LuMay AI Agents

Build Intelligent AI Agents That Turn Business Goals Into Action

Custom AI agent development designed for production and secure business workflow automation.

LuMay develops AI agents that understand requests, retrieve information, use approved tools, complete multi-step tasks, and work alongside your teams — from focused task agents to enterprise multi-agent systems, built for production, not just demos.

Beyond Chatbots

Move Beyond AI That Only Answers Questions

Standard chatbots generate content or respond to queries. AI agents execute multi-step workflows autonomously with control.

Goal Interpretation & Execution

Most AI applications generate content or answer questions. AI agents go further — interpreting a goal, planning the steps to complete it, retrieving information, taking approved actions, and checking the result. A support agent, for example, can understand a request, pull account and order data, search the knowledge base, resolve or recommend a fix, update the ticket, and escalate when human judgment is needed.

Systems Orchestration & Memory

Building a reliable agent takes more than connecting a language model to an interface — it needs memory, system integrations, access controls, orchestration, validation, monitoring, and human-approval mechanisms. We bring these together into solutions that are useful, controlled, and tied to measurable outcomes.

Architecture & Logic

How a Production AI Agent Works

A prompt connected to a language model isn't enough for a reliable enterprise solution — production agents need all of these components.

Step 1

Request or Trigger

Step 2

Goal & Instructions

Step 3

Reasoning & Planning

Step 4

Knowledge Retrieval

Step 5

Memory & State

Step 6

Tool Selection

Step 7

Action Execution

Step 8

Validation & Approval

Step 9

Monitoring & Evaluation

Comparison Matrix

AI Agents vs. Chatbots, Copilots, and Automation

AI agents aren't always the right fit — a simple chatbot may suit information access, and traditional automation may suit stable, predictable processes. We assess your workflow before recommending an approach.

CapabilityAI AgentAI CopilotChatbotAutomation
Main purposeComplete goals/workflowsAssist usersAnswer questionsExecute fixed rules
AutonomyControlled/semi-autonomousUser-directedMostly reactiveFully predefined
Multi-step tasksYesLimitedUsually limitedYes, if predictable
Tool useDynamicUser-approvedLimitedPreconfigured
Human involvementBased on riskHighModerateRequired for exceptions
Best useVariable workflowsKnowledge workInfo supportStable processes
Our Services

Our AI Agent Development Services

We offer end-to-end development services to plan, build, integrate, and scale secure autonomous agents inside your enterprise.

01

AI Agent Strategy & Consulting

We review your workflows, data, and risk profile to identify which tasks are right for agentic automation, then deliver an architecture and integration roadmap tied to a defined business outcome.

02

AI Agent Proof of Concept

We build a focused agent around one workflow, test it against real data and success criteria, and confirm whether it can reliably do useful work before you scale it.

03

Custom AI Agent Development

We design agents around your workflows and systems — able to interpret requests, retrieve approved information, call tools, hold context, produce structured outputs, seek approval, and escalate exceptions — each with a defined role, permissions, and boundaries.

04

Single-Purpose Agents

Focused agents built for one job — classifying requests, extracting contract or invoice data, updating CRM records, summarizing meetings — often the easiest starting point to test, monitor, and govern.

05

Multi-Agent Systems

For complex workflows, we design specialized agents (collection, analysis, validation) coordinated by a supervisor agent, with task delegation, shared state, conflict resolution, and human escalation — used only when it beats a simpler single-agent approach.

06

AI Copilots

Copilots that retrieve information, summarize documents, draft content, and recommend next steps while keeping the user in control — built for employees, customers, sales, developers, and other roles.

07

Conversational & Voice Agents

Text and voice agents for support, scheduling, onboarding, and service requests, with speech recognition, multilingual support, and real-time system integration where needed.

08

AI Workflow Automation Agents

Agents that coordinate across applications and teams — collecting data, applying business rules, updating systems, and routing exceptions — for onboarding, invoicing, claims, procurement, and similar processes, combined with traditional automation where full predictability is required.

09

RAG-Powered Knowledge Agents

Agents that retrieve from approved sources — policies, manuals, contracts, support articles — to generate accurate, context-aware answers, with attention to permissions, freshness, accuracy, and sensitive-data protection.

10

AI Agent Integration

We connect agents to your CRM, ERP, HR, support, and analytics systems, handling authentication, permissions, retries, failure recovery, and audit logging.

11

Security & Governance

Role-based access, least-privilege permissions, tool allowlists, input/output validation, prompt-injection protection, approval gates, spending limits, and full execution logs — routing sensitive actions to an authorized person before execution.

12

Testing & Evaluation

We test full workflow outcomes, not just responses — task completion, tool accuracy, edge cases, safety, and prompt-injection scenarios — to confirm the agent uses the right data, picks the right tool, and escalates when it should.

13

Deployment & Monitoring

Cloud or private deployment with CI/CD, version control, rollback, and scaling, followed by ongoing monitoring of task success, errors, latency, cost, and user feedback.

14

Maintenance & Optimization

Ongoing incident investigation, prompt and workflow refinement, model migration, new integrations, and security and performance tuning as your needs evolve.

Business Benefits

What AI Agents Improve

Automate complex workflows across applications, documents, and teams.

Reduce repetitive research, data entry, and follow-up work.

Improve response times, including outside business hours.

Increase consistency through clear rules and structured outputs.

Improve knowledge access without manual searching.

Support faster decisions while keeping judgment with your people.

Extend existing applications without replacing your tech stack.

Improve auditability with full execution logs.

Scale capacity so employees focus on exceptions and higher-value work.

Agent Types

Types of AI Agents We Develop

We build specialized agents customized to specific departmental goals, systems, and operational boundaries.

Customer-Support Agents

resolve requests, update tickets, escalate complex cases

Sales Agents

research accounts, enrich leads, keep CRM records current

Research Agents

gather and compare information, prepare structured reports

Data-Analysis Agents

retrieve data, run approved analyses, explain findings

Operations Agents

coordinate recurring cross-team tasks and approvals

Finance & Accounting Agents

invoice processing, reconciliation, exception detection

HR & Employee-Support Agents

onboarding, policy questions, scheduling

IT Support Agents

triage incidents, recommend fixes, escalate unresolved issues

Software Engineering Agents

code review, test generation, debugging support

Document-Processing Agents

extract, classify, and validate contracts and forms

Knowledge Agents

surface reliable answers from approved sources

Scheduling Agents

coordinate availability, book and update appointments

How We Deliver

Our AI Agent Development Process

Our engineering lifecycle focuses on security, model validation, and progressive rollout to guarantee reliability.

Discovery & Assessment

We define objectives, confirm fit, and outline technical security requirements.

Architecture & Design

We map out the agent models, memory states, tools, and integration paths.

Proof of Concept

We construct a lightweight prototype to validate the core workflow with real data.

Development & Integration

We build the complete agent and connect it safely to your enterprise systems.

Testing & Deployment

We run security reviews, deploy in stages, and monitor initial outcomes.

Risk Mitigation

How We Build Reliable Production Agents

We safeguard your applications against standard LLM edge cases, loops, hallucinations, and unauthorized actions.

Incorrect actions

grounding, structured outputs, validation, human approval

Failed tools

timeouts, retries, fallback paths, safe termination

Loops

step limits, execution budgets, duplicate-action controls

Sensitive-data exposure

access controls, filtering, encryption, retention policies

Unauthorized actions

least privilege, tool allowlists, approval gates, logs

Missing auditability

full logging of activity, calls, approvals, and outcomes

Frequently Asked Questions

What is AI agent development?

The process of building software that understands objectives, retrieves information, uses tools, and completes multi-step tasks — covering model selection, architecture, integrations, testing, security, and monitoring.

How is an AI agent different from a chatbot?

A chatbot mainly answers questions. An agent can also plan tasks, interact with applications, retrieve records, and complete approved workflow steps.

What's the difference between an agent and a copilot?

A copilot supports a user with information or drafts. An agent can independently perform approved actions, though sensitive tasks can still require human approval.

Should we use one agent or multiple?

A single agent usually suits a focused workflow. Multiple agents help when a process has clearly separate responsibilities needing different tools or knowledge.

Can agents integrate with our existing systems?

Yes — CRM, ERP, HR, support, document, analytics, and custom systems, wherever suitable APIs and permissions exist.

Can an agent use private company data?

Yes, through controlled databases, APIs, or retrieval systems with appropriate access controls, encryption, and retention rules.

How do you prevent an agent from taking the wrong action?

Through tool restrictions, structured outputs, validation, confidence thresholds, approval gates, testing, and monitoring.

Can agents work with human approval?

Yes — an agent can prepare an action and route it to an authorized person for review before execution.

How are agent activities monitored?

We log model requests, retrieved data, tool calls, approvals, errors, latency, cost, and final outcomes.

Which AI model is best for an agent?

It depends on task complexity, accuracy needs, tool-use reliability, speed, cost, and privacy requirements — there's no single best model.

How long does development take?

It depends on workflow complexity, integrations, and security needs. A proof of concept generally takes less time than a full multi-agent platform.

How much does it cost?

Cost depends on the agent's capabilities, architecture, integrations, security, usage, and maintenance needs.

Can you improve an existing agent?

Yes — we can evaluate and improve architecture, prompts, integrations, retrieval, reliability, and cost.

What support is needed after deployment?

Ongoing monitoring, incident handling, model reviews, integration maintenance, security updates, and optimization.

Turn Your Business Workflow Into a Production-Ready AI Agent

Whether you're exploring your first AI agent, validating a proof of concept, or building an enterprise agent platform, LuMay combines strategy, secure architecture, evaluation, and deployment to build agents that support real business work.