Inteligencia artificial
We solve business needs and capture business opportunities which can be approached by AI, resulting into positive impact on business.
Thanks to a multidisciplinary and collaborative team, we build INTEGRAL solutions, iterating the process data, model and automation, answering/meeting all business requirements and taking advantage of every available IT capacity.
Through our multiple technology practices, we implement an end-to-end comprehensive solution that includes the Artificial Intelligence component best suited for the project:
01.
Analytics, Predictive & Prescriptive Models
02.
Computer
Vision
03.
Natural Language Understanding & Generation (NLU/NLG)
Inspiring Cases
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OPTIMIZE PROCESSES
Are you seeking to automate document analysis to shorten processing time and reduce tendency to make mistakes? Do you need to streamline your processes so that your company may keep competitiveness around the clock?
By means of Natural Language Understanding we process multiple communication channels with customers, claims, policies, contracts, subscriptions and other documents, thanks to the short time needed for the analysis of huge volume of data.
By means of Computer Vision we can automate the supervision of industrial processes while surveiling the use of security elements, controlling the quality of processes and autonomously
detecting failures/bugs in products, among other actions.
By means of Predictive and Prescriptive Models, we streamline productivity as from the preventive maintenance of equipment up to the clearest follow-up of the requirement lists throughout the entire supply chain. Besides, with Reinforcement Learning we optimize the transportation handling queue rank/score as per type of goods carried.
MANAGE RISKS
Do you need a real-time exact system to rapidly detect failures in your operations to protect the company from losses? Do you have to manage risks in order to make decisions which minimize cost and maximize benefits/profits?
Traditional systems for the rapid detection of failures/exceptions base on rules and are not sufficient, they frequently cause false positive high rates which should be later eliminated manually.
AI-based systems are proactive and can improve the analysts work flow since they reduce noises without descarding alerts/warnings. They can effectively enhance follow-up and identification of fraud by cross referencing data - whether human or non-human – from different data bases (Fraud Detection).
AI also provides a more granular and individualized approach to implement risk analysis. This is the case of credit scoring where greater precision is achieved, based upon grounds/factors larger than the traditional ones (Risk Scoring).
AI allows us to evaluate, identify, monitor and mitigate risks while augmenting robustness and resilience and reducing vulnerability, securing supply chain continuity and profitability (Risk Assessment).
ATTRACT AND RETAIN CUSTOMERS
Is your aim to increase sales efficiency and effectiveness at the same time you cut cost? Are you concerned about the growth of your business and finding the proper customers? Do you want to retain them and enhance the management of their value?
Tradition rules that calculations supporting growth-oriented decisions have been made with simple formulas. These basic models not only render unreliable predictions but also incomplete aspects.
Nowadays AI segmentation is dynamic, descriptive, actionable, real-time, granular, anticipative and supplementary (AI-driven Customer Segmentation) for:
- Forecasting the customer behaviour, since they are presented with information on products or services adapted to their interests, preferences or behavioural history (Product Recommendation).
- Offering the best price at any time by means of AI-based price determination algorithms which analyse a huge amount of internal and external factors (Price Optimization).
- Reacting based upon the amount of money received from customer throughout its history/permanence/stay (AI-driven CLV).
- Preventing customer dropout through retention-oriented actions (Churn Prevention).
- Focusing marketing campaigns on products which customer buys and which subsequently shoot future purchase of other related products (Influencer Discovery).
Identifying the best trial-sold product of the catalogue starting as from a certain reference product for decision-making (Product Matching).
IMPROVE THE EXPERIENCE OF CUSTOMERS AND CO-WORKERS AS WELL
Are you seeking for the automatic reply for daily applications and repetitive activities in order to focus on greater value interactions with customers? Are you concerned about the perfect balance between virtuality and human interaction to generate more efficient processes with same level of approachability?
Well-designed chatbots may be beneficial if they give valuable time in return to the Company as well to the customers. If customers do not get the answer they were looking for or it takes too long, their experience will be negative. It turns that their “customer centricity” level is finally supported by its development and technological sophistication.
In Baufest we have developed AI-Enabled Chatbots and Assistants which implement Natural Processing Language (NPL) processing techniques to understand the context of the conversation and decode the intention, organizing it into categories which allow for the selection of the proper answer or action, resulting thus into a “human-like” conversation.
The use of machine learning enables the recall of the data the user has been looking for, their past queries and according to these, personalized solutions are delivered. When combining this process with the analysis of feeling, customer satisfaction may be definitely enhanced.
OPERATION OF AI PLATFORMS
Would you like to accelerate and automate the deployment of your Machine Learning applications to go hand-in-hand with needs and time your business need? Would you like to have the continuous monitoring of the performance of your Machine Learning solutions? Do you want to incorporate the best practices to synchronize the Development areas of Advanced Analytics and Operations so that they may jointly work in collaboration and with a common purpose: the continuous value delivery?
We have implemented Model Operations in the processes of our customers and have been working on lead IT platforms and we succeeded in:
- Reducing time-to-market because we progressively release early versions of the model and reuse already-built pipelines.
- Augmenting the team productivity and increasing speed in launching new functionalities.
- Early detecting adjustments by means of continuous and automated monitoring.
Obtaining safer and more stable operations and quicker changes thanks to automation.