vector Databases
- Python
- Node.js