YOUR COMPANY NEEDS AN AI INTEGRATOR
The integration of AI with your business starts here. Discover how to do it without losing control.
WHERE DO I START: A GUIDE TO INTEGRATING AI
Integrating AI into your business doesn't have to be complicated. Here are 8 key tips to successfully take the first steps:
Identify your most costly pain point
Before thinking about technology, identify the process that consumes the most time, money, or resources. AI should solve real problems, not create new ones.
Start small, think big
Don't try to transform your entire company at once. Start with a pilot in a specific area, measure results, and scale what works.
Audit your data (but don't obsess)
You need data to train AI, but you don't need perfect data. Start with what you have and improve along the way.
Define clear metrics from day one
How will you measure success? Define concrete KPIs: time savings, cost reduction, sales increase. What isn't measured can't be improved.
Involve your team from the start
Resistance to change is the biggest obstacle. Train your team, listen to their concerns, and turn them into allies, not resistors.
Don't reinvent the wheel
For 80% of cases, proven solutions already exist. Use pre-trained tools and platforms like NAiOS instead of developing from scratch.
Calculate ROI before investing
Before committing to a solution, do the math. Compare the current cost of the problem with the cost of the AI solution. The ROI should be clear.
Plan for security and compliance from the start
GDPR, data protection, role-based access... These are not problems for later. Integrate them from the design phase or you'll have to redo everything later.
Compatible Technologies and Systems
NAiOS integrates natively with the leading platforms in the market. Whether you use Azure, AWS, Salesforce, SAP, or any other system, our flexible architecture allows for secure and efficient connections.
Cloud Providers
CRM Systems
ERP Systems
Business Intelligence
Productivity Tools
Databases
APIs and Protocols
ROADMAP: YOUR ROADMAP TO AI
Integrating AI is not a one-time event, it's an evolutionary process. Here is your roadmap:
CONNECT YOUR DATA
The first step is to connect your information sources: internal documentation, ERP, CRM, BI... AI needs context to be useful. Without integrated data, you only have a generic chatbot.
DEPLOY CUSTOM AGENTS AND GPTs
With your data integrated, create specialized assistants for each area: sales, support, operations, finance. These agents work with your company's specific knowledge.
AUTOMATE KEY PROCESSES
Connect your agents with your systems to automate complete workflows: from lead generation to invoicing, including support and document management.
EVOLVE AND SCALE
With the core functioning, expand to new departments, add advanced use cases (prediction, optimization), and consolidate AI as the engine of your business.
INTEGRATION STORIES: REAL CASES
APD
“With NAiOS we have built a platform for shared and updated knowledge, which helps us design our meetings and direct commercial action. Now we integrate in one place the most relevant sources of information (internal/external). And we open access to that knowledge to all teams so they can work with it on a daily basis and extract the information they need when they need it.”
Juan Duce
Director of Marketing & Digital Strategy
Integraciones:
LegalTech SaaS
“Our team reviews critical clauses with a legal assistant and citations to internal documents. We went from weeks to hours without losing control.”
Legal Director
Legal Director
Integraciones:
InduLogix
Pilot“We connected ERP with predictive maintenance and an operations co-pilot. Response time decreased and we better prioritized orders.”
COO
COO
Integraciones:
CampusNova
In production“We activated an agent for admissions and a content engine. Better tracking and personalized messages without expanding the team.”
Admissions Manager
Admissions Manager
Integraciones:
HOW NOT TO FALL BEHIND IN THE AI ERA
AI is advancing quickly. Here are 5 strategies to ensure your company doesn't fall behind:
Adopt a continuous learning mindset
AI is not a project with an end date. It is a process of continuous improvement. Spend time each month exploring new tools, use cases, and best practices.
Watch your competition (and other industries)
What is your competition doing with AI? And companies from other sectors facing similar challenges? Innovation often comes from applying proven solutions in different contexts.
Invest in training, not just technology
Tools are constantly changing, but fundamental skills (critical thinking, prompt engineering, data analysis) are enduring. Train your team in these core competencies.
Create a culture of experimentation
Allocate time and budget for your team to experiment with AI without fear of failure. The best insights often come from internal experiments, not from external consultants.
Measure, measure, measure (and adjust)
Have updated dashboards for usage, costs, ROI, and satisfaction. AI that is not measured and adjusted regularly loses effectiveness quickly. Review your metrics at least monthly.