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AI Agent Development Services

Build autonomous AI agents capable of planning tasks, calling API tools, querying databases, and executing multi-step business workflows.

01. What I Do 02. Services Included 03. Process 04. FAQ

01 / Overview

Core Capabilities & Scope

Unlike simple chatbots that only reply to prompt inputs, autonomous AI agents are designed to execute complex, multi-step tasks independently. By combining LLM reasoning with custom code "tools," an AI agent can plan a workflow, query databases, trigger external APIs, and audit its own results. I provide specialized AI agent development services, building custom agents that run on Node.js. I specialize in prompt loops, tool-calling structures, and secure sandbox database executions. Whether you need an agent that audits incoming lead emails, searches the web for market metrics, drafts a structured report, and emails it directly to your sales team, I construct resilient agent frameworks that automate manual tasks and lower operational costs.

Who It Is For

·Businesses looking to automate multi-step email workflows
·SaaS companies building autonomous software workers
·Marketing agencies needing automated SEO reporting agents
·Teams looking to automate data entry and verification tasks

Problems Solved

·Time lost manually running tasks across separate APIs
·Repetitive copy-paste data cleaning steps
·Inability of simple AI tools to execute code or write to databases
·Lack of automated checks validating AI generation accuracy

Core Benefits

·Autonomous task execution running 24/7 in the background
·Self-correcting prompt loops that audit and fix formatting errors
·Custom code tools allowing agents to read/write databases
·Detailed execution log files showing the agent’s reasoning steps

02 / Offerings

What Is Included

A comprehensive breakdown of all features and tasks handled under the AI Agent Dev scope.

Tool-Calling API Setup

Exposing custom database search and update functions as tools the AI model can trigger.

Reasoning & Planning Loops

Implementing ReAct (Reasoning and Acting) loops allowing the agent to formulate step-by-step plans.

E-Mail & Communication Hooks

Orchestrating agents to listen for incoming emails, parse requirements, and email solutions.

Web Scraping & Analysis Tools

Equipping agents with web scrapers to gather live metrics and compile comparative charts.

Execution Logging & Audits

Writing detailed server logs showing the agent’s thought processes and actions taken.

Automated Correction Scripts

Adding validator steps that check generated text for criteria before final submission.

03 / Technologies

Tech Stack Focus

Technologies selected for scalability, speed, and production reliability.

Node.js

The fast server runtime used to execute agent loops and coordinate API request flows.

LangChain / LangGraph

Developer frameworks designed to construct complex stateful multi-agent workflows.

TypeScript

Enforcing typed schemas on tools, keeping agent executions predictable.

Redis Queue

Managing asynchronous agent runs in background execution tasks.

Puppeteer

Headless browser tool allowing the agent to scrape public text data from search engines.

04 / Product Scopes

Solutions I Build

Custom applications and system layers built to replace slow, manual operations.

Autonomous Email Lead Response AgentsSelf-Auditing SEO Content WritersAutomated Competitor Pricing ScrapersMulti-Step Database CleanersAutomated Social Media Post SchedulersLog Audit & Notification Triggers

05 / Methodology

The Development Process

A structured lifecycle designed to build correct architectures, catch logical gaps early, and launch securely.

01Phase 1

Discovery

Understanding business goals, target audience flows, and scoping out requirements into a clear backlog document.

02Phase 2

Planning

Drafting data schema flowcharts, API specifications, user journeys, and structuring milestone-based delivery dates.

03Phase 3

Architecture

Selecting optimized technologies, designing relational table linkages or NoSQL patterns, and preparing environment structures.

04Phase 4

Development

Writing clean, typed, modular code with daily version control commits, strict validation guards, and design system hooks.

05Phase 5

Testing

Running unit validation scripts, API route calls, mobile-responsive layout testing, and security scanning for loops or leaks.

06Phase 6

Deployment

Publishing builds to secure edge servers with automatic compilation pipelines, database indexing checks, and custom domain paths.

07Phase 7

Maintenance

Monitoring server log files, installing safety package updates, generating databases backups, and executing performance tweaks.

06 / Commitment

Why Work With Me

Clean, secure code and direct communication pathways without broker layers.

Tool-Calling Experts

I write secure, validated code tools for agents to query DBs safely.

State Management Design

Ensuring multi-step agent runs maintain memory of past outputs.

API Security Focused

Strict parameters ensuring agents only trigger safe, read-scoped operations.

Log Tracking Shipped

Providing clear admin dashboards to review what actions the agent took.

6+ Years Experience

Deep full-stack experience deploying production software.

14-Day Staging Follow-up

Monitoring agent runs and fine-tuning prompts to eliminate logic loops.

07 / Case Studies

Featured Projects & Proof

Selected production builds demonstrating engineering excellence in AI Agent Dev services.

Backend2025

Aracuda Inspection SaaS Platform

A multi-role inspection SaaS marketplace and CRM — managing client bookings, agent bidding, inspector scheduling, secure document uploads, and subscription billing in one Laravel platform.

Challenge

Managing complex workflows involving five different stakeholder roles — admins, buyers, inspectors, agents, and staff — was highly fragmented, with no single system coordinating who does what and when. The business struggled with manual scheduling that led to missed or double-booked inspections, delayed inspection reporting because there was no structured way for inspectors to submit findings, insecure document handling for sensitive inspection reports, and complex payment splits between agents and the platform that had to be calculated and tracked by hand. None of this scaled, and every new client or inspector added more manual coordination overhead rather than the business getting more efficient — exactly the kind of operational bottleneck a SaaS marketplace platform is meant to remove.

Solution

Architected a Laravel and MySQL backend built around security from the ground up — prepared statements, hashed credentials, and role-based access control across every one of the five user roles. Integrated a payment gateway with a full subscription and billing module so the platform could charge for plans and handle payment splits automatically instead of manually. Implemented a secure multi-role bidding system letting agents bid on and win inspection jobs, built automated inspection scheduling to remove manual coordination, enabled secure document uploads for inspection reports with per-client storage isolation, and shipped an interactive analytics reporting dashboard giving admins real-time visibility across bookings, bidding activity, and revenue. Every part of the system was designed as a repeatable SaaS workflow — new clients, agents, and inspectors can be onboarded without custom development work, which is what makes it a genuine multi-role marketplace platform rather than a one-off internal tool.

Results

Scalable marketplace SaaS platform automating workflows for clients, agents, inspectors, and admins with built-in subscription billing and secure document uploads.

LaravelMySQLJavaScript

Case Study

08 / Questions

Service FAQ

Detailed answers regarding scopes, pricing, timelines, and contract conditions for AI Agent Dev implementations.

What is an autonomous AI agent?▼

An AI agent is a software system that uses an LLM to reason, plan, and call custom code tools (like web search or database queries) to complete multi-step tasks independently.

How does an agent call external tools?▼

I register custom JavaScript functions (tools) with description metadata. The LLM reads the description, decides which tool is needed, and returns JSON arguments to execute the function.

Is it safe to let an AI write to my database?▼

Yes. I enforce strict data validation, schema validation, and parameter sanitization on all tools, ensuring the agent cannot execute arbitrary queries.

What is the ReAct framework in AI agents?▼

ReAct stands for Reasoning and Acting. The agent cycles through: Thought (planning what to do), Action (calling a tool), and Observation (evaluating the tool output).

Can an AI agent run in the background?▼

Yes. I configure agents to run as background worker tasks triggered by cron schedules, incoming emails, webhooks, or user action alerts.

How do you prevent an AI agent from running in endless loops?▼

I implement strict iteration caps (e.g. max 10 tool calls per run) and token usage limits to terminate runaway loops automatically.

Can the agent search the web for metrics?▼

Yes. I equip agents with search API integration (like SerpAPI) or Puppeteer scrapers to extract text from top search ranking sites.

How long does custom AI agent development take?▼

Developing a multi-step, tool-calling AI agent with detailed execution logs takes between 3 to 6 weeks, depending on the tool complexity.

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