03

Build & deploy

From roadmap to running AI systems — deployed in your environment, on your terms.

This is where strategy becomes reality. Build and Deploy is a hands-on technical engagement where we design and build production AI systems on our side, then deploy and test them within your cloud environment. We work to your infrastructure standards, your data policies, and your security requirements — but the heavy lifting happens in our development environment first. Once validated, every workflow, agent, and integration is deployed production-grade into your infrastructure, where your team can own it, extend it, and maintain it long after we leave.

Our technical stack is deliberately built on open-source foundations. We use n8n for workflow automation, CrewAI and LangGraph for AI agent orchestration, and standard cloud-native tooling for data pipelines and infrastructure. This is a conscious decision to eliminate vendor lock-in. You are never dependent on a proprietary platform that can raise prices or change terms. Your AI systems are yours, built on technology your engineers can inspect, modify, and scale without asking anyone for permission.

Every engagement includes structured team training and a comprehensive handover process. We do not believe in creating dependency. Our goal is to make your team self-sufficient as quickly as possible, with full documentation, training sessions, and 30 days of post-launch support to smooth the transition. Whether we are building automated customer service agents, intelligent document processing pipelines, or custom internal tools, the outcome is the same: AI systems that work, that your team understands, and that deliver measurable value from the day they go live.

What you get

Deliverables from a typical engagement

1

Production AI workflows and agents

Fully functional AI automations and agents running in your environment, built on open-source tools like n8n, CrewAI, and LangGraph.

2

Data integration pipelines

Robust pipelines connecting your existing data sources to AI systems, with proper validation, error handling, and monitoring.

3

Custom dashboards and interfaces

Purpose-built tools and interfaces that make AI outputs accessible and actionable for your teams.

4

Technical documentation

Comprehensive documentation covering architecture, configuration, maintenance procedures, and troubleshooting guides.

5

Team training and handover

Structured training sessions for your technical and operational teams, ensuring they can manage and extend the systems independently.

6

30-day post-launch support

Dedicated support after go-live to resolve issues, fine-tune performance, and ensure a smooth transition to steady-state operations.

Get started

8-16 weeks