AI Agents

Custom AI Agent Development

Off-the-shelf AI tools solve generic problems. If your business has a workflow that no existing tool handles, I build a custom AI agent designed specifically for it.

Ex-Google Strategist
🤖OpenAI / Claude / Custom LLM
📊13+ Years Experience
Built for Your Specific Workflow
🔗Full API and System Integration

What's Included

An AI Agent Built Around Your Business — Not Around a Template

Every custom agent project starts with a discovery phase to understand the workflow, the decision logic, the tools involved, and the outcomes the agent needs to produce. What gets built depends entirely on what you need — not on what a platform happens to support.

🔍

Workflow Discovery and Scoping

A structured discovery process to understand the workflow in detail — inputs, decision points, tools involved, exception handling, and the output the agent needs to produce.

🏗️

Custom Agent Architecture

Design the agent's structure: single-agent vs. multi-agent orchestration, tool definitions, memory architecture, and the decision loop logic that controls how it works through a task.

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Custom Tool and API Development

Build custom tool functions that connect the agent to your internal systems, proprietary data sources, and third-party APIs that no existing platform integrates with out of the box.

🧠

Domain-Specific Training and Prompting

Craft the system prompt, few-shot examples, and knowledge base that give the agent deep expertise in your domain — the difference between a generic AI and one that knows your business.

🛡️

Testing and Reliability Engineering

Build an evaluation suite with real task scenarios and edge cases. The agent only ships when it handles the hard cases — not just the easy ones.

📋

Documentation and Handoff

Full technical documentation covering the agent's architecture, tool definitions, prompt structure, and maintenance guide. You own and understand what was built.

How It Works

My Custom Agent Development Process

I scope every project before quoting it. The complexity of an agent build varies significantly based on the number of tools, the decision complexity, and the quality of existing system APIs. Discovery prevents surprises.

1

Discovery

A paid discovery engagement to fully map the workflow, assess technical feasibility, identify integration requirements, and define the success criteria for the agent.

2

Architecture and Scoping

Deliver an architecture document and fixed-scope build proposal. You know exactly what will be built, how long it will take, and what the agent will and will not do.

3

Build and Iterate

Build in milestones with working demos at each stage. You see the agent working on real tasks throughout the build — not just at the end.

4

Test, Deploy, and Hand Off

Run the evaluation suite, deploy to your environment, and hand off with full documentation and a 30-day support window for post-launch issues.

100%

Built around your specific workflow — not adapted from a template

Full

Ownership of the agent architecture and codebase

2-8 wk

Typical build timeline depending on scope

Who It's For

For Businesses With Workflows That No Existing Tool Handles

Custom agent development makes sense when the workflow is complex enough that off-the-shelf automation falls short, but valuable enough that a custom build pays for itself within a few months.

Companies with Proprietary Data Sources Businesses with Complex Multi-Step Decisions Operations with High-Volume Manual Processing Agencies with Bespoke Client Workflows Enterprises with Legacy System Integrations Founders with a Specific AI Use Case in Mind

Build an AI Agent That Works the Way Your Business Works

Book a free strategy session. Describe the workflow you want to automate and I will tell you honestly whether a custom agent is the right approach, and what the build would look like.

Get a Free 30-Minute Strategy Session →