Enterprise Intelligence Platform

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  Workflow with Cognitive Models

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  Form creator for simple BPM

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Inspiration

Every industries and enterprise have different silos of data and different platforms which makes the time taken to stream data for predictive analytics and collaboration very slow which leads to operational and productivity loss.We were inspired by this problem to bridge the gap between different silos and intelligence.

In order to overcome the operational and productivity loss, our centralized platform comes into play where you can witness the power of conversational and cognitive intelligence collaborated with automation and analytics to automate tasks and improve productivity in industries

What it does

Proper collaboration is necessary for a good company to obtain a higher level of productivity, but collaboration must not be limited to humans, Collaboration must happen between people, devices, applications, machines, and data, which is not happening now. This is where our platform comes into play, It is an A.I powered intelligent enterprise platform which offers conversational and cognitive intelligence; Estreetz can collaborate not only with humans but with all machines, applications, people and data in the company.It provides integrated dashboards, automation workflow, and collaboration tools. With the AEI platform you can improve the productivity of the organization with low cost in the low time. AEI platform features include Drag and Drop workflow automation, Dynamic dashboards, and inbuilt collaboration tools.

Accomplishments IM proud of:

                               We used the prototype of this product to pitch in a real use case. Our product was selected as a top 3 solutions of an MNC Industrial challenge.

Challenges I ran into

                    We struggled with the dynamic integration of Microsoft API with different data and the re-usability of machine learning code multiple times for multiple users. As of now, we need to set up some APIs for some use cases which require some customization. But, In the future, we try to solve this.

We didn't use much cognitive API in the core system. But, we want to enable cognitive intelligence in the platform using Microsoft Cognitive API which the user needs to configure. It eliminates the need to design separate UI, process data and triggers. Thus they can easily adopt Microsoft products into their system.

What's next for AEI platform

                 We are looking forward to collaborating with Industries in order to improve productivity by minimizing human efforts between handling data and operations using the no-code platform and cognitive intelligence.

How I built it

         The application was built using React.js, Mysql, Mongo Db, and  Azure cognitive intelligence API. Also, We use MQTT to stream live data from machines and python -Flask backend.

What I learned

                        We learned about the credibility of Microsoft Enterprise Products in industries.

Also, how IT technologies can make a positive impact in improving industrial, individual and enterprise productivity.We learned the difficulty of people in integrating AI, ML, DL products into their system. Thus we came up with this idea of connecting all resources with ai.

Built With

• python
• react