VectorShift Product Update (Mar 5, 2024)

VectorShift Product Update (Mar 5, 2024)

By Albert Mao

Mar 5, 2024

March 5 - VectorShift Update

With VectorShift, you can place triggers across your applications (e.g., new typeform message, new slack message, new email), create AI workflows with our no-code builder, and perform actions (e.g., send a slack message, send an email, update a lead in CRM).For example, we have seen many users use their customer support / lead collection Typeform as a trigger for sending a slack message (to help coordinate who to take action) or to send a personalized email to the user (e.g., to schedule a demo).

Product Updates

In the two weeks, we shipped:

  • Start from template form: clicking “new” on the pipeline page will bring up a page where you can either start from a blank canvas or from a no-code template. Hopefully this will make it easier to get started building!

  • New Data Sources / Integrations: Github (new commit trigger, new PR trigger, new issue trigger, search files, read files, create a PR, update PR), Notion (create a new page), Hubspot (new contact trigger, new company trigger, new deal trigger, new ticket trigger, new engagement - notes trigger, new engagement - tasks trigger, new engagement - calls trigger, search items, fetch contacts, fetch companies, fetch deals, fetch notes, fetch calls)

  • Deploy as Slack: deploy a chatbot directly as a slack app. Can be found in the “Export” tab under chatbots.

  • Cron Job: schedule your workflows to deploy at predetermined time intervals (e.g., every hour, day, week, month).

  • Gemini Vision Model:  Google’s new Gemini multi-modal model is now on our platform!

  • New variables: within LLM and text nodes, you can insert a variable by clicking the insert variable button. Variables will also be displayed differently than text as well.

LLM Guide Highlight

Chain of Thought prompting: Chain-of-thought prompting (CoT) is a prompting method that leads to the emergence of reasoning abilities with large language models and significantly increases their performance. To this end, CoT prompting induces a large language model to articulate its reasoning steps before giving the final answer to the initial question.

If you have any questions or if we can be helpful in any way! Feel free to book a time here as well.

© 2023 VectorShift, Inc. All Rights Reserved.

© 2023 VectorShift, Inc. All Rights Reserved.

© 2023 VectorShift, Inc. All Rights Reserved.