VectorShift Platform Overview

An overview of the VectorShift Platform

VectorShift's platform allows you to design, prototype, build, deploy, and manage generative AI workflows and automations across two interfaces: no-code and code SDK. Example use cases:

  • Chatbots: Build a fully functional AI chatbot and embed it into your website. AI chatbots are able to respond to user queries and answer questions based on a knowledge base (e.g., product documentation, support articles, live-synced google drive).

  • Search: centralize and live-sync your data across your applications (e.g., Google Drive, Slack, One Drive, etc.) in one knowledge base and perform search queries over all your data.

  • Automations: automate workflows end to end: schedule workflows to run at certain time intervals or allow certain triggers (e.g., email, slack message) to trigger the running of a workflow; have the VectorShift platform automatically perform actions (e.g., send an email, create a notion document, add data to an Airtable database).

  • Content Creation: Create marketing copy, personalized outbound emails, call summaries, proposals, and graphics at scale and in a predetermined format and style.

  • Workflow Automation: Replicate the logical thinking of a process by breaking down a task into sub-tasks and having different LLMs perform them.

VectorShift Pipeline Dashboard

At the core of the VectorShift platform is a pipeline. Pipelines are AI workflows. On the "Pipelines page", click "New" on the top left to create a new pipeline.


This will bring up a modal that either allows you to "Create Pipeline from Scratch" or to start from a template. You can filter on the different templates categories with the buttons on the left.

For example, you can choose the template called "Customer Support Chatbot template" to build a workflow that can automate customer support requests.

No-code builder

The no-code builder is comprised of three components:

  • Nodes: Nodes are found on the top bar and contain the tabs named "General", "LLMs", "Knowledge Base", etc. Nodes are components of AI workflows that perform various functions such as fetching data, performing actions, and leveraging LLMs.

  • Canvas: The canvas is where nodes can be connected to form a workflow.

  • Control bar: The control bar is on the top right. These allow you to "Deploy" a workflow to production, "Deploy as" your pipeline as a chatbot, automation, or search, "Run" the pipeline, or Name the workflow / share it with teammates (under "Details").

To operationalize this customer support chatbot pipeline, you can add relevant data to the "Knowledge Base Reader" node. This node allows you to centralize your data wherever it sits (e.g., files, Google Drive, Notion, etc.) to perform semantic search over it (e.g., to find the most relevant pieces based on a query). You can do this by either selecting an existing knowledge base through the drop down menu, or creating a new knowledge base by clicking "Create New Knowledge Base".

Knowledge Base

Within the "Storage" tab, you can create a "Knowledge Base" that centralizes and live-syncs to your data (e.g., Google Drive, OneDrive, Notion, Airtable). You can then use knowledge bases within pipelines to perform semantic search and return relevant information that LLMs can use.

Create a Knowledge Base by clicking on "New" within the "Storage" tab.

You can then "Add Documents" to the knowledge base including files, data from "Integrations" (e.g., live sync to data within Google Drive, Airtable, OneDrive), URLs, and more. Using the "Knowledge Base Reader" node within the no-code builder will return the most relevant pieces across the knowledge base.


Pipelines can be deployed as Chatbots, which can be done by clicking on "Deploy as" within the No-code Builder.

Once created, you can customize the functionality (e.g., suggested initial prompts, Welcome Message) and UI (e.g., color).

You can export the chatbot via URL (with a ChatGPT inspired interface), embed the chatbot directly into your website via an iFrame, as a WhatsApp / SMS bot, as an API endpoint, or as a Slack App bot.

Finally, you can also Manage the chatbot and 1) view conversations, 2) see Analytics (# of messages, AI cost, user feedback etc.), or 3) download collected data.


Pipelines can be deployed as Automations, which can be done by clicking on "Deploy" within the No-code Builder.

Automations allow you to run pipelines automatically. Here, you can schedule workflows to run at certain time intervals (Cron) or allow defined triggers (e.g., email, slack message, typeform message) to trigger the running of a workflow.

Pipelines can also be deployed as a Search, which can be done by clicking on "Deploy" within the No-code Builder.

Compare to chat, search has more of a focus in citations and has more of a traditional search engine interface.

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