20 Jul 2025
Marketing

Sourcing tool for private equity firms based on knowledge graphs

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Strong Contender

The market has shown clear demand for this type of solution. Your challenge now is to create a version that stands out while delivering what people already want.

Should You Build It?

Build but think about differentiation.


Your are here

Your idea for a sourcing tool for private equity firms based on knowledge graphs falls into the "Strong Contender" category, meaning there's demonstrated market demand. Four similar products have already emerged, so the need is validated, but competition is present. The average engagement (10 comments) across these similar products suggests that users are indeed interested and providing feedback. Although there is no direct use signal, it appears that there is a very strong, positive buy signal, which is rare and promising. This means people are willing to pay for this kind of product. Now your challenge is to create a tool that stands out and delivers unique value within this established market. You need to differentiate yourself.

Recommendations

  1. Begin by deeply analyzing what the most successful competitors, like Accorata and Private Equity List, do well. Accorata is praised for quick and accurate deal flow information and automated pitch decks. Private Equity List is commended for its comprehensive nature, particularly in AI, EdTech, and blockchain sectors. Identify their strengths to understand the baseline expectations of users.
  2. Based on competitive analysis, pinpoint 2-3 key areas where you can surpass existing solutions. Consider addressing criticisms of competitors. For example, Private Equity List faced concerns about data accuracy and pricing; focus on providing meticulously cleaned data and a more accessible pricing model or trial period to alleviate user concerns. Offering a free basic tier might attract new users initially.
  3. Launch a minimum viable product (MVP) focusing on the core features that private equity firms value most. Prioritize delivering immediate value with the essential functions, such as deal sourcing, company information, and industry insights. This allows you to validate your assumptions and iterate based on real-world usage.
  4. Implement a charging model from the outset, even if it's a discounted rate for early adopters. This will help you to validate real demand and gauge willingness to pay. Offer different pricing tiers to cater to varying needs and budgets within private equity firms, from smaller boutiques to larger enterprises.
  5. Concentrate on delivering exceptional service and value to your first 50 customers. Gather their feedback meticulously, address their pain points promptly, and incorporate their suggestions into product development. Word-of-mouth referrals from satisfied customers will be invaluable in the early stages.
  6. Consider the UI/UX. Some users found the Private Equity List overwhelming. A guided tour or simplified interface could improve user experience. Also, avoid stock images to maintain a professional look.
  7. Since data accuracy is a concern (as noted in the criticism of Private Equity List), clearly articulate your data cleaning and validation processes. Transparency in how you ensure data quality will build trust.

Questions

  1. How will you ensure the knowledge graph is consistently updated with the latest information, and what specific data sources will you utilize to maintain accuracy and completeness, especially considering the dynamic nature of private equity deals and market trends?
  2. Given that the positive buy signal is strong, what specific features or unique data points can you offer that would justify a premium pricing strategy compared to existing solutions like Crunchbase or Pitchbook, and how will you communicate this value proposition effectively to private equity firms?
  3. How will you balance the depth and breadth of information within your sourcing tool to avoid overwhelming users, and what filtering or customization options will you provide to enable private equity professionals to quickly identify relevant deals and insights based on their specific investment criteria?

Your are here

Your idea for a sourcing tool for private equity firms based on knowledge graphs falls into the "Strong Contender" category, meaning there's demonstrated market demand. Four similar products have already emerged, so the need is validated, but competition is present. The average engagement (10 comments) across these similar products suggests that users are indeed interested and providing feedback. Although there is no direct use signal, it appears that there is a very strong, positive buy signal, which is rare and promising. This means people are willing to pay for this kind of product. Now your challenge is to create a tool that stands out and delivers unique value within this established market. You need to differentiate yourself.

Recommendations

  1. Begin by deeply analyzing what the most successful competitors, like Accorata and Private Equity List, do well. Accorata is praised for quick and accurate deal flow information and automated pitch decks. Private Equity List is commended for its comprehensive nature, particularly in AI, EdTech, and blockchain sectors. Identify their strengths to understand the baseline expectations of users.
  2. Based on competitive analysis, pinpoint 2-3 key areas where you can surpass existing solutions. Consider addressing criticisms of competitors. For example, Private Equity List faced concerns about data accuracy and pricing; focus on providing meticulously cleaned data and a more accessible pricing model or trial period to alleviate user concerns. Offering a free basic tier might attract new users initially.
  3. Launch a minimum viable product (MVP) focusing on the core features that private equity firms value most. Prioritize delivering immediate value with the essential functions, such as deal sourcing, company information, and industry insights. This allows you to validate your assumptions and iterate based on real-world usage.
  4. Implement a charging model from the outset, even if it's a discounted rate for early adopters. This will help you to validate real demand and gauge willingness to pay. Offer different pricing tiers to cater to varying needs and budgets within private equity firms, from smaller boutiques to larger enterprises.
  5. Concentrate on delivering exceptional service and value to your first 50 customers. Gather their feedback meticulously, address their pain points promptly, and incorporate their suggestions into product development. Word-of-mouth referrals from satisfied customers will be invaluable in the early stages.
  6. Consider the UI/UX. Some users found the Private Equity List overwhelming. A guided tour or simplified interface could improve user experience. Also, avoid stock images to maintain a professional look.
  7. Since data accuracy is a concern (as noted in the criticism of Private Equity List), clearly articulate your data cleaning and validation processes. Transparency in how you ensure data quality will build trust.

Questions

  1. How will you ensure the knowledge graph is consistently updated with the latest information, and what specific data sources will you utilize to maintain accuracy and completeness, especially considering the dynamic nature of private equity deals and market trends?
  2. Given that the positive buy signal is strong, what specific features or unique data points can you offer that would justify a premium pricing strategy compared to existing solutions like Crunchbase or Pitchbook, and how will you communicate this value proposition effectively to private equity firms?
  3. How will you balance the depth and breadth of information within your sourcing tool to avoid overwhelming users, and what filtering or customization options will you provide to enable private equity professionals to quickly identify relevant deals and insights based on their specific investment criteria?

  • Confidence: Medium
    • Number of similar products: 4
  • Engagement: Medium
    • Average number of comments: 10
  • Net use signal: 13.0%
    • Positive use signal: 13.0%
    • Negative use signal: 0.0%
  • Net buy signal: 2.0%
    • Positive buy signal: 2.0%
    • Negative buy signal: 0.0%

This chart summarizes all the similar products we found for your idea in a single plot.

The x-axis represents the overall feedback each product received. This is calculated from the net use and buy signals that were expressed in the comments. The maximum is +1, which means all comments (across all similar products) were positive, expressed a willingness to use & buy said product. The minimum is -1 and it means the exact opposite.

The y-axis captures the strength of the signal, i.e. how many people commented and how does this rank against other products in this category. The maximum is +1, which means these products were the most liked, upvoted and talked about launches recently. The minimum is 0, meaning zero engagement or feedback was received.

The sizes of the product dots are determined by the relevance to your idea, where 10 is the maximum.

Your idea is the big blueish dot, which should lie somewhere in the polygon defined by these products. It can be off-center because we use custom weighting to summarize these metrics.

Similar products

Relevance

Accorata - The AI deal sourcing platform for early-stage investors

The AI deal sourcing platform for early-stage investors. Never miss a deal within your investment niche with daily signals of early-stage startups, automated processing of decks landing in your inbox, and founder due diligence.

Accorata's Product Hunt launch has garnered positive feedback. Users appreciate its ability to provide accurate and quick information for deal flow, automate pitch decks, and offer market updates. The tool is seen as helpful for VCs in assessing startups, addressing a gap in the market. Several users expressed excitement about trying out the idea and congratulated the team on the launch, praising both the concept and design. Beta sign-ups were reported, with users looking forward to the tool's simplification of startup scouting.

The primary criticism revolves around the product being a beta version with unresolved issues and tweaks still needed. This suggests a lack of polish and potential instability that could negatively impact the user experience.


Avatar
121
8
50.0%
8
121
50.0%
Relevance

Private Equity List - User-friendly alternative to Crunchbase and Pitchbook

A platform where you can search over 6000 PE/VC funds, 1600 accelerators and incubators, and 23,000 investor contacts. Filter by region, stage, industry, investment ticket, minority support and more. From $25 per month.

The Product Hunt launch received overwhelmingly positive feedback, with many users congratulating the team and individuals on the launch. Several users praised the product's usefulness and comprehensive nature. Specific interests included its focus on AI, EdTech, and blockchain. Constructive feedback included suggestions for expanding coverage, reviewing fund robustness, and offering lifetime deals to address pricing concerns. Some users found the platform overwhelming, suggesting a free basic tier to attract new users. Questions arose about data cleaning methods and the platform's function as a connection database. One user criticized the stock images used on the site.

Users criticize the platform's data accuracy, citing false positives from sources like CB and PitchBook. The pricing is considered too high, with suggestions for lifetime deals. Some find the platform overwhelming and suggest a guided tour for new users. Minor issues include stock images and outdated information, specifically an outdated VentureNursery listing which needs a fund list review.


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341
31
6.5%
3.2%
31
341
6.5%
3.2%
Relevance

Compare GraphRAG and RAG on earning call transcripts

Hi HN,Microsoft recently open-sourced the GraphRAG framework for information retrieval, utilizing graph-based structures. It automates the construction of knowledge graphs using LLMs and enhances retrieval by connecting related concepts and entities in a query for more contextual and accurate responses.GraphRAG offers a larger connected context for retrieved information, which LLMs use to answer summarization-focused queries. It does not replace RAG but can significantly augment existing information extraction pipelines.Asking questions on financial data is one example of a great use case for GraphRAG.Check out this demo comparing quarterly earnings call transcripts from a few companies to see a side-by-side comparison: https://graphrag-demo.deepset.aiCurious to hear your thoughts.

Vector RAG struggles with complex queries.

Vector RAG can't answer complex queries.


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