Inspiration
Our company, Scratchpad, empowers our users to update their sales pipelines, forecast and inspect their deals, and adhere to sales processes. We heavily integrate with Salesforce in order to provide all of these values. We've seen a lot of the pain that goes into configuring and entering data into a CRM like SalesForce. Why not offload that pain to AI?
What it does
It is a simple CRM that allows that lets you browse sales opportunities. The opportunities are created by connecting different data sources (for this prototype we are processing a list of Chorus call recordings). You can see a grouping of opportunities by selecting or creating a view. You create and modify views using text input prompts.
How we built it
BE is powered by Python using the Flask framework. We are using a local Postgres DB to store opportunities, views, and notifications. We have a python script that fetches sample call recordings from Chorus. Then prompts are generated through OpenAI's api using a combination of the opportunity table schema, and call recording to extract column values. We again use OpenAi to generate a SQL query to upsert the opportunity and insert a notification of the updates made to that opportunity. We also have a set of apis for views. The view's fetch opportunities by executing a query associated with that view. This query is again generated through OpenAI using prompts generated by user text input and the opportunity table schema. The FE is a Vue app that allows the user to create, switch between, and modify views. The user also can view notifications of all updates that occurred due to ingested call recordings.
What's next for CRM.AI
The main reason we used OpenAI to generate SQL statements is that we plan to let OpenAI define the schema of opportunities or any other tables that provide insight into a sales pipeline. We also want to allow text input to batch update records, not just affect views.
Built With
- chorus
- flask
- openai
- pinia
- postgresql
- python
- vue3
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