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In2AI: Tu consultora en Inteligencia Artificial

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Your Artificial Intelligence Partner

We create a real digital transformation on our clients’ business through artificial intelligence and disruptive technologies. That is what we do, that is, Intelligent Transformation.

We accompany you in the process of evolution, transformation, reinvention or creation of your business to maximize your competitive value. Aligning who you are with what you should be, building a future to believe in and develop the strategic AI products helping you address the most challenging tomorrow in history.

Our Expertise

Experts creating new products through Artificial Intelligence improving your digital transformation.


Data Driven

How do we do it?

Data-driven organizations are committed to gathering data concerning all facets of the business. By enabling employees, at every level, to use the right data at the right time, data can foster conclusive decision-making and becomes part of the companies’ competitive advantage.

Who should engage this transformation?

t is an advantage that brings ‘opportunities’ to data collected, therefore become a more effective agent in the market. Any company, regardless of size, is an advantage that contributes intelligence to decisions to be more effective in the market.

It is about technology, but it is not only that

Technology is not enough to be the best, it is necessary to invest in a global strategy: “the Data” in the center, the only certain thing to take decisions. Our proposal: to become a “Data Driven Company”.

RPA / IPA: Robotics & Intelligence Process Automation

RPA /IPA a Must have for every company

Robotics Process Automation or its evolution Intelligence Process Automation, It is the main demand of companies to simplify and solve the problems that legacies cause on their way to desired digital transformation. It is the most interesting current application of AI obtaining a fast ROI.

In essence, IPA “takes the robot out of the human.” At its core, IPA is an emerging set of new technologies that combines fundamental process redesign with robotic process automation and machine learning. IPA mimics activities carried out by humans and, over time, learns to do them even better.

How do we do it?

Our own technology developed in: Python and Tensorflow mixed by other technologies: Scraping, Human interaction simulation, Machine Learning, BPM, Document Management, API REST Gateways, Chatbots (Rasa, Dialog Flow), NLP, Legacy Integrations, NoSql data repositories, Single Sign-On addons. Market Tools: UI-VISION, UI-Path, Automation Anywhere, TagUI, Camunda BPM.

RPA / IPA Business Applications

  1. RRHH (recruiting, Employee portal, payroll, Calendar, vacations …),
  2. Sales (CRM integrations – legacy Systems – Operations),
  3. Contact-Center (call quality analysis),
  4. Industry (reporting, incidents, preventive systems)…

Machine Learning

Where do we apply ML?

Machine learning works wonderfully in situations where there is a lot of ground truth data, but very little obvious correlation of the elements that produce a ground truth. Use machine learning for the following situations:

  • You cannot code the rules: Many human tasks (such as recognizing whether an email is spam or not spam) cannot be adequately solved using a simple (deterministic), rule-based solution. A large number of factors could influence the answer. When rules depend on too many factors and many of these rules overlap or need to be tuned very finely, it soon becomes difficult for a human to accurately code the rules. You can use ML to effectively solve this problem.
  • You cannot scale: You might be able to manually recognize a few hundred emails and decide whether they are spam or not. However, this task becomes tedious for millions of emails. ML solutions are effective at handling large-scale problems.

How do we do?

  1. Build the Team (AI Squad)
  2. Frame the problem
  3. Get the data: Research
  4. Explore the data, Data Aggregation / Mining / Scraping
  5. Prepare the data: Data Preparation / Preprocessing / Augmentation
  6. Model the data: Training
  7. Fine-tune the models: Parameter tuning and Inference. Evaluation
  8. Present the solution
  9. Launch the ML system: Model Deployment.

What do we do?

Assessment non-payment risk, automatic document classification, Customer Segmentation, preventive mainteinance, Churn Rate, Prediction of employee exit … The applications are endless.

Chatbots, Bots & NLP

What do we do?

We humanize the way that systems interact with people. We help users to connect and receive information, or carry out transactions, in a simple way without the need of complex interfaces, through a system that emulates a person in an intelligent and precise way.

How do we do?

We are experts on Natural Language Processing. We develop Text to Speech, Speech to text solutions. We are experts on RASA framework although we can create any chatbot with other technologies such as DialogFlow, Watson, Flowxo… We develop the interfaces to interact with users such as social networks, mobile apps, even on digital signage.

Applications / Use Cases

Sales: Commercial solution in social networks.
Support: Troubleshooting solutions , information inquiries.
HR: Virtual recruiter on Linkedin, Facebook, web and other networks.
Communication: Social Listening + reaction to reputational crisis.
Others: advisor to specialized topics.

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