Applied AI for Business in Colombia and Latin America

Replaces: Someone on the team opens each email or ticket, figures out what it is about, and forwards it before real handling can start.

The AI: Classifies the message by topic and urgency, extracts the key data (customer, product, reason), and routes it to the right team or queue.

Human control: The receiving team confirms the classification and can reassign in one click; ambiguous cases go to a manual review queue.

Data needed: A history of already-classified tickets or emails and the current category/team taxonomy.

Integrates with: Email inbox, help desk, and CRM.

Related terms: LLM

Replaces: An agent manually answers the same frequently asked questions over WhatsApp, searching for the information across several internal documents.

The AI: Answers using RAG over an approved knowledge base (FAQs, policies, catalog) and drafts the reply citing the internal source used.

Human control: If the question falls outside the approved scope or the customer asks for it, it escalates to a human agent; off-script replies are never sent on their own.

Data needed: Approved documents to answer from (FAQs, policies, catalog) and clear rules for when to escalate.

Integrates with: WhatsApp Business API, knowledge base/documents, and CRM.

Related terms: RAGPrompt Injection

Replaces: A salesperson or coordinator reviews every incoming form or message to decide whether it is a real opportunity and who should own it.

The AI: Classifies the inquiry by type of interest, estimated size, and urgency, and routes it to the right salesperson or channel.

Human control: The assigned salesperson reviews and confirms before reaching out; the sales team can adjust the routing rules.

Data needed: A history of already-qualified inquiries and the current assignment rules by territory or product.

Integrates with: CRM, website forms, and email.

Replaces: After a visit or call, someone transcribes loose notes and loads them into the CRM by hand, often with delay.

The AI: Summarizes the conversation or field note into a standard format (need, next steps, follow-up date) and pre-fills the CRM record.

Human control: The salesperson reviews and edits the summary before saving it; nothing is recorded without their confirmation.

Data needed: Field notes, transcripts, or emails from the interaction, and the record format the sales team uses.

Integrates with: CRM, email, and, where applicable, call recording or transcription.

Replaces: An analyst opens each claim or request, reads the attached document, and manually decides the case type and which queue it belongs to.

The AI: Classifies the document by claim or request type and extracts the relevant data to pre-fill the case file.

Human control: The assigned analyst confirms the classification and makes the final decision on the case; the model never approves or rejects a claim.

Data needed: Already-classified claims or requests as examples and the process’s current categories.

Integrates with: Case or policy management system, email, and document repository.

Related terms: SLM

Replaces: The team periodically checks reports or dashboards to notice if something went out of range (temperature, stock, consumption), sometimes too late.

The AI: Monitors inventory or sensor readings and generates an alert when a value falls outside the expected range, with the relevant context.

Human control: The alert reaches a responsible person who decides the action; the system does not intervene physically or close the case on its own.

Data needed: Historical series of the relevant readings and the process’s normal ranges or thresholds.

Integrates with: IoT sensors or a monitoring system, inventory/ERP, and an alert channel (email, WhatsApp, Slack).

Replaces: Drafting every response to a customer or third party (status update, request, collections communication) takes time even though the content is similar each time.

The AI: Drafts a reply based on the case and the current template, using the data from the corresponding file.

Human control: No response goes out without a person reviewing it, editing it if needed, and approving it.

Data needed: Current response templates and the case or file data.

Integrates with: Case management system, email, and CRM.

Replaces: A new employee or someone from another area asks over internal chat or email where a policy lives or how a procedure works, and someone has to look it up.

The AI: Answers the team’s questions using RAG over current internal manuals, policies, and procedures, citing the source document.

Human control: When the documentation does not have a clear answer, the assistant says so instead of making one up; the area that owns the document validates the source content.

Data needed: Current internal manuals, policies, and procedures, and someone responsible for keeping them up to date.

Integrates with: Internal document repository (wiki, Drive, SharePoint) and the internal chat channel.

Related terms: RAGMCP

Replaces: Field visit reports arrive in different formats (notes, photos, forms) and someone in the office has to read through all of them to know what happened.

The AI: Summarizes each report into a standard format (finding, action taken, pending item) and leaves it ready for review or follow-up.

Human control: The supervisor reviews the summary and decides the next step; the summary does not close or assign work on its own.

Data needed: Historical field reports and the summary format the operations team uses.

Integrates with: Field app or form, email, and work order system.

Replaces: Checking that a contract or document covers the usual points (clauses, terms, conditions) is manual and depends on the reviewer not missing anything.

The AI: Compares the document against a checklist of points to verify and flags which clauses or sections need the reviewer’s attention.

Human control: The person responsible for legal or compliance does the final review; the checklist is a reading aid, not an approval.

Data needed: The current checklist or control points and examples of already-reviewed contracts.

Integrates with: Document/contract repository and email.

Related terms: RAG

Replaces: Loading each product into the catalog (description, attributes, category) from the manufacturer’s data sheet takes manual time for every single item.

The AI: Extracts the relevant attributes from the technical sheet or vendor document and builds a draft product listing for the catalog.

Human control: The catalog team reviews and publishes the listing; nothing goes live automatically without that review.

Data needed: Technical sheets or vendor documents and the catalog’s field structure.

Integrates with: Catalog/eCommerce platform, ERP, and vendor document repository.