Internal systems.
Custom agents and workflows that work across your tools, with people in control.
AI engineering and development services.
Build AI into the systems you run and the products your customers use.
We design and build AI that works inside your tools and in front of your customers, with people in control where it matters.
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Start with the problem.
We begin with the people who will use it and the systems it has to work with. Then we build against your real data, not a demo.
Scope
The problem, the users, and what good looks like, agreed before we build.
Build
Agents, integrations, and interfaces that work with the tools you already use.
Hand off
Tested, documented, and owned by someone on your team.
Build what comes next.
AI that runs inside your operations, and AI your customers can use.
Customer-facing products.
AI features and products your customers can actually use.
What our AI development work covers.
Four kinds of build. Most projects use more than one.
Custom AI agents
An agent reads what comes in, decides what to do next, and works across your tools, with a person approving anything that matters. Orders, bills, intake and reports are the usual starting points. Our page on AI agent development covers the kinds of work agents take off a team.MCP connectors
A connector is an MCP server: the piece that lets Claude reach your records and answer a real question about your buildings, orders or contracts instead of guessing. We deploy ours on Cloudflare Workers. People add the connector in Claude and sign in through a browser, so there is no API key to paste into a file.Internal tools
A process held together by spreadsheets and memory becomes a tool the team can run. For product teams, that can mean coding agents inside the repo: automated code review, security review agents and MCP tools that give the agent the context it needs.Customer-facing AI
AI your customers touch directly: an upload that turns a photo into a production brief, or a phone agent that runs a first conversation and hands a written summary to a person. The customer gets a faster answer, and a person still signs off on the result.
Not everything needs AI. If the steps never change and the information arrives clean, a plain automation is cheaper, and we will say so. If that sounds like your process, start with our workflow automation consultant in Tampa page.
Based in Tampa Bay, building for teams nationwide. Across Tampa Bay we can work in the room with you; everywhere else runs over video. Local teams can read more about AI consulting in Tampa.
Work you can read in full.
Each one is written up as a case study: the problem, what we built and who owns it now.
- spARK Labs connectorA remote MCP server on Cloudflare Workers that connects Claude to BossHub, Verkada, Nexudus and Outlook for a nonprofit innovation hub in St. Petersburg.
- Kara, our intake agentA five-minute AI phone call that replaced our own 90-minute discovery calls, built on ElevenLabs, Claude, Cal.com, Telnyx and Cloudflare Workflows.
- County records connectorHillsborough, Pinellas, Pasco and Polk property records inside Claude for Tampa Bay commercial real estate brokers.
- Fishin PrintsA customer's catch photo becomes a production brief and print-ready artwork, with a person approving the art.
- BeBriefCodex set up inside a full-stack product team: code review, security review agents, remote agents and MCP tools.
- Why Cloudflare WorkersWhy every client MCP server we build runs on Workers: one-command deploys and browser sign-in instead of API keys.
Why you need us.
Getting AI to work in a demo is easy. Getting it to work every day is the job.
Real data is messy.
We build against your actual systems and exceptions from the start.
People need to stay in control.
Review points and permissions are part of the design, not added later.
Someone has to own it.
We hand over a system your team understands and can keep running.
Some work needs a plan first.
When the process itself has to change, AI Transformation maps it before we build.