Case Studies implemented using Trillo Workbench

Enterprise data resides in multiple systems. Trillo Workbench can ingest data from these systems into BigQuery, Cloud SQL, Cloud Storage Bucket, and Snowflake. A complete enterprise modernization entails the following functions.

1. Use third-party services, such as Fivetran, Stitch Data, etc., to pull data from the source system into BigQuery or Cloud SQL.
2. Write custom connectors as Trillo Workbench workflows when the data ingestion requires complex processing, such as transforming data before loading, event-driven decisions, etc.
3. Transform data once data is available in the BigQuery tables or Cloud Storage Bucket.
4. Provide master data ingestion UI from Excel/CSV/JSON/XML files or manually.
5. Role Based Access Control (RBAC) rules for governance and compliance.
6. Data catalogs using Trillo Workbench and Google Dataplex.
7. Data security measures such as column encryption and redaction.

Trillo helped several Google customers modernize their on-premise applications and migrate to the cloud. The applications covered under this use case had the following characteristics. This is an ongoing use case we still fulfill for new customers.

1. They were legacy applications running on-premise or colo centers servers.
2. The applications used old Microsoft technologies or a very old Lamp stack.
3. The customer managed the data server (backup, restore).
4. These applications were at the end of life and performing poorly. A few customers reported one failure per month.

Trillo modernized these applications using Trillo Workbench in a few months and at a low cost. Anything else would have cost the customers a year or more work. It involved the following steps.

1. Understand existing applications and propose new designs through a reusable POC (using Trillo Workbench as the server).
2. Design a data model using Trillo Workbench UI.
3. Write application logic as serverless functions.
4. Replaces existing databases with the managed Cloud SQL instances. Write a workflow for data migration.

This use case is a part of the solution Trillo built for a brokerage firm. The brokerage firm sells products from manufacturers to grocery shops. Each manufacturer allocates a certain quota of products to it. Its sales team sells them by phone, email, or in person. During the interaction with a customer, a salesperson needs to answer certain questions, such as,

1. How many boxes of "diet coke" are in stock?
2. What is the price of a box of "diet coke"?
3. Is there a promotion available on "Florida orange juice"?

The above use case is served by an application providing a conversational interface on mobile devices and computers. The application flow at a high level is as follows:

1. Using a web or mobile application, a user asks a question.
2. The question is converted to text using Google Cloud's speech-to-text service.
3. The text is passed to an AI service to detect intent and entities within questions such as "product = diet coke", "query = stock", etc.
4. The returned result of intent is processed by application logic which substitutes template values in the answer with actual values queried from the database.
5. The final text of the answer is converted to an audio file using Google Cloud's text-to-speech service.