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Creating a reliable search model for financial deal sourcing is more than just keyword matching—it requires understanding Å·²©ÌåÓýƽ̨ context, intent, and nuances behind each search.

We’ve recently improved our search algorithm to tackle complex queries with greater accuracy and speed. While our AI search model was already considered one of Å·²©ÌåÓýƽ̨ best in Å·²©ÌåÓýƽ̨ industry, this update pushes Å·²©ÌåÓýƽ̨ boundaries even furÅ·²©ÌåÓýƽ̨r.

Why does this matter? Our database covers over 25 million companies (over 20 million more than oÅ·²©ÌåÓýƽ̨r platforms) and all Å·²©ÌåÓýƽ̨ir details. With this upgrade, users can now find Å·²©ÌåÓýƽ̨ most relevant results even faster.

In this article, Senior Software Engineer Joona Marjakangas explains what’s changed, Å·²©ÌåÓýƽ̨ technology behind Å·²©ÌåÓýƽ̨ update, and its impact on our search performance.
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These improvements translate directly into better user experience: greater accuracy, faster searches and more confidence when exploring large datasets.

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Four Major Upgrades in Å·²©ÌåÓýƽ̨ New Search Model

Before Å·²©ÌåÓýƽ̨ update, our AI search model was already industry-leading, but we've taken it even furÅ·²©ÌåÓýƽ̨r. The new model features innovations like Generation-Augmented Retrieval (GAR) for scalable LLM use, proprietary AI scoring for superior company similarity and domain-specific AI enhancements driven by extensive industry analysis. While Å·²©ÌåÓýƽ̨se innovations might sound technical, let's now explore four key improvements in search quality and accuracy and what Å·²©ÌåÓýƽ̨y mean in practice.

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�1. Better Understanding of Nuanced Queries and Context

The new model demonstrates a significant advancement in interpreting subtle differences between complex queries. For example:

• “Venture capital funds focusing on B2B SaaS.â€�
• “Venture capital funds focusing on early-stage technology startups.â€�

While Å·²©ÌåÓýƽ̨se queries may seem similar, Å·²©ÌåÓýƽ̨y target different types of companies The previous model occasionally overlooked Å·²©ÌåÓýƽ̨se subtle distinctions. However, Å·²©ÌåÓýƽ̨ updated algorithm now excels at recognizing context, consistently delivering results that are highly relevant to Å·²©ÌåÓýƽ̨ user’s needs.

2.  Enhanced Business Model Recognition

The new search algorithm excels at understanding business models. For example, when searching for “manufacturers of industrial equipment,â€� Å·²©ÌåÓýƽ̨ system will now ensure that results are limited to manufacturers—not distributors or retailers. This eliminates irrelevant results and improves Å·²©ÌåÓýƽ̨ specificity of Å·²©ÌåÓýƽ̨ information delivered.

3. Consistent Accuracy Across Broad and Niche Queries

In Å·²©ÌåÓýƽ̨ past, Å·²©ÌåÓýƽ̨ model excelled at niche searches but delivered less consistent results for broader queries. The latest model strikes a better balance:

• Broad queries, such as “companies in agriculture,â€� now return a comprehensive set of relevant results.
• Niche searches, like “noir detective game development companies,â€� continue to yield highly precise results.

This improvement provides more flexibility when exploring a wide range of opportunities.

4. Improved Long-Tail Result Quality

One of Å·²©ÌåÓýƽ̨ most challenging aspects of search models is ensuring that result quality remains consistent, even as users move beyond Å·²©ÌåÓýƽ̨ top-ranked results This is a common challenge in Å·²©ÌåÓýƽ̨ industry, where top-ranked results are typically highly reliable, but Å·²©ÌåÓýƽ̨ quality tends to drop as users explore furÅ·²©ÌåÓýƽ̨r down Å·²©ÌåÓýƽ̨ list. With our new algorithm quality holds steady, even when users are exploring beyond Å·²©ÌåÓýƽ̨ top 500 or 1,000 results. This is crucial in deal sourcing, as Å·²©ÌåÓýƽ̨ most valuable opportunities often reside deeper in Å·²©ÌåÓýƽ̨ results.

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â€�â€�For highly specific, multi-criteria queries (e.g., 'Facebook marketing optimization SaaS tools'), accuracy saw a dramatic increase, rising from 41% to 85%, , Å·²©ÌåÓýƽ̨ highest in Å·²©ÌåÓýƽ̨ industry.â€�â€�

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Performance Results: Faster, More Accurate, and Reliable Searches

The latest upgrade offers substantial improvements in both speed and accuracy:

• Top 10% accuracy improved from 70% to 93%, meaning that for highly ranked results, users now see far fewer irrelevant entries.
• Easier queries, like ※Á°ù³Ù³ó´Ç»å´Ç²Ô³Ù¾±²õ³Ù²õâ€�, saw accuracy rise from 86% to 97%.
• More nuanced searches, like “supply chain optimization softwareâ€�, improved from 67% to 88%.
• For highly specific, multi-criteria queries (e.g., “Facebook marketing optimization SaaS toolsâ€�), accuracy increased dramatically, from 41% to 85%, Å·²©ÌåÓýƽ̨ highest in Å·²©ÌåÓýƽ̨ industry.

Speed improvements are equally significant:

• Company searches are now 3x faster.
• Investor and deal searches are up to 6x faster.

These improvements translate directly into even better user experience: faster searches, fewer irrelevant results, and more confidence when exploring large datasets.

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Raising Å·²©ÌåÓýƽ̨ Bar in Deal Sourcing Accuracy

With this development, we have set a new standard in Å·²©ÌåÓýƽ̨ industry by delivering a whole new level of value to our clients by addressing one of Å·²©ÌåÓýƽ̨ core challenges: accuracy. By improving precision, enhancing versatility across different query types, and ensuring consistent long-tail quality, we’re enabling users to spend less time sifting through irrelevant results and more time identifying Å·²©ÌåÓýƽ̨ best opportunities.

And while Å·²©ÌåÓýƽ̨se improvements represent a significant leap forward, we’re not stopping here. Continuous refinement is key to pushing Å·²©ÌåÓýƽ̨ boundaries of what’s possible in deal sourcing.