Service 03

Custom AI Agents in Boca Raton

Task-completing agents with tools, memory, and hard operational limits.

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Overview

Agents that actually finish work: research, triage, quoting, onboarding, internal support. Every agent ships with tool permissions, audit logs, escalation paths, and evaluation suites before it touches production.

Outcomes

Agents that complete multi-step tasks, not just answer questions.
Hard tool-permission boundaries so an agent cannot act outside its lane.
Full audit trail of every action, tool call, and escalation.
Cost and latency budgets enforced, so usage stays predictable.

Define the job and where a person takes over

Custom AI agents can carry out multi-step work such as triage, research and internal support. The design starts with the tools the agent can use, the information it can access and the decisions that need human approval.

Bring one repeatable workflow and examples of both routine and unusual requests. Those examples can become evaluation scenarios for testing whether the agent completes the job or escalates appropriately.

What you receive

What comes with a custom AI agent

Agent architecture and tool design

Evaluation and regression suites

Permissioning and audit trails

Cost and latency budgets

How we deliver

How we test permissions and escalation

Scope

A fixed-scope definition session pins down the inputs, outputs, success metrics, and the single process we will touch — nothing more.

Prove

A narrow pilot with agreed metrics. If the numbers do not hold against your baseline, we stop and tell you before any further spend.

Build

Production-grade build inside your environment: security review, access controls, observability, and human-in-the-loop where accuracy matters.

Hand over

Documentation, enablement, and a support model so your team operates the system without us. Quarterly reviews route savings into the next initiative.

Questions

What clients ask first.

01How is an agent different from a chatbot?

A chatbot responds. An agent uses tools, holds memory across steps, makes decisions, and completes a task end-to-end — with escalation to a human when it hits its limits.

02Can the agent take actions in our systems?

Yes, but only through explicitly permissioned tools. Every action is logged and reversible where possible, and sensitive actions require human approval by default.

03How do you stop it degrading over time?

Each agent ships with an evaluation and regression suite run on every change, plus live monitoring of cost, latency, and outcome quality.

AI Agents vs. Traditional Automation: When to Use Each

Agents are powerful and expensive. Rules-based automation is boring and reliable. Here is how to choose without over-engineering.

January 20, 2025 · 6 min read

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Evaluating AI Agents: Metrics That Matter Beyond Accuracy

Accuracy is the easy number. Cost, latency, tool-call success and escalation rate decide whether an agent ships.

March 24, 2025 · 7 min read

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Cost and Latency Budgets for Production AI Agents

Treat cost and latency like features with specs, not variables to optimise later.

April 21, 2025 · 6 min read

Related engagements

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01AI ConsultingBoard-level clarity on where AI creates margin — and where it burns budget.02AI AutomationReplace the manual middle of your process with reliable, monitored automation.04Voice AINatural phone agents that qualify, book, and route without hold music.05Workflow AutomationEnd-to-end orchestration across the twelve tools your team lives in.

Authoritative references

Standards and research behind our ai agents work.

The external references we cite most often when delivering ai agents for Palm Beach and Broward teams — governance, adoption and value-capture research we align to rather than reinvent.

McKinsey — The State of AI

Annual benchmark on enterprise AI adoption, value capture and the gap between leaders and laggards.

Open reference

Harvard Business Review — Adopting AI

Practical guidance on sequencing AI into operations and avoiding the common adoption traps.

Open reference

Stanford AI Index Report

The most-cited annual measure of AI capability, investment and deployment across industry.

Open reference

Gartner — AI Insights

Enterprise research on AI strategy, governance and the automation technology landscape.

Open reference

Forrester — AI Research

Analyst coverage of AI platforms, automation platforms and the build-vs-buy economics.

Open reference

NIST AI Risk Management Framework

The US national standard for governing AI risk in production — the governance baseline we align to.

Open reference

OECD AI Principles

The first intergovernmental standard on trustworthy AI, adopted by 40+ countries.

Open reference

MIT Sloan — AI & Business Strategy

Research-backed guidance on where AI creates margin and how to sequence adoption.

Open reference

Is ai agents the right fit for your operation?

A 30-minute discovery call, no deck required. You leave with an honest read on feasibility, sequencing and rough cost.

Start the conversation

What should a custom AI agent be allowed to do?

Start with the smallest set of tasks, data and tools needed for the job. Define when the agent can act, what needs approval and how operators can review its actions.