AI Knowledge and Search Startup Funding

What are all the funding deals in the AI knowledge and search market from August 2024 to July 2026?

The table below lists every disclosed equity round raised by pure-play AI knowledge and search companies between August 2024 and July 2026. We count as “pure-play” AI knowledge and search companies those focused on enterprise search, AI knowledge bases, retrieval augmented generation, document intelligence, research assistants, semantic search APIs, or answer generation from information sources.

Each row shows the company, what it does, its category, the deal date, the funding stage, the round size, the region, the main investors, and the announcement source.

How active has fundraising been in the AI knowledge and search market?

As of July 2026, fundraising in the AI knowledge and search market has been active, but not evenly spread. Over the past 24 months, the dataset includes 26 disclosed equity rounds and $2.38B in total capital.

That works out to 1.13 disclosed deals per month, with a median of one deal per month. The AI knowledge and search market therefore shows regular financing activity, but not a broad flood of monthly rounds.

Capital flow looks much larger than deal flow. Average capital raised per month was $103.3M, while the median monthly capital figure was $75M. That difference confirms that large rounds shape the market more than routine activity.

The market also contains 18 unique companies, so the 26 deals are not all first-time events. Several companies raised more than once, including Perplexity, Glean, Reducto, Rogo, Exa, and Parallel Web Systems.

How concentrated has fundraising been in the AI knowledge and search market?

As of July 2026, fundraising in the AI knowledge and search market has been highly concentrated. Over the past 24 months, the largest deal accounts for 21.0% of total capital, while the top 3 deals account for 42.5%.

The top 5 deals reach 57.2% of all disclosed funding. The top 10 deals reach 77.6%, which means most of the market’s visible capital sits in a small group of large platform rounds.

This concentration is not just a mathematical detail. It changes how the AI knowledge and search market should be read. A headline total of $2.38B does not mean dozens of companies had equal access to funding.

The main reading rule is simple. When the AI knowledge and search market looks large, first ask whether Perplexity, Glean, Exa, or another outlier round drove the result.

How much of the AI knowledge and search funding signal is driven by outliers?

As of July 2026, a large share of the AI knowledge and search funding signal is driven by outliers. Over the past 24 months, 13 of 26 deals were above $50M, which means half of all disclosed rounds were megarounds.

The outlier effect is even clearer when rounds above $50M are removed. Total capital falls from $2.38B to $321.6M, so most of the apparent market size comes from large checks.

Rounds above $100M are less common, with 5 deals, or 19.2% of the dataset. But those few rounds carry a disproportionate amount of the market’s funding narrative.

Perplexity is the clearest example. It raised $800M across three rounds, equal to 33.7% of the full dataset. That company should not be treated as a normal peer when reading market averages.

Is the AI knowledge and search market broad with many targets, or narrow with few fundable companies?

As of July 2026, the AI knowledge and search market is moderately narrow. Over the past 24 months, 18 unique companies produced 26 disclosed rounds, so the market has activity but not a long tail of public fundraisers.

The split between categories confirms this. Semantic Search APIs produced 9 deals, Answer Engines produced 7 deals, and Document Intelligence produced 3 deals. The remaining categories had only one or two deals each.

The market is broad enough to cover different product layers, from answer engines to document parsing and vector search. But it is not broad in the sense of having dozens of equally funded companies.

Several categories are effectively represented by a small number of winners. Document Intelligence is driven entirely by Reducto, while Enterprise Search is driven by Glean, and Retrieval Augmented Generation has only one disclosed company in the dataset.

Is AI knowledge and search mostly an early-stage formation market or a late-stage scaling market?

As of July 2026, the AI knowledge and search market is more late-stage scaling market than pure early-stage formation market. Over the past 24 months, late-stage rounds captured $1.52B, or 63.7% of disclosed capital.

Early-stage activity is still meaningful. Seed through Series B rounds captured 18 of 26 deals and $861.6M, which shows company formation has not disappeared.

But the dollars skew late. Series D+ rounds alone captured $910M, or 38.3% of total capital, across only three deals. That means proven platforms absorbed the largest checks.

Series A and Series B each produced seven deals, making them the most active stages by count. The market is therefore doing two things at once: creating new specialized entrants and concentrating capital around visible leaders.

Which categories attract the most investor attention in AI knowledge and search?

As of July 2026, Answer Engines and Semantic Search APIs attract the most investor attention in the AI knowledge and search market. Over the past 24 months, they account for 16 of 26 disclosed deals and $1.65B in capital.

Answer Engines lead by dollars, with $980.4M raised, or 41.3% of total capital. Perplexity, Genspark, You.com, Liner, and Phind make the category the most visible application layer.

Semantic Search APIs lead by deal count, with 9 deals, or 34.6% of the dataset. Exa, Tavily, Parallel, Seltz, Qdrant, TinyFish, and The Intelligent Search Company show how many startups are forming around retrieval infrastructure.

Enterprise Search is smaller by deal count but meaningful by dollars. Glean’s two rounds gave the category $410M, or 17.3% of capital, despite only 7.7% of deals.

Which categories attract disproportionately large checks in the AI knowledge and search market?

As of July 2026, Enterprise Search attracts the most disproportionately large checks in the AI knowledge and search market. Over the past 24 months, it captured 17.3% of capital from only 7.7% of deals, giving it a capital share to deal share ratio of 2.24.

Answer Engines also over-index on check size. They captured 41.3% of capital from 26.9% of deals, giving the category a 1.53 ratio and an average deal size of $140.1M.

Retrieval Augmented Generation sits near parity because Contextual AI had one $80M Series A. Semantic Search APIs, despite leading deal count, under-index slightly with 28.3% of capital from 34.6% of deals.

The lower ratios sit in Document Intelligence, Research Assistants, and AI Knowledge Bases. These categories are fundable, but they are not yet attracting the same scale of checks as answer engines and enterprise search platforms.

Which geographies matter most for fundraising in the AI knowledge and search market?

As of July 2026, North America is the geography that matters most for fundraising in the AI knowledge and search market. Over the past 24 months, it captured $2.25B, or 94.7% of all disclosed capital.

North America also led by deal count, with 23 of 26 disclosed rounds, or 88.5% of activity. The region produced almost every large platform round in the dataset.

Europe appears in the dataset through Sana and Qdrant. It captured $105M, or 4.4% of capital, across two disclosed deals.

Asia-Pacific appears through Liner only. The region captured one deal and $20M, or 0.8% of disclosed capital, which makes it nearly absent from the public English-language funding sample.

Is the AI knowledge and search opportunity set broad or concentrated in one hub?

As of July 2026, the AI knowledge and search opportunity set is concentrated in one main hub. Over the past 24 months, North America accounted for 88.5% of deals and 94.7% of disclosed capital.

This does not mean all product activity is in North America. It means the public venture funding signal is overwhelmingly tied to North American AI talent, enterprise software buyers, and venture networks.

Europe has credible technical assets, especially in knowledge platforms and vector search. But the disclosed funding totals are much smaller, with only $105M across Sana and Qdrant.

Asia-Pacific is even less visible in this dataset. Liner’s $20M Series B is the only qualifying disclosed round, so the region’s public funding footprint is narrow under these filters.

Is AI knowledge and search a market of small experiments or scaled financings?

As of July 2026, the AI knowledge and search market is more a market of scaled financings than small experiments. Over the past 24 months, 16 of 26 disclosed rounds were $50M and above.

The lower end of the market is thin. Only 2 deals were below $5M, 4 deals were between $5M and $20M, and 4 deals were between $20M and $50M.

The median round size of $52.5M is high for a young AI category. It suggests investors are underwriting infrastructure, indexing, data acquisition, and go-to-market budgets before profitability is widely proven.

The average round size is even higher at $91.4M. But that number should be treated carefully because Perplexity, Glean, Exa, and Genspark pull the average above the normal company experience.

Who are the investors that appear the most in AI knowledge and search fundraising?

As of July 2026, the investors that appear most often in the AI knowledge and search market are firms backing multiple layers of the stack. Over the past 24 months, repeat names include IVP, NEA, NVIDIA, Y Combinator, Benchmark, Khosla Ventures, Thrive Capital, Sequoia, Kleiner Perkins, Lightspeed, ICONIQ, Menlo Ventures, and SoftBank.

The repeat investor pattern is important because it spans both applications and infrastructure. Some investors appear around Perplexity and You.com, while others show up around Exa, Reducto, Glean, Parallel, Sana, and Rogo.

This suggests leading venture firms are not choosing only answer engines or only retrieval APIs. They are building exposure across user-facing search, enterprise knowledge, document intelligence, and machine-facing retrieval infrastructure.

One caveat matters. Round announcements rarely disclose the exact check size from each investor, so repeat participation should not be read as exact dollars committed by investor.

What does the stage distribution say about risk in the AI knowledge and search market?

As of July 2026, the stage distribution says risk in the AI knowledge and search market is split between platform concentration and early infrastructure uncertainty. Over the past 24 months, Series A and Series B each produced seven deals, while Series D+ captured the largest dollar share.

Seed rounds are visible but small. They account for 5 deals and only $36.6M, or 1.5% of disclosed capital, which means early experiments exist but do not drive market value.

Series A rounds raised $395M and Series B rounds raised $430M. That shows investors still want to fund specialists, especially in retrieval APIs, document intelligence, and domain research assistants.

But Series C and later plus Growth Equity captured $1.52B. The market risk is therefore not just whether new companies can form, but whether the largest platforms can justify their scale and valuations.

Who is the author of this content?

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