Automation & AI That Does Actual Work.
We build AI agents, automate workflows with n8n/Make/Python, and engineer CI/CD pipelines - replacing manual tasks with systems that run reliably, repeatedly, and without waking anyone up.
Service Overview
The gap between 'AI is amazing' and 'AI is doing something useful' is enormous. We close that gap. We take AI from experiment to operation - building LLM-powered agents, RAG systems, and custom integrations that connect to your actual data. We also build the DevOps infrastructure that keeps everything shipping: CI/CD pipelines, Infrastructure as Code, and configuration management that turns releases from manual events into automated processes.
Common Scenarios
Drowning in Docs
RAG systems that let you query contracts, reports, and records in plain English - with citations.
Manual Data Entry
AI that reads emails/PDFs and enters structured data into your ERP/CRM automatically.
The 'Bus Factor' Deploy
Automating the release process that only one senior engineer knows how to run.
The Stalled Prototype
Turning a fragile demo notebook into a robust, secure production application.
Infrastructure Sprawl
Importing unmanaged cloud resources into version-controlled Terraform state.
CEO Wants AI Strategy
A structured evaluation and phased adoption roadmap - not just a list of tools.
What's Included
- Custom LLM Agent Development (OpenAI/Claude/Gemini)
- RAG Systems (Chat with Your Documents)
- AI Workflow Automation (n8n/Make/Python)
- CI/CD Pipeline Design (Jenkins/GitHub Actions/Azure)
- Infrastructure as Code (Terraform & Bicep)
- Desktop Automation Agents (osctrl)
- Container Orchestration (Kubernetes/Docker)
- AI Security, Governance & Risk Frameworks
- Prompt Engineering & Optimization
- GitOps & Automated Release Strategies
How We Deliver This
Define the Problem
Moving from 'we want AI' or 'we need automation' to a specific, scoped use case with clear success criteria.
Assess Feasibility
Honest evaluation of whether AI, scripting, or pipeline automation is the right tool - and which approach fits your stack.
Build & Iterate
Focused development cycles starting with core capabilities. High-impact pipelines and automations first, then expand.
Production-ize
Adding error handling, logging, rate limiting, security guardrails, and rollback capabilities.
Hand Off
Training your team to own, maintain, and extend the system. Complete documentation and runbooks.
Perfect For:
- Businesses drowning in document processing or manual data entry
- Engineering teams with manual, slow deployments
- Organizations needing AI-powered internal tools
- Companies with stalled AI prototypes that need production-izing
- Executive teams under pressure to adopt AI with no clear roadmap
- Regulated industries (Healthcare/Finance) needing compliant automation
Proven Capabilities
- Production LLM development & deployment
- Enterprise AI strategy & implementation at scale
- Enterprise-grade CI/CD automation frameworks
- Infrastructure-as-Code in PCI/FIPS environments
- 100+ hours of AI training delivered to teams
- Production computer vision systems (OpenCV)
Common Questions
How much does workflow automation or AI integration cost?
A focused automation project typically costs $3,000-$15,000 depending on complexity. Simple n8n or Make workflows start at the lower end. Custom AI agents with RAG, function calling, and production hardening are at the higher end. We serve businesses in Ormond Beach, Daytona Beach, and across Central Florida, and always scope with a free discovery call first.
What automation tools do you use?
We work with n8n, Make (Integromat), Python scripts, and custom TypeScript solutions depending on complexity. For CI/CD, we use Jenkins, GitHub Actions, and Azure DevOps. For infrastructure, Terraform and Bicep. We pick the tool that fits your stack and budget rather than forcing a single platform.
Can you build AI that works with our existing systems?
Yes. We specialize in integration, connecting AI to your CRM, ERP, databases, and APIs. We use function calling and tool use patterns so AI agents can read from and write to your actual business systems safely. Our clients across Volusia County and Central Florida run everything from legacy on-premise systems to modern cloud stacks.
How long does it take to build a custom AI agent?
A focused proof-of-concept typically takes 2-4 weeks. Production deployment with error handling, security, and monitoring takes 6-12 weeks depending on complexity. We start with the highest-value use case and iterate from there.
Do you offer AI strategy consulting without building anything?
Absolutely. We offer executive AI roadmaps, use-case prioritization, and platform evaluations as standalone engagements. You get a phased adoption plan with clear milestones and costs. Many businesses in the Daytona Beach and Ormond Beach area start here before committing to a build.
What if we don't know where to start with automation?
That is the most common starting point. We begin with a discovery session to map your workflows, identify bottlenecks, and score opportunities by business impact versus effort. You get a ranked list of projects designed to start with a quick win and build momentum.
Is AI safe to use with sensitive business data?
It can be, with the right architecture. We build AI systems with data isolation, access controls, and audit logging. For regulated industries like healthcare and finance, we design compliant AI pipelines that keep sensitive data within your environment and never send it to third-party models without proper safeguards.
Every Engagement Starts with a Conversation.
Not sure if this is the right fit? Let's talk through your specific requirements.