WhatsApp · Voice · ERP · CRM
AI agents for business, connected to your processes and systems
When repetitive queries overwhelm your team, information is scattered across systems, or manual processes eat up time, an AI agent can help. We design agents that query data, use tools, integrate with your ERP or CRM and execute tasks within defined rules.
More than 20 developments in production across AI agents, automations and enterprise integrations, in sectors such as healthcare, hospitality, professional services, optical retail, marketing, finance and commercial operations.
How it works
Agent → tools → data → actions → human
Understands the context and the goal of each interaction.
Connects with APIs and internal software.
Queries real business information.
Executes tasks within defined rules.
Hands off when judgment is needed.
What an agent is
What is an AI agent
An AI agent doesn't just answer questions. It can receive information, query systems, use tools and take actions according to your company's rules.
Understands context
It knows what the company does, how it works and the goal of each interaction.
Queries information
It accesses business data, systems and tools to respond with real information.
Uses tools
It connects with APIs, databases and internal software to query or record.
Executes actions
Within a defined scope, it can trigger tasks, validations or handoffs.
When it makes sense
A custom agent isn't for every case. It usually makes sense when the operation grows faster than the team, when there are repetitive tasks, or when you need more order, consistency and access to information.
Chatbot vs. agent vs. automation
A chatbot is not the same as an agent
The difference is how much it understands, what it can query, and what it can do within your operation.
Chatbot
Answers questions from a script or knowledge base. It doesn't query systems or execute actions.
Agent
Understands context, queries data and systems, uses tools and executes actions within defined rules.
Automation
Runs a predefined flow, step by step, without needing to interpret or decide.
When the path is defined, an automation is enough. See how we automate business processes.
Types of agents
Types of AI agents for business
Every agent is designed around the case. These are the types we build, and they're often combined into a single solution.
Support and sales
Agents over WhatsApp, voice, audio or text that inform, assist, organize conversations and hand off when needed.
Internal agents
Assistants that let your team query business information in natural language, with defined permissions and scope.
Voice
Conversational systems for incoming or outgoing calls: they guide conversations, filter, route and record.
Data and business queries
Agents that answer questions about metrics, reports and business information connected to your data.
Operational
Agents that run internal logic, validations, handoffs or actions within a workflow.
ERP and business systems
Custom builds integrated with ERP, CRM, databases or spreadsheets to query, record and trigger actions.
Looking for an AI system for hospitality? See our AI system for hotels.
Need to connect AI with your ERP? See how we build intelligent systems on top of your ERP.
How we build agents
How we build an enterprise agent
Connecting a model to WhatsApp isn't enough. Production quality depends on integration, permissions, limits, observability, validation and maintenance.
We don't promise full autonomy or absolute security. We design agents with clear limits, oversight and traceability.
Model
We choose the model based on the case, language, cost and latency the operation requires.
Instructions
We define how it should behave, what tone to use and the goal of each interaction.
Context
We give it the knowledge base and real information from your company.
Tools and APIs
We connect it with the systems and functions it needs to query or act.
Data
It works with the agreed information, within defined scope and permissions.
Permissions
Each agent only accesses what it should, according to roles and scope.
Memory
When the case requires it, it keeps context between interactions.
Human-in-the-loop
We define when it acts alone and when it asks for confirmation or hands off to a person.
Logs and monitoring
There's a record of what it queries or executes, to audit and improve.
Evaluations
We measure the quality of responses and actions before and after going live.
Agents + humans
The agent works with the person, not instead of them
A well-designed agent can work with different levels of autonomy, depending on what the process needs.
Full autonomy isn't the goal. The goal is for the agent to handle the repetitive and leave people what requires judgment.
Resolve
It responds or executes within the agreed scope.
Ask for confirmation
When the action is sensitive, it checks before executing.
Execute
It performs the task and keeps a record of what it did.
Escalate to a person
It hands off when the query is complex or needs human judgment.
Leave context
It hands the person everything it already knows, so they don't start from zero.
Custom vs. generic
What sets a custom agent apart from a generic platform
The difference isn't the interface, but how much the agent understands about your business, what data it works with, and what it can actually do within your operation.
Understands the business context
It knows what the company does, how it works and the goal of each interaction.
Uses your own knowledge base
It responds with your company's real information, not generic answers from a closed platform.
Follows agreed rules and handoffs
It routes to a person, filters or escalates according to the logic we define with your team.
Integrates with your systems
It connects with CRM, ERP, databases and internal tools to query and record information.
Respects permissions and traceability
It works with roles, permissions and defined scope over the data, and keeps a record of what it queries or executes.
Is tested with real scenarios
Before going live it's tested with real cases and conversations from your operation.
How to choose a provider
How to choose an AI agent provider
Not all providers are the same. These are the criteria worth evaluating before deciding, beyond price or a demo.
Understands your real process
It asks how your company works today and designs the agent around that flow, not a generic template.
Integrates with your systems
It can connect with your CRM, ERP, databases and internal tools, not just answer messages.
Defines limits and human oversight
It makes clear when the agent acts alone and when it hands off to a person, with rules and traceability.
Works with your data and permissions
It respects roles, permissions and scope over information, and keeps a record of what it queries or executes.
Tests with real scenarios
Before going live, it tests with real cases and conversations from your operation.
Explains limits honestly
It tells you what the agent can and can't do, without promising results it can't deliver.
Real cases
Agents working in real operations
Real cases of agents we've built. Each one is adapted to the process, systems and permissions of the company.
La Casa del Multifocal
Problem
Service depended on the human team, with repetitive queries and difficulty responding quickly without creating disorder.
Agent
WhatsApp support agent that responds with audio and text, guides the customer and organizes part of the commercial flow.
Integration
WhatsApp, connected to the business logic and information.
Operational change
Faster responses, more consistent service and greater ability to scale without adding the same operational load.
Cziber
Problem
Accessing business data and metrics required opening multiple systems or requesting reports from the technical team.
Agent
WhatsApp agent that lets you query business data in natural language, without technical knowledge.
Integration
WhatsApp connected to the business data and systems (ERP).
Operational change
Immediate access to key information from your phone, without depending on intermediaries.
Frequently asked questions
Frequently asked questions about AI agents
What is an AI agent?
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An AI agent doesn't just answer questions. It can receive information, query systems, use tools and take actions according to your company's rules. Unlike a chatbot, it understands context, accesses real data and can execute tasks within a defined scope.
How is it different from a chatbot?
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A chatbot answers from a script or knowledge base, without querying systems or executing actions. An agent understands context, queries data and systems, uses tools and executes actions within defined rules. We also don't sell a generic chatbot platform: we design custom agents for each business.
What kind of AI agents does Solvo build?
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We build support and sales agents, internal agents to query business data, voice agents, data and business query agents, operational agents, and agents connected to ERP and business systems. Customer support is an important case, but not the only one.
Can it connect to our ERP or CRM?
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Yes. We design agents to connect with ERP, CRM, databases, spreadsheets and internal tools so they can query up-to-date information, record data and trigger actions within your operation, always within a defined scope.
Can it use WhatsApp?
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Yes. We develop WhatsApp agents for support or sales: they guide conversations, filter and route, follow business rules and record information or trigger actions based on what happens. We also build voice agents for incoming or outgoing calls.
Can it execute actions?
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Yes, within a defined scope. The agent can trigger tasks, validations, handoffs or records in your systems, always with permissions, rules and traceability. Sensitive actions are configured to ask for confirmation or hand off to a person.
How do you control what it can do?
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Everything involving internal data, ERP, CRM or business queries is designed with permissions, roles, defined scope and traceability. The agent only works on the information and actions agreed with the company, and keeps a record of what it queries or executes.
When does a person step in?
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A well-designed agent has clear limits: it acts alone only within the agreed scope and hands off to a person when the query is sensitive, complex or needs confirmation. Human oversight and handoff rules are defined with your team.
When should I use an agent vs. an automation?
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An automation makes sense when the path is defined: the steps are always the same. An agent makes sense when you need to interpret context or decide between options. They're often combined: deterministic parts automated and variable parts handled by the agent.
How do I choose an AI agent provider?
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Evaluate whether it understands your real process, integrates with your systems (CRM, ERP, databases), defines limits and human oversight, respects permissions and traceability, and tests with real scenarios before going live. A good provider also honestly explains what the agent can and can't do.
Do you have a process where a person receives information, queries systems and then decides or executes actions?
Tell us how it works today and let's evaluate whether an agent makes sense for your operation.
Want to evaluate your case?
Request a free initial assessment and we'll get back to you to understand where to start.