AI agents for customer service
Answer recurring questions, retrieve order or product information, collect context, and escalate complex conversations to the right person.
Custom AI Agent Development Services for Business
We design, build, and integrate AI agents that help customer service, sales, and operations teams complete real work — grounded in your business data, connected to your systems, and governed by clear human controls.
Business-specific data
Secure integrations
Human oversight
AI agent development company
Move AI from experimentation into daily operations
Useful AI agents do more than generate text. They understand context, retrieve approved information, use connected tools, follow business rules, and know when to involve a person.
Mercabits works as an implementation-focused AI agency. We identify a high-value workflow, build the agentic AI solution around your real processes, and connect it to the software your team already uses.
AI agents for business
AI agents built around measurable business outcomes
Our AI agent development services begin with a defined job, trusted information, approved actions, and a clear way to measure whether the agent is creating value.
Sales and lead qualification
Engage prospects, ask structured questions, recommend next steps, and send qualified opportunities into your sales workflow.
Knowledge and RAG agents
Give teams fast, cited answers from approved policies, documentation, catalogs, and internal knowledge instead of scattered files.
Workflow automation agents
Classify requests, process documents, prepare summaries, route work, and coordinate repeatable tasks across connected systems.
Enterprise AI agents
Role-aware agents designed for larger teams, controlled data access, defined permissions, auditability, and human approvals.
AI agent integration
Connect agents with your website, CRM, WhatsApp, e-commerce platform, analytics, knowledge base, and internal applications.
Production-ready agentic AI
Designed for reliability, control, and adoption
The model is only one component. Production-ready agentic AI solutions depend on the complete system around it.
Grounded in trusted data
Retrieval and knowledge architectures help agents answer from approved business sources instead of relying on generic model knowledge.
Guardrails and permissions
We define what the agent can access, which actions it can take, and where review or human approval is required.
Evaluation and monitoring
Test scenarios, quality checks, logs, and outcome metrics make performance visible before and after launch.
Human-centered implementation
We design the handoffs, controls, and team workflows that make the agent useful without removing necessary judgment.
Platform or custom build?
AI agent platform or custom development?
AI agent platforms can be useful for testing a narrow idea. A custom implementation becomes important when the agent must reflect your operations, connect securely, and perform reliably at scale.
Evaluate your use caseBest for prototypes and simple tasks
- Prebuilt templates and connectors
- Fast proof-of-concept setup
- Limited workflow customization
- Managed within your own team
Best for operational integration
- Designed around your business process
- Connected to approved data and tools
- Custom guardrails and human handoffs
- Evaluation, monitoring, and improvement
How to build an AI agent
From business workflow to a production AI agent
Building an AI agent starts with a valuable job and ends with a monitored system your team can trust.
Define the outcome
Choose a focused workflow, baseline its current performance, and define the result the agent should improve.
Prepare knowledge
Identify approved data, clean the source material, and define which information the agent may retrieve.
Design actions and rules
Specify tools, permissions, tone, boundaries, fallback behavior, and when a human must take over.
Integrate and evaluate
Connect business systems and test expected, edge, and failure scenarios before the agent reaches users.
Launch and improve
Monitor quality and business outcomes, review exceptions, and refine the system as workflows evolve.
AI in real operations
Implementation beyond the prototype
Our work connects AI strategy with customer experience, team enablement, and the systems businesses use every day.
scOsnaya
360°
digital brand launch
Launched the brand from the ground up across identity, social media, web, organic and paid acquisition, then added AI agents to improve customer service and conversions.
ICEST
LLM
enabled workflows
Defined lead acquisition pipelines, integrated SEO-enabling technologies, and trained teams to apply LLM tools to streamline internal processes.
AI agent FAQ
Questions about building AI agents
Practical answers about use cases, development, integrations, customer service, and enterprise controls.
Discuss your workflowWhat is an AI agency?
An AI agency helps businesses identify, design, build, integrate, and improve practical artificial intelligence solutions. Unlike a software reseller, Mercabits maps the technology to your workflows, data, systems, risk requirements, and measurable business outcomes.
What can AI agents do for a business?
AI agents can answer customer questions, qualify leads, retrieve company knowledge, summarize documents, prepare reports, update business systems, route requests, and coordinate multi-step workflows. The best use cases are repetitive, rules-based processes with clear inputs and outcomes.
How do you create an AI agent?
We begin with one valuable workflow, define the agent actions and limits, connect approved knowledge and tools, create guardrails, test real scenarios, and establish monitoring. A production agent requires more than a prompt: it needs reliable data, integrations, evaluation, security, and a clear human escalation path.
Can AI agents integrate with our existing business tools?
Yes. We can connect AI agents with websites, CRMs, knowledge bases, e-commerce platforms, messaging channels, analytics tools, and internal software through available APIs and secure automation workflows.
How do customer service AI agents work with human teams?
The agent handles approved questions and routine actions, collects context, and transfers conversations when confidence is low or a human decision is required. This hybrid model improves response times while keeping people in control of sensitive or high-value interactions.
How do you keep enterprise AI agents secure and accurate?
We restrict data and tool access by use case, use approved knowledge sources, define action permissions, log important events, test failure scenarios, and place human approval around consequential steps. Monitoring and evaluation continue after launch so the system can improve safely.
Turn one workflow into your first production AI agent
Tell us where your team loses time and we’ll help identify a practical, measurable place to start.
Plan Your AI Agent