Workflows
Workflows allow you to automate multi-step prompts, making complex interactions more structured and efficient. Unlike Agents, which function as single-prompt shortcuts, Workflows guide the AI through a sequence of prompts to ensure a more accurate and refined final response.
You can enhance each step by activating web search capabilities, adding external integrations via API (e.g., HTTP requests), or scheduling workflows to run automatically. These upgrades make workflows even more powerful for tasks like continuous monitoring, report generation, and real-time research.
When asking for too much in a single prompt, the AI may struggle to process and provide precise answers. Workflows break down complex queries into manageable steps, improving accuracy and relevance at each stage.
Why use Workflows?
Improved Accuracy – The AI delivers more precise responses when given structured, step-by-step prompts.
Better Context Retention – Each step builds on previous answers, leading to a more cohesive final result.
Scalability – Automate repetitive, multi-step tasks to save time and improve efficiency.
Live Web Search (New!) – Enable real-time web search in specific steps to pull the latest, most relevant information directly from the internet.
API Integrations (New!) – Connect external systems and tools using HTTP requests in any workflow step, allowing you to fetch, send, or enrich data programmatically.
Scheduling & Auto-Delivery (New!) – Run workflows on a recurring schedule and receive results via email—perfect for ongoing research, updates, or reporting tasks.
Advanced Setup
Adding Integrations
You can integrate external APIs directly into a specific step of your Workflow. This allows your Workflow to fetch, post, or interact with live data from external tools or platforms.
1. Change Step Type to “Integration”
In the Workflow card, change the Step Type from Prompt to Integration.
This unlocks additional configuration options for connecting to external APIs.
2. Add API URL
The API URL is the endpoint you want to connect to. This is typically provided by the external service you’re integrating with.
Example:
https://api.example.com/v1/company-profile
3. Choose HTTP Method
Select how the Workflow should interact with the API. You can choose from common HTTP methods:
GET– Retrieve dataPOST– Send new dataPATCH– Partially update dataPUT– Fully update or replace dataDELETE– Remove data
Choose the method that matches the API action you need.
4. Configure HTTP Settings
Click the HTTP Settings button to open the setup panel. You’ll need to choose the appropriate Authentication Type depending on the API you're using:
🔐 Authentication Options:
None – No authentication required
You can optionally configure:
Headers (e.g., content-type)
Query Parameters
Request Body (in JSON format)
Basic Auth – Enter a Username and Password for authentication
Additional fields: Headers, Query Parameters, Request Body
Bearer Token – Enter your Token for secure access
Additional fields: Headers, Query Parameters, Request Body
These settings let you pass extra information the API might require (e.g., authentication credentials, filters, data payloads, etc.).
5. Select a Data Room
Choose the Data Room where this Integration step will be executed and its results stored. Think of this like the chatroom context in ChatGPT—it helps the AI understand the environment for this task.
6. Set Run Mode
Choose how this step will be triggered:
Human in the Loop – Manual review required before moving to the next step.
Autopilot – Runs automatically as part of the Workflow.
Scheduling Workflows
Workflows can now be scheduled to run automatically at specific times and frequencies—perfect for recurring tasks like daily reports, market scans, or product updates.
1. Open the Workflow Menu
From your list of workflows, find the workflow you want to schedule. In this example, we’ll use “Company Analysis.”
2. Access the Scheduling Option
Click the three-dot menu (•••) beside the workflow name, then select “Workflow Scheduling.”
3. Set Up the Schedule
A window will appear with scheduling fields:
Start Date: Choose when the workflow should begin.
Time: Set the specific time of day the workflow will run.
Repeat: Select if you want the workflow to repeat (e.g., daily, weekly, monthly).
Notifications: You may choose to receive an email every time this workflow executes.
Use this to automate research, reporting, or other regular AI tasks—so you don’t have to start them manually.
Sample Use Cases
Below are some practical ways to integrate workflows:
Crafting a Brand Analysis – A structured workflow can automate a deep dive into a company’s positioning. Start by analyzing industry trends, then gather competitive insights, and finally perform an internal assessment of services and overall performance. This approach ensures a well-researched and strategic brand analysis.
Setting Up Continuous Market Monitoring – Stay up to date on rapidly evolving topics like AI advancements or economic trends. You can now create a workflow that performs weekly web searches on a topic (e.g., “latest LLM model releases”) and summarizes them. Schedule it to run every Monday and send results directly to your email for convenient tracking.
Enriching Reports with API Integrations – Use integrations to fetch external data (e.g., product pricing, financial stats, or competitor feeds) directly into your workflow. For example, Step 1 could use an integration step to query an external pricing API, and Step 2 could summarize and contextualize that data using the AI model. This is especially useful for dashboards or real-time reporting.
Best Practices
To maximize the effectiveness of your workflows, it's essential to design them with clarity, continuity, and precision in mind. Follow these best practices to ensure smooth execution and optimal AI performance:
Break down complex prompts – Focus on one specific query per step.
Ensure continuity – Each prompt should build on previous responses.
Be clear and specific – Define non-negotiable "need-to-know" information.
Use concise, structured prompts – Avoid vague or overly broad instructions.
Provide context – Give background information when necessary.
Customize the LLM model – Select the best model for each task to enhance output quality.
Use Data Rooms to Organize – Try organizing workflow responses into different datarooms
Leverage Workflow Scheduling – Have weekly scans, or automate repetitive workflows
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