AI Agent Implementation
Production AI agents wired into your revenue program, not another sandbox demo.
AI agents are at their most useful when they do live work inside a working business: qualifying leads, drafting outreach, running research, triaging inbound, updating systems of record. I scope, build, and ship the agent end to end, wire it into your stack, evaluate it against measured outcomes, and hand it off to your team so it keeps running after I leave.
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What you get
Agent Scoping & Design
I identify the highest-impact agent jobs in your revenue program and design them around live workflows, live data, and clear handoffs to humans.
Production Implementation
Agents built on the right combination of LLMs, orchestration, and your existing stack: CRM, sequencer, helpdesk, data warehouse, internal APIs.
Evaluation & Guardrails
Quality, accuracy, and brand-safety evaluations baked in from day one, with human-in-the-loop checkpoints anywhere the stakes justify them.
Hand-off & Ownership
Documentation, runbooks, and team training so your operators own the agent after launch instead of being stuck calling me every time it misbehaves.
What we put in place together
- Agent opportunity map and prioritized build list
- Production agent build with prompt, tools, and integrations
- Evaluation harness with quality, safety, and outcome metrics
- Runbooks, alerting, and human-in-the-loop checkpoints
- Team training and ownership transfer plan
AI agents that earn their seat on the team, running live work, measured against clear outcomes, and owned by your operators.
Book a Discovery CallWhere AI Agent Implementation shows up in your business
The four use cases this service most often plugs into, each with its own playbook, deliverables, and outcome.
Who I run AI Agent Implementation for
The industries I know best, each with a different buyer, sales process, and AI opportunity.
Questions buyers ask about AI Agent Implementation
The objections I hear most often before a discovery call, answered up front.
Most often: inbound qualification and routing agents, research and account-prep agents for sales, content and lifecycle drafting agents for marketing, and ops agents that keep CRM and downstream systems in sync. I focus on agents that move revenue or save material operator time.
I am platform-agnostic. Common stacks include OpenAI and Anthropic models, orchestration in n8n, Clay, custom Node or Python services, and direct integrations with HubSpot, Salesforce, Slack, and your data warehouse. I pick the simplest stack that meets the SLA.
Every build ships with an evaluation harness, structured outputs where possible, retry and fallback logic, and human-in-the-loop checkpoints on anything customer-facing or financially material. I treat reliability as a first-class deliverable, not a nice-to-have.
First production agents typically ship in 4 to 8 weeks depending on integration depth. I scope each engagement to the smallest valuable agent first, then expand once it is earning its keep.
Stop demoing agents. Start running them in production.
30 minutes to scope an AI agent that does useful work across sales, marketing, ops, or support, built, evaluated, and handed off to your team.