Artificial intelligence applied to how your company runs
We take AI from pilot to daily operations: assistants that answer with your company's knowledge, agents that take action, and automations that free up hours of manual work.
In short
How does Julsmind implement AI in a company?
Julsmind SAS, a software company in Medellín, Colombia, implements AI applied to concrete business processes: assistants and chatbots grounded in the company's own data (RAG), AI agents that act inside existing systems, document and email automation, and predictive analytics. It works with models such as Claude, GPT, Gemini and DeepSeek, and always starts from a measurable use case before scaling. It is also the company behind Opttia, its multi-agent AI platform for supply chain intelligence.
AI with a business purpose
We start with the process that costs you the most time or money, not with the trendiest technology.
Assistants on your data
Chatbots that answer from your documents, catalog and policies — not generic information.
AI agents
Agents that read, create and update records in your ERP, CRM or email.
Document automation
Reading invoices, orders and forms to extract and load data without typing.
Predictive analytics
Models that anticipate demand, risk or customer behavior from your history.
Workflow automation
Processes that combine AI with rules and integrations (n8n, webhooks, APIs).
Privacy and control
Designed for data protection, access control and human review of sensitive decisions.
What an AI project includes
- Process assessment and highest-impact use cases
- Proof of concept with real data
- Choosing the right model (Claude, GPT, Gemini or others)
- Connection to your documents and systems (RAG and integrations)
- Interface: web chat, WhatsApp, internal panel or API
- Answer-quality evaluation and guardrails
- Production deployment with cost monitoring
- Team training and continuous improvement
From pilot to production
- 1
Assessment
We map repetitive tasks and decisions where AI adds real value.
- 2
Measurable use case
We pick one process and define how to measure savings or improvement.
- 3
Proof of concept
A working pilot with your data in a few weeks.
- 4
Integration
We connect the AI to your systems and service channels.
- 5
Production
Deployment with quality, security and cost-per-use monitoring.
- 6
Scale
With measured results, we extend the solution to more processes.
Models and tools
- Claude
- GPT
- Gemini
- DeepSeek
- RAG
- Vector databases
- Multi-agent systems
- n8n
- WhatsApp Business API
- Python
- Node.js
- Google Cloud
- AWS
Frequently asked questions
How much does implementing AI in a company cost?
It depends on scope, integrations and design depth. We work fixed-scope, with a monthly hour bank or as a dedicated team. After a first call we send a proposal with estimated scope, timeline and cost within 48 hours, with no commitment.
What is it like to work with a nearshore team in Colombia?
Medellín is in Colombia's time zone (UTC-5, no daylight saving), so our working day overlaps with US business hours. You get real-time calls, sprint demos and a shared backlog, with an English-speaking point of contact.
What is an AI agent?
A system that, beyond chatting, can take actions — query a database, create an order, update a CRM or send an email — following defined rules and permissions. In multi-agent systems, several specialized agents collaborate on a task.
Do you build your own AI products?
Yes. We build Opttia, a multi-agent AI platform for supply chain intelligence, and KAI, the AI assistant built into Katuq.
Let's find your first AI use case
In a 30-minute call we identify where AI can save your team time and how to test it with low risk.
Get a quote