Should I Build It Should I Build It
16 Sep 2025
SaaS

Invoice and bank statement data extraction from PDF and images

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Swamp

The market has seen several mediocre solutions that nobody loves. Unless you can offer something fundamentally different, you’ll likely struggle to stand out or make money.

Should You Build It?

Don't build it.

Your are here

You're entering a crowded space with your invoice and bank statement data extraction idea. We found 24 similar products, suggesting high competition. The average engagement for these products is low, with only 2 comments per launch, meaning the users might not be finding a good solution, or the products are not discoverable enough. There is no net use or buy signal, meaning that on average people didn't express a clear intention to use or buy these similar products explicitly. Overall, this puts your idea into the 'Swamp' category, which is a market filled with mediocre solutions. To succeed, you'll need to find a significant differentiator or focus on an underserved niche.

Recommendations

  1. Given that you're entering a crowded market, thoroughly research why existing solutions haven't achieved widespread success. What are their limitations, and where do users express frustration? Use the criticism summaries from the similar product launches as a starting point to identify pain points that you can address.
  2. If you decide to proceed, identify a specific niche or group that's currently underserved by existing solutions. For example, focus on businesses that require support for very specific custom invoice formats, or those needing advanced handwriting parsing capabilities. Tailor your solution to meet their unique needs.
  3. Instead of directly competing with existing providers, consider developing tools that enhance their offerings. You could create a plugin or API that adds specific functionality to existing invoice processing software, making it more attractive to potential users and easier to adopt.
  4. Based on feedback from similar products, prioritize data security and privacy. Implement robust encryption and data handling practices to address user concerns and build trust. Consider offering a direct Excel export option to mitigate potential risks associated with intermediary data handling processes.
  5. Explore adjacent problems that might be more promising or less competitive. Could you expand your solution to handle other types of documents, such as receipts or contracts? Or could you focus on providing data analysis and reporting services based on the extracted data?
  6. Focus on accuracy and customization as key differentiators. According to criticism summaries, many products rely on off-the-shelf OCR solutions that lack accuracy and customization options. Develop a solution that allows users to fine-tune the OCR process for their specific use cases.
  7. Address the need for scalability and efficient processing of multi-page documents. Users have expressed interest in products that can handle large volumes of documents and process them in parallel. Ensure that your solution can meet these requirements.

Questions

  1. Given the existing solutions, what specific pain points or unmet needs do you believe your solution addresses in a fundamentally different or superior way? How will you validate these assumptions early on?
  2. Considering the low engagement observed in similar product launches, what innovative go-to-market strategies will you employ to ensure your solution gets discovered and adopted by your target audience?
  3. How will you balance the need for robust data security and privacy with the desire for ease of use and seamless integration with existing workflows?

Your are here

You're entering a crowded space with your invoice and bank statement data extraction idea. We found 24 similar products, suggesting high competition. The average engagement for these products is low, with only 2 comments per launch, meaning the users might not be finding a good solution, or the products are not discoverable enough. There is no net use or buy signal, meaning that on average people didn't express a clear intention to use or buy these similar products explicitly. Overall, this puts your idea into the 'Swamp' category, which is a market filled with mediocre solutions. To succeed, you'll need to find a significant differentiator or focus on an underserved niche.

Recommendations

  1. Given that you're entering a crowded market, thoroughly research why existing solutions haven't achieved widespread success. What are their limitations, and where do users express frustration? Use the criticism summaries from the similar product launches as a starting point to identify pain points that you can address.
  2. If you decide to proceed, identify a specific niche or group that's currently underserved by existing solutions. For example, focus on businesses that require support for very specific custom invoice formats, or those needing advanced handwriting parsing capabilities. Tailor your solution to meet their unique needs.
  3. Instead of directly competing with existing providers, consider developing tools that enhance their offerings. You could create a plugin or API that adds specific functionality to existing invoice processing software, making it more attractive to potential users and easier to adopt.
  4. Based on feedback from similar products, prioritize data security and privacy. Implement robust encryption and data handling practices to address user concerns and build trust. Consider offering a direct Excel export option to mitigate potential risks associated with intermediary data handling processes.
  5. Explore adjacent problems that might be more promising or less competitive. Could you expand your solution to handle other types of documents, such as receipts or contracts? Or could you focus on providing data analysis and reporting services based on the extracted data?
  6. Focus on accuracy and customization as key differentiators. According to criticism summaries, many products rely on off-the-shelf OCR solutions that lack accuracy and customization options. Develop a solution that allows users to fine-tune the OCR process for their specific use cases.
  7. Address the need for scalability and efficient processing of multi-page documents. Users have expressed interest in products that can handle large volumes of documents and process them in parallel. Ensure that your solution can meet these requirements.

Questions

  1. Given the existing solutions, what specific pain points or unmet needs do you believe your solution addresses in a fundamentally different or superior way? How will you validate these assumptions early on?
  2. Considering the low engagement observed in similar product launches, what innovative go-to-market strategies will you employ to ensure your solution gets discovered and adopted by your target audience?
  3. How will you balance the need for robust data security and privacy with the desire for ease of use and seamless integration with existing workflows?

  • Confidence: High
    • Number of similar products: 24
  • Engagement: Low
    • Average number of comments: 2
  • Net use signal: 14.3%
    • Positive use signal: 14.3%
    • Negative use signal: 0.0%
  • Net buy signal: 0.0%
    • Positive buy signal: 0.0%
    • 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.

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The Invoice OCR launch received overwhelmingly positive feedback, with users praising its ease of use, high data extraction accuracy, and impressive self-learning handwriting parsing. Many congratulated the team and wished them success. The user interface was described as awesome. The product is regarded as a top-notch solution for invoice processing and data entry, recommended for easing user tasks. There was an inquiry about API pricing and a suggestion to compare the product with existing solutions like edenai.co, and a collaboration suggestion for Invoice OCR implementation.

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Hi HN, I've built a SaaS to solve a data entry task that I have often had as a business owner - to be able to extract key invoice data from batches of invoice files for financial record keeping.From my experience GPT-4o now outperforms traditional OCR for extracting text from documents, plus the LLM's reasoning ability means that specific data can be extracted and formats can be converted as desired. Traditional OCR services generally extract all text in the document and of course they extract it as-is without the ability to convert dates etc. Accounting software usually expects imported data to be in a specific format.The tool can extract data from batches of mixed invoice types (PDF, Word, JPG, PNG) which is particularly useful for 'bricks and mortar' businesses who often have mixed format invoices such as scanned documents or photos of receipts. The data is extracted to a spreadsheet with columns that the user defines ready for the user's workflow or for importing into their accounting software.The tool optimizes the document contents for best LLM understanding - which isn't necessarily what happens when you upload the documents to ChatGPT for example.I've tried to make the software as easy to use as possible, so hopefully there isn't a learning curve involved - it is just completing our template by using natural language to describe the data you need extracting. Again, with traditional (non LLM) OCR tools there is usually a learning curve involved in using the software, a long set-up process, and a rigid invoice format expected.If there are any business owners, bookkeepers or accountants who think the tool might be useful for them then I'm extremely open to working with you as an early user to onboard you with additional free credits so you can test out the software.I've tried to keep this brief - it would be great to hear feedback or hear from anyone who thinks this might be useful for them!Best regards, David.

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