05 / ARTIFICIAL INTELLIGENCE

Artificial Intelligence integrated into the business.

Not just a model answering prompts.

We design and engineer AI systems connected to operations — able to understand context, access data, use tools, execute processes and produce traceable outcomes.

From generative AI to autonomous agents, we turn language models into systems that work inside the company.

01 / CONTEXT

Intelligence starts with the operation.

Before selecting models, frameworks or architectures, we learn how the company actually works. We map data, people, systems, rules, decisions and processes to identify where AI can create measurable operational impact.

From that context, we design AI solutions integrated with the business infrastructure and objectives.

What we analyze

  • 01Operational processes and flows
  • 02Data and knowledge sources
  • 03Existing systems and APIs
  • 04Business rules and decisions
  • 05Manual and repetitive tasks
  • 06Human intervention points
  • 07Security and governance

02 / ORCHESTRATION

Input → Model → Agent → Tool → Action.

An isolated language model answers. A well-engineered AI system understands context, retrieves information, selects tools, executes actions and records what happened.

We connect models, agents, APIs, databases, enterprise systems and people within controlled flows.

ININPUT
  1. 01Input
  2. 02Model
  3. 03AgentDECIDES + COORDINATES
  4. 04Tool
  5. 05Action
OUTOUTCOME

OPERATING ARCHITECTURE

  • L01Context and memory
  • L02Models and LLMs
  • L03AI agents
  • L04Tool use
  • L05APIs and integrations
  • L06Human approval
  • L07Evaluation
  • L08Observability
  • L09Traceability

The goal is not to add AI to software. It is to create an intelligent layer that can participate in the operation.

03 / AI AGENTS

Agents that understand, decide and execute.

We build agents that operate complete processes or precise stages of an operation. They interpret information, query systems, use tools, decide within defined rules and request human approval when needed.

Agents for

  • 01Customer support
  • 02Sales prospecting
  • 03Lead qualification
  • 04Internal operations
  • 05Document analysis
  • 06Research and intelligence
  • 07Finance
  • 08Customer Success
  • 09Content
  • 10Back office
  • 11Data processing

An agent does not need to replace a person. It can take on repetitive work so people can focus on decisions that require human judgment.

04 / GENERATIVE AI & LLM

Models connected to company knowledge.

We turn language models into systems that work with each organization’s information, rules and data. We design applications with LLMs, RAG, memory, semantic search, function calling and multi-agent architectures.

Capabilities

  • 01LLM integration
  • 02RAG and knowledge bases
  • 03Semantic search
  • 04Function calling
  • 05Structured outputs
  • 06Contextual memory
  • 07Document processing
  • 08Data classification and extraction
  • 09Enterprise assistants
  • 10Multi-agent systems

Technology is selected around the problem — never the other way around.

05 / INTELLIGENT AUTOMATION

From decision to execution.

Traditional automation follows rules. AI can also work with context, language, documents and situations that do not fit deterministic flows.

We combine AI, agents, integrations and automation to execute work end to end.

  1. 01Lead received
  2. 02AI reads the context
  3. 03Queries the CRM
  4. 04Qualifies the opportunity
  5. 05Researches information
  6. 06Prepares the approach
  7. 07Records activity
  8. 08Requests approval
  9. 09Executes the next action

One process. Different systems. One intelligent layer coordinating everything.

06 / INTEGRATIONS

AI connected to what your company already uses.

AI becomes more powerful when it can access and operate the systems already inside the company. We connect agents and AI applications to APIs, databases, CRMs, ERPs, service platforms, internal systems and external services.

SOURCES & CHANNELS

  • IN/01CRM
  • IN/02ERP
  • IN/03WhatsApp
  • IN/04Email
  • IN/05Databases

SYSTEMS & TOOLS

  • APIsOUT/01
  • DocumentsOUT/02
  • Internal systemsOUT/03
  • SaaS platformsOUT/04
  • Enterprise toolsOUT/05
INPUTCONTEXTREASONACTTRACE

AI stops being an isolated interface and becomes part of the organization’s digital infrastructure.

07 / GOVERNANCE

Autonomy with clear boundaries.

The greater an AI system’s ability to act, the stronger the control over its decisions must be. We design governance into the architecture.

  1. 01OBJECTIVE
  2. 02DECISION
  3. 03TOOL
  4. 04ACTION
  5. 05RECORD

Operational control

  • 01Per-agent permissions
  • 02Execution limits
  • 03Human in the loop
  • 04Human approvals
  • 05Action logs
  • 06Decision history
  • 07Tool control
  • 08Response evaluation
  • 09Monitoring
  • 10Traceability

Autonomy does not mean absence of control. It means allowing systems to execute within explicitly defined boundaries.

08 / OUTCOME

AI that takes on real work.

Automation and agents are measured by their ability to improve flow, decisions and outcomes — not by a demo effect. Our AI projects start with the operational problem and end in execution.

What we aim to create

  1. 01Fewer repetitive tasks.
  2. 02Lower operational time.
  3. 03More capacity per person.
  4. 04Faster decisions.
  5. 05More consistent processes.
  6. 06Information available at the right moment.
  7. 07Operations able to scale.

09 / AI ENGINEERING

From proof of concept to production.

Building an AI demo is relatively simple. Building a dependable system that operates every day is an engineering problem. Caristeo combines software, architecture, product and AI from discovery through deployment, observability and continuous evolution.

  1. 01Discovery
  2. 02Architecture
  3. 03Prototype
  4. 04Integration
  5. 05Production
  6. 06Evaluation
  7. 07Evolution

10 / SOLUTIONS

What we can build with Artificial Intelligence.

  1. 01

    AI agents

    Agents that understand context, use tools and execute processes within defined rules.

  2. 02

    Enterprise assistants

    Intelligent interfaces connected to organizational documents, data and knowledge.

  3. 03

    AI automation

    Processes combining rules with AI-based interpretation, decision and execution.

  4. 04

    Generative AI systems

    Products built on LLMs, RAG, multimodal models and generative AI.

  5. 05

    Document intelligence

    Automated extraction, classification, interpretation, comparison and processing.

  6. 06

    AI integration

    Models and agents connected to existing systems, APIs, databases and tools.

  7. 07

    Multi-agent systems

    Specialized agents collaborating to execute more complex processes.

  8. 08

    AI digital products

    Applications where AI is part of the experience and value proposition.

11 / TECHNOLOGY

Model-agnostic by design.

We do not build solutions dependent on a single model. Models, infrastructure and architecture are selected around quality, latency, privacy, cost and complexity.

Our engineering can work with commercial and open-source models across different AI infrastructures, keeping the business layer decoupled whenever the architecture allows.

The solution can evolve as models and technologies advance.

12 / FAQ

Artificial Intelligence for business.

01What is an enterprise AI solution?

A system that uses AI to interpret information, support decisions, automate processes or execute tasks within an operation. It may involve LLMs, agents, RAG, specialized models, automation and integrations.

02Does Caristeo build AI agents?

Yes. We build custom agents for different business processes, connecting language models to data, APIs, tools and enterprise systems.

03Can AI integrate with the systems my company already uses?

Yes. We integrate AI with CRMs, ERPs, APIs, databases, support platforms, documents, internal systems and other tools.

04What is an AI agent?

A system that receives an objective, understands context, uses tools and executes actions within defined rules and permissions.

05Do you build solutions using LLMs and generative AI?

Yes. We build applications with language models, RAG, function calling, structured outputs, memory, document processing, semantic search and agent architectures.

06Can we create AI trained on company data?

Training a new model is not always necessary. We can connect existing models to private organizational knowledge with RAG, semantic search, vector databases and internal data integrations.

07How does an AI project begin?

We start by understanding the process, available data, systems involved and expected outcome. Then we define the architecture and identify where AI, automation and agents create real value.

13 / START

Is there work in your operation that AI could take on?

Let’s find where Artificial Intelligence can create real impact in your business.

Start a project