Pre-Seed Startup analysis

Specification for AI-Powered Pre-Seed Startup Analysis Tool using Latitude

Live example

Try out this agent setup in the Latitude Playground.

Copy to your Latitude

Objective

We want to create an AI-powered tool that can analyze pre-seed startups based on pitch decks and other documents. The tool will extract key information, conduct research, and generate a structured report in Notion. Let’s put an example.

Input email

Let’s imagine is 2008 and Bryan Chesky sends an email to a fund with a pitch deck for a startup called Airbnb. Our tech incubator is super successful and we don’t want to miss any good candidates. So we create an agentic tool in Latitude that can receive emails like this and analyze the startups that are being pitched.

Show Original Bryan's email

Analysis of the email

The final result is a structured report stored in a Notion database.

Show Extracted data from Bryan's email

The setup

This project use different parts from Latitude let’s start by listing them:

Show Prompt references

Prompt references like for example <prompt path="section_example" /> allow you to reuse prompts in different parts of your project. This is useful to avoid duplication and keep your code DRY.

Show Steps

Steps allow to interact with the AI in a step-by-step manner, breaking down complex tasks into manageable parts. In this case, we use steps to handle the analysis of the startup in a structured way.

steps

<step agents={{ ["agents/interpreter"] }}>
1. Interpretation:
You should use the `interpreter` agent to extract and organize all the official information provided in the email, including the complete content and attached URLs.
</step>
<step agents={{ ["agents/team_finder"] }}>
2. Team identification:
You should use the `team_finder` agent to find the main team members.
</step>
<step agents={{ ["agents/identity_checker"] }}>
3. Team verification:
You should use the `identity_checker` agent to validate the background and profiles of all founders and key members.
</step>
<step agents={{ ["agents/metrics_hunter"] }}>
4. Traction metrics:
You should use the `metrics_hunter` agent to search and confirm data about users, revenue, growth, etc.
</step>
<step agents={{ ["agents/business_model_analyzer"] }}>
5. Business model:
You should use the `business_model_analyzer` agent to investigate and analyze the business model.
</step>
<step agents={{ ["agents/investigator"] }}>
6. Funding:
You should use the `investigator` agent to research investment rounds, investors, and valuation.
</step>
<step agents={{ ["agents/tech_stacker"] }}>
7. Product analysis:
You should use the `tech_stacker` agent to investigate the technology used in the product.
</step>
<step agents={{ ["agents/market_mapper"] }}>
8. Market analysis:
You should use the `market_mapper` agent to analyze the target market, size, and competitors.
</step>
<step agents={{ ["agents/competition_research"] }}>
9. Solution mapping:
You should use the `competition_research` agent to obtain an overview of all existing solutions to the problem the company is trying to solve, without bias.
</step>
<step agents={{ ["agents/evaluation_expert"] }}>
11. Final evaluation:
You should use the `evaluation_expert` agent to evaluate the draft, identify strengths, risks, and issue a final recommendation.
</step>

Show Email triggers

Email triggers allows us to receive emails in our Latitude accoun when they are sent to a specific address. Check the docs to see how to set it up.

Show Agents

In latitude you convert a prompt into an agent by adding the type: agent field to the prompt. This allows you to create a multi-agent architecture where each agent is responsible for a specific task in the analysis process. You can learn more about agents in the agents documentation.

Show Latitude tools

Latitude tools are used to search information in Internet

Show MCP calls

In this example we use the Notion MCP integration to call the Notion API and create a database item with the final report. MCP calls allow you to interact with external APIs in a structured way, making it easy to integrate with services like Notion. We also use this Apify MCP to extract information from Crunchbase.

notion mcp

---
provider: Latitude
model: gpt-4o-mini
temperature: 0
tools:
  - use_cases_notion/*
type: agent
---

Notion integration

Most of the elements used in this project are easy to understand following Latitude documentation, but the Notion integration is a bit more complex. Let’s do a quick overview of how to set it up.

1. You need to create a Notion workspace
2. Go to Notion Integrations and create new integration for Latitude. You will need an API to setup the Notion’s MCP server on Latitude.

   Show Create integration

   

3. Once you have the integration we need do do 2 more things.

   1. copy the Internal Integration Token for configuring the MPC server on Latitude.
   2. Give access to this integration to one of our pages in the workspace (yellow box in the image above).

   Show Copy Integraion token

   

The prompts

The tool is an AI agent divided in sub-agents, each responsible for a specific task in the analysis process. The main agent coordinates the workflow and ensures that all tasks are completed efficiently.

Latitude is flexible enough to allow you to structure workflows quite complex in a way that makes sense for you. In this case we decided to create an agents folder with all the processing work and a publish agent that is responsible for the formatting and publishing of the final report in Notion.

main

---
provider: OpenAI
model: gpt-4.1
temperature: 0
type: agent
maxSteps: 40
agents:
  - agents/interpreter
  - agents/team_finder
  - agents/identity_checker
  - agents/metrics_hunter
  - agents/investigator
  - agents/competition_research
  - agents/evaluation_expert
  - agents/market_mapper
  - agents/tech_stacker
  - agents/business_model_analyzer
  - publish

Let’s do a breakdown of all the prompts (agents) and their roles.

Data extraction

Purpose: Gather all foundational, official, and structured data directly from source materials (pitch decks, websites, emails). Agents:

• agents/interpreter: Extracts comprehensive company, product, market, team, and funding information from any document or webpage.
• agents/team_finder: Collects a verified list of current team members, focusing on accuracy and relevance.

Validation & Enrichment

Purpose: Ensure accuracy, completeness, and credibility of extracted information; deepen profiles and history. Agents:

• agents/identity_checker: Verifies founder and executive backgrounds using professional networks and databases.
• agents/investigator: Confirms fundraising history, round details, and investor lists using financial and deal sources.

Market & Business Analysis

Purpose: Contextualize the company within its business model, market, competition, and traction environment. Agents:

• agents/business_model_analysis: Maps how the startup makes money, whom it serves, and how it goes to market.
• agents/market_mapper: Defines the addressable market, sizes opportunity, and identifies key competitors and trends.
• agents/competition_research: Builds a competitive landscape, classifying direct and indirect solutions in the space.
• agents/tech_stacker: Details technology stack and infrastructure, surfacing technical strengths or risks.
• agents/metrics_hunter: Finds, validates, and contextualizes traction metrics—users, revenue, growth, engagement.

If you want to really play with this example in live you can copy it to your Latitude account here