Production AI systems, built to operate.

Multi-Agent System Design & Build

Multi-step workflows with explicit control and escalation.

We design agent systems that coordinate across tools, data sources, and reasoning steps. Adaptive depth, MCP integrations, and proper controls from day one.

This means agent teams that know when to act and when to escalate, tool orchestration that holds under load, persistent memory and context, and observability so you can trace exactly what happened and why.

• Working agent system deployed to your infrastructure
• Architecture documentation and decision log
• Observability and monitoring setup
• Handover sessions with your engineering team

Knowledge & Retrieval Systems

Source-cited answers from the information your team is allowed to use.

We design retrieval pipelines that ground agents in your actual data so they act on facts, cite sources, and stay inside their lane.

This goes beyond plugging in a vector store. It means getting retrieval quality right for your specific documents and queries, measuring it honestly, and connecting it through MCP so agents can access context from across your stack.

• Retrieval pipeline tuned to your data and queries
• Evaluation suite with precision and recall benchmarks
• MCP integration with your existing tools and data sources
• Source citation and traceability built in

Production Deployment & Engineering

A disciplined path from prototype to production.

Getting agents working in a demo is the easy part. Production requires evaluation, inference-cost controls, compound-error management, observability, and graceful failure handling.

Westland Labs focuses on the gaps between a promising prototype and a system a team can operate and own.

• Production-ready deployment with CI/CD pipeline
• Evaluation framework for ongoing quality measurement
• Cost monitoring and inference optimization
• Failure handling and graceful degradation patterns

AI Audit & Advisory

Outcome: A clear picture of what's working, what's at risk, and exactly what to fix first.

Already have agents or AI systems in place? We conduct structured reviews of architecture, agent behavior, reliability, safety, and risk, and deliver a clear report with prioritized recommendations.

• Agent architecture and orchestration review
• Tool use, memory, and retrieval quality assessment
• Failure mode, edge case, and safety analysis
• Recommendations for observability, governance, and cost control

• Written report with findings and prioritized recommendations
• Risk assessment with severity ratings
• Architecture diagrams of current vs recommended state
• Follow-up session to walk through findings