What are the top startups in the agentic AI market?
In our agentic AI market deck, you will find everything you need to understand the market
SUMMARY
What are the top startups in the agentic AI market? Cursor, ElevenLabs, Harvey, Sierra, Glean, Cognition, Legora, Decagon, Vapi, LangChain, Browserbase, Rogo, Factory, Hebbia, and Perplexity are the clearest names today, but they are not winning for the same reasons.
The strongest pattern is that agentic AI does not have one leaderboard. Coding, legal work, customer service, voice, finance, research, and infrastructure are developing with different proof points, so a single ranking would hide more than it explains.
Revenue is the cleanest first filter, and that is why Cursor and ElevenLabs stand out. Both have crossed into a scale where the question is no longer whether people will pay for AI-native workflows, but how durable those workflows become.
Cursor is the clearest commercial winner because it combines revenue, developer habit, and category ownership. In coding agents, daily workflow position matters more than technical spectacle, because the winner becomes part of how engineers actually work.
Legal AI looks unusually investable because the buyer and the task are clear. Harvey and Legora are not selling vague productivity; they are compressing expensive legal labor around review, drafting, research, and document-heavy workflows.
Customer service is the biggest labor pool in the map, but also one of the hardest to judge. Sierra has the capital and enterprise position, Decagon has sharp momentum, and Vapi matters because phone automation may become a core infrastructure layer underneath many applications.
Voice AI is splitting into two different markets. ElevenLabs is winning on platform-scale monetization, while Vapi is proving production-agent usage through live call volume, which is a more operational kind of evidence.
Infrastructure may be the less glamorous but more durable layer. LangChain, Browserbase, Composio, Glean, and Vapi matter because every agent company needs orchestration, browser execution, integrations, context, permissions, and reliability.
Valuation tells a different story from momentum. Cursor and ElevenLabs look more grounded because their revenue bases are already large, while Sierra, Harvey, Legora, Cognition, and Decagon require sharper scrutiny because the implied expectations are heavier.
The best emerging names are the ones where recent signals changed the map. Legora, Decagon, Vapi, Browserbase, Rogo, Factory, and Manus are interesting because they are not just “promising”; they have new evidence that changed how their categories should be read.
The most useful conclusion is layered. Cursor, ElevenLabs, Harvey, Sierra, and Glean are the clearest scaled leaders, while Legora, Decagon, Vapi, Browserbase, Rogo, Factory, and Manus are the names where the freshest signals made the market more interesting.
This market map, featured in our agentic AI market deck, highlights top companies and startups in the agentic AI market
Which agentic AI startups are actually making serious money right now?
Cursor, ElevenLabs, Harvey, Legora, Sierra, Glean, and Perplexity are the clearest revenue-backed names today.
Cursor is in its own category. In June 2026, Forbes reported that Cursor had reached about $4 billion in annualized revenue. When you look at it, that is already bigger than many public software companies. Compared with Cognition, Factory, Magic, or Augment, Cursor has the cleanest proof that AI coding agents have become a paid daily habit, not just an impressive demo.
ElevenLabs is the strongest voice-AI revenue story. The company announced a $500 million Series D at an $11 billion valuation in February 2026, then reportedly crossed $500 million ARR in the first four months of 2026. The reason it ranks above smaller voice-agent startups such as Vapi, Retell, or Bland AI is simple: ElevenLabs has both infrastructure usage and serious revenue scale. The others may be more purely “voice-agent” companies, but ElevenLabs is the one already monetizing voice at platform scale.
Harvey and Legora are the two legal-agent companies with the cleanest commercial proof. Harvey is still ahead: it announced a $200 million raise at an $11 billion valuation in March 2026, and recent reporting put it above $200 million in annualized revenue. Legora is the one catching up fastest. In April 2026, it announced more than $100 million ARR less than 18 months after launch, with over 1,000 customers. Harvey wins on current scale and elite legal penetration. Legora wins on recent acceleration.
Sierra deserves to be here, but with more caution. It reportedly raised $950 million at a $15.8 billion valuation in May 2026, and public estimates put it around $150 million to $200 million ARR. That makes it one of the biggest agentic AI application startups, but its revenue multiple looks much richer than Cursor’s or ElevenLabs’. The company is clearly important; the open question is whether customer-service automation can justify the valuation faster than competitors such as Decagon close the gap.
Glean is less noisy, but it may be one of the more durable enterprise plays. It has reported more than $100 million ARR, and newer estimates put it closer to $200 million ARR. The signal we care about is not only revenue. Glean also reported more than 100 million annual agent actions, which suggests its product is moving from enterprise search into actual workflow execution.
Perplexity is the hardest one to classify. It is more AI search than pure agent startup, but recent estimates put it around $500 million annualized revenue, and its Computer product pushes the company toward task execution. We would include it in the agentic AI map, but we would not put it above the more workflow-native startups.
Which coding-agent startups are really winning developers today?
Cursor is the coding-agent leader right now, with Cognition as the most serious autonomous-agent challenger and Factory as the emerging enterprise workflow bet.
Cursor is ahead because it has the rare combination of daily usage, enterprise pull, and revenue scale. The reported June 2026 annualized revenue figure of about $4 billion makes it difficult to treat any other coding-agent startup as co-leader today. GitHub Copilot may have broader incumbent distribution through Microsoft, but among startups, Cursor is the one that turned coding agents into a breakout business.
Cognition is the stronger “agent replaces engineer tasks” story. Devin made autonomous software engineering feel like a real category, and 2026 reporting put Cognition around a $26 billion valuation with roughly $492 million in annualized revenue. That is enormous, but the comparison with Cursor matters. Cursor looks like a daily developer environment; Cognition looks more like an autonomous worker for larger engineering tasks. Those are related markets, but they are not the same wedge.
Factory is the newer name we would watch closely. In April 2026, the company was reported to be raising $150 million at a $1.5 billion valuation for enterprise coding “Droids.” Its edge is not trying to out-Cursor Cursor. Factory is going after enterprise engineering work queues: tickets, migrations, codebase chores, and tasks where companies want flexible agents that can switch between models. That is a more operational wedge than a developer IDE wedge.
Augment and Magic remain credible, but the evidence is less fresh. Augment has been strong on codebase-aware development, and Magic has been associated with long-context coding models. The issue is that public 2026 revenue and customer evidence is thinner than for Cursor, Cognition, or Factory. In this category, we would rank companies by visible pull first, not by technical mystique.
If you want more recent data on this point, please see our latest agentic AI market report.
As this chart shows, and as featured in our agentic AI market deck, search interest in AI agents has been rising rapidly
Which legal AI startups are actually replacing junior legal work?
Harvey and Legora are the two names that matter most in legal agents right now.
Harvey is still the legal-agent leader. Its March 2026 $11 billion valuation, more than $1 billion in total funding, and reported $200 million-plus annualized revenue put it ahead of every other legal AI startup. It also has the buyer quality: elite law firms, in-house legal teams, and international usage. In legal, that matters more than raw user count because the hard part is winning trust in expensive, high-risk workflows.
Legora is the sharpest emerging challenger in the whole agentic AI market. Its April 2026 announcement of more than $100 million ARR, less than 18 months after launch, is not a normal enterprise SaaS ramp. The comparison with Harvey is useful: Harvey is roughly twice as large on reported annualized revenue, while Legora has scaled fast enough to force a real two-player legal AI race.
The more interesting point is that both companies are winning because legal AI has a clean economic buyer. Law firms already pay junior lawyers and associates to review documents, compare contracts, summarize data rooms, and draft briefs. If an AI agent can compress those hours while staying auditable, the budget case is easier than in vague “AI productivity” categories.
We would not overfill this category with smaller legal AI tools. A lot of startups can say they help lawyers draft or review documents. Very few can show Harvey-level penetration or Legora-level revenue acceleration. For now, legal AI has two obvious startup leaders, and the gap after them is still large.
Which customer-service AI agents are getting closest to real enterprise deployment?
Sierra leads customer-service agents today, Decagon is the fastest-rising challenger, and Vapi is the infrastructure name that could quietly become just as important.
Sierra is ahead because it combines enterprise brand, funding scale, and distribution into real customer-service workflows. In May 2026, it reportedly raised $950 million at a $15.8 billion valuation. In June 2026, it announced a partnership with Kraken Technologies to embed Sierra’s agents into utility customer-service infrastructure. That second signal is more interesting than the round because it gives Sierra a way into a specific operational layer: customer accounts, meters, rates, billing questions, and energy-provider workflows.
Decagon is the challenger with the strongest recent momentum. It raised a $131 million Series C at a $1.5 billion valuation in June 2025, then completed a tender offer at a $4.5 billion valuation in March 2026. That is a 3x valuation step-up in about nine months. Sierra is still much larger, but Decagon is forcing the question: can a more focused customer-experience platform grow into the same enterprise budgets without needing Sierra’s giant capital base?
Vapi belongs in this section because a lot of customer service still happens by phone. In May 2026, Vapi announced a $50 million Series B at a $500 million valuation after processing more than 1 billion calls. It also reported 1 to 5 million calls per day and 10x enterprise ARR growth over the past year. Sierra and Decagon sell more of the customer-service application layer. Vapi sells the voice-agent infrastructure that other companies can build on.
ElevenLabs is relevant too, but the comparison is different. ElevenLabs is far bigger than Vapi on reported revenue, yet Vapi is more directly built for live phone-agent deployment. If we are ranking by total voice AI scale, ElevenLabs wins. If we are ranking by “who powers production voice agents through APIs,” Vapi deserves a separate seat.
Parloa, PolyAI, Bland AI, and Retell are still worth watching, but they do not have the same mix of recent public valuation, usage, and enterprise distribution evidence. The current customer-service stack looks like this: Sierra at the top application layer, Decagon as the fast-rising CX challenger, Vapi as the voice infrastructure breakout, and ElevenLabs as the voice platform giant crossing into agents.
If you want more recent data on this point, please see our latest agentic AI market report.
This chart, included in our agentic AI market deck, illustrates yearly VC funding for agentic AI startups
Which voice-agent startups are hot because people are actually using them?
ElevenLabs and Vapi are the two strongest voice-agent signals now, with Retell, Bland AI, PolyAI, and Parloa behind them.
ElevenLabs is the scale leader. Its February 2026 Series D valued the company at $11 billion, and later reporting said it crossed $500 million ARR in the first four months of 2026. That puts it far ahead of most voice-agent startups commercially. The company started with voice generation, but its ElevenAgents push shows the direction: voice is becoming an interface for doing tasks, not just producing audio.
Vapi is the sharper “agent-native” voice infrastructure bet. The 1 billion processed calls milestone matters because voice agents are fragile in production. Latency, interruptions, accents, transfers, failed integrations, and angry customers expose weak systems fast. A startup processing millions of calls per day is showing a different kind of proof than a startup with polished demos.
Retell and Bland AI are earlier-stage names to track because developers and sales teams are experimenting heavily with phone agents. The issue is evidence depth. We found less public proof of revenue scale and enterprise deployment than for ElevenLabs or Vapi. They may still become important, but today they sit behind the two clearer leaders.
PolyAI and Parloa are more established contact-center voice players. They matter because enterprise voice automation is not new, but the recent heat has shifted toward more flexible AI-native infrastructure. That favors Vapi for builders and ElevenLabs for broad voice capability.
So the voice-agent ranking depends on what we measure. ElevenLabs wins on business scale. Vapi wins on production-agent purity. Retell, Bland AI, PolyAI, and Parloa are credible, but they need fresher comparable signals to move into the top tier.
Which finance and research agents are moving beyond “AI search”?
Rogo, Hebbia, Glean, and Perplexity are the strongest names here, but they solve different jobs.
Rogo is the most important emerging finance-agent startup. In April 2026, it announced a $160 million Series D led by Kleiner Perkins, with participation from Sequoia, Thrive, Khosla, J.P. Morgan Growth Equity Partners, and others. The reason Rogo stands out is its workflow specificity. It is not just answering finance questions but also targeting investment-banking outputs: models, memos, deal screening, buyer outreach, and diligence workflows.
Hebbia is stronger in document-heavy analysis. Its public materials emphasize AI agents that break down complex tasks, review large document sets, and support finance, legal, and government users. The clearest business clue is pricing: reported professional seats at around $10,000 per year for unlimited reasoning, integrations, and workflow automation. That suggests Hebbia is selling to high-value analysts rather than chasing broad consumer usage.
Glean is the enterprise knowledge layer in this category. It is not finance-specific, but it becomes important wherever people need permissioned access to company documents, Slack, tickets, knowledge bases, and internal context. Its reported ARR and agent-action scale make it more proven than many specialized workflow startups. The tradeoff is that Glean is broader, while Rogo and Hebbia are sharper for finance and document work.
Perplexity is the research wild card. It has strong revenue estimates and a clear user habit around answers, but it is less workflow-specific than Rogo or Hebbia. If the task is “find and explain something,” Perplexity is highly relevant. If the task is “produce the model, memo, deck, or diligence output,” Rogo and Hebbia feel closer to the actual job.
That distinction matters. The market is moving from information retrieval to artifact creation. In that shift, Rogo and Hebbia look more agentic than classic search tools because they are built around the work product, not only the answer.
If you want more recent data on this point, please see our latest agentic AI market report.
This chart, included in our agentic AI market deck, shows how Cognition is positioned in agentic AI
Which agent infrastructure startups could become the boring winners?
LangChain, Browserbase, Composio, LlamaIndex, and CrewAI are the infrastructure names to watch, with LangChain clearly ahead on maturity.
LangChain is the leading agent engineering platform. In October 2025, it announced a $125 million Series B at a $1.25 billion valuation, alongside LangChain and LangGraph 1.0, a new Insights Agent, and a no-code agent builder. That matters because the hard problem in agents is no longer making a cool demo. The hard problem is reliability: orchestration, evaluation, monitoring, state, tool use, and failure recovery.
Browserbase is smaller but strategically important. It raised about $40 million at a reported $300 million valuation and launched Director for web automation. The comparison with LangChain is useful: LangChain helps developers structure and monitor agents, while Browserbase gives web agents the browser infrastructure they need to survive production. If agents browse websites, fill forms, and interact with messy interfaces, Browserbase sits close to the pain.
Composio is another hidden-layer startup. It raised $25 million in 2025 and focuses on connecting agents to business tools, with authentication, sandboxes, delegated access, and integrations across hundreds of apps. That is less glamorous than a consumer-facing agent, but it solves a real deployment bottleneck. Agents need to act inside Gmail, Slack, GitHub, Salesforce, Notion, and internal systems without breaking permissions.
LlamaIndex and CrewAI remain important builder tools, but the public commercial proof is less crisp. LlamaIndex is strong around data and retrieval pipelines. CrewAI is strong around multi-agent orchestration. The current hierarchy is therefore LangChain first, Browserbase and Composio as emerging infrastructure specialists, and LlamaIndex/CrewAI as important developer ecosystem players.
Infrastructure startups may look less exciting than application startups, but they can be more durable. If every agent company needs orchestration, browser execution, tool integrations, retrieval, and observability, the picks-and-shovels layer gets paid across the whole market.
Which AI agent startups look most overpriced, and which valuations make more sense?
Cursor and ElevenLabs look the most defensible on revenue scale, while Sierra, Harvey, Legora, Cognition, and Decagon need sharper scrutiny because their multiples are high or less transparent.
Cursor’s valuation is huge, but its revenue base is huge too. Using the reported $4 billion annualized revenue figure, even a $50 billion to $60 billion valuation implies roughly 12.5x to 15x annualized revenue. That is expensive, but in AI terms it is less extreme than many companies with much smaller revenue bases.
ElevenLabs also looks comparatively grounded. An $11 billion valuation against more than $500 million ARR implies roughly 22x ARR. That is still a premium software multiple, but the company has revenue scale, developer usage, enterprise expansion, and a large voice market behind it.
Harvey and Legora are pricier relative to revenue. Harvey at $11 billion and roughly $200 million-plus ARR implies a multiple in the 50x range. Legora at about $5.6 billion and $100 million ARR lands in a similar zone. The difference is that legal AI has unusually clear willingness to pay. If these platforms become the default workspace for law firms, the multiple is easier to understand.
Sierra looks more stretched. Using a $15.8 billion valuation and public ARR estimates around $150 million to $200 million, the implied multiple is roughly 79x to 105x ARR. Sierra may still deserve a premium because customer service is a massive labor budget, but this valuation assumes very fast conversion from pilot and deployment into durable recurring revenue.
Cognition’s reported $26 billion valuation and roughly $492 million annualized revenue imply a multiple around 53x. That is aggressive, but less wild if Devin keeps scaling as an autonomous engineering worker. The missing piece is public proof that customers keep using it deeply after the initial excitement.
Decagon’s $4.5 billion tender valuation is harder to judge because revenue is less visible. The valuation step-up from $1.5 billion in June 2025 to $4.5 billion in March 2026 is a strong momentum signal, but without public ARR we should not pretend we can compare it cleanly with Sierra.
The cleanest valuation-backed leaders are Cursor and ElevenLabs. The most expensive but still strategically credible are Harvey, Legora, Cognition, and Sierra. Decagon is highly interesting, but we need more revenue transparency before calling the valuation obviously justified.
If you want more recent data on this point, please see our latest agentic AI market report.
This chart, included in our agentic AI market deck, illustrates yearly funding for agentic AI startups
Which emerging agentic AI startups should we watch before everyone agrees?
Legora, Decagon, Vapi, Browserbase, Rogo, Factory, and Manus are the emerging names that changed the agentic AI market map lately.
Legora is the clearest emerging breakout because the numbers are unusually clean: more than $100 million ARR, more than 1,000 customers, and less than 18 months since launch. It is rare to see a vertical AI startup scale that quickly in a conservative market. The fact that Harvey is still larger does not weaken Legora’s case; it makes the legal AI race more credible.
Decagon is the customer-service challenger we would watch most closely. A 3x valuation step-up between June 2025 and March 2026 is not enough by itself, but in context it says investors are seeing something in enterprise adoption. The comparison with Sierra is the point: Sierra is the bigger platform, while Decagon may be the more focused AI customer-support company rising underneath it.
Vapi is the voice-agent infrastructure breakout. The 1 billion-call milestone gives it a cleaner usage signal than most early voice-agent startups. If voice agents become a standard customer-service layer, Vapi can win even when the end-user brand belongs to another company.
Browserbase is the hidden web-agent startup. It is not the biggest company on this list, but it sits near a real bottleneck. Web agents need reliable browser sessions, concurrency, anti-bot handling, and automation infrastructure. If the market moves from chat agents to web-acting agents, Browserbase becomes more important.
Rogo is the finance workflow agent to watch. It is not trying to become a generic AI assistant. It is attacking work that investment bankers and investors already produce every week: memos, models, screeners, and diligence outputs. That makes the product easier to evaluate than vague “AI productivity” tools.
Factory is the emerging enterprise coding-agent bet. Cursor owns developer habit. Cognition owns the autonomous-engineer narrative. Factory is going after enterprise engineering work management, where flexibility across models and corporate workflows may matter more than having the prettiest IDE.
Manus is the speculative one. It has serious strategic heat, including reported acquisition interest, but less public revenue and customer evidence. We would watch it closely, not rank it above startups with cleaner business proof.
Which agentic AI startups are famous but less obviously “hot” right now?
Adept, Magic, Augment, Retell, Bland AI, CrewAI, and LlamaIndex are still relevant, but the current evidence does not put them at the top of the market.
Adept is the clearest cautionary example. It helped shape the early general-agent narrative, but the 2024 Amazon licensing and talent deal changed the story. It remains historically important, but it does not look like one of the hottest independent agentic AI startups today.
Magic and Augment are still meaningful in coding. Magic has attracted attention around long-context models, and Augment has a strong codebase-aware positioning. The issue is not that they are weak companies. The issue is that Cursor, Cognition, and Factory have fresher public commercial signals. In a fast market, old buzz decays quickly.
Retell and Bland AI are credible voice-agent startups, but ElevenLabs and Vapi currently have stronger public proof. Retell and Bland may still grow into important players, especially in sales and support calls. Today, they belong on the watchlist rather than the top-leader list.
CrewAI and LlamaIndex are important to builders, but they sit behind LangChain when we rank infrastructure by maturity, funding, and enterprise platformization. CrewAI has mindshare around multi-agent orchestration. LlamaIndex has strong relevance around data and retrieval. The gap is that LangChain has made the clearer move from open-source tool into agent engineering platform.
This is where we should be strict. A startup can be important without being one of the hottest companies right now. For this article, the bar is recent evidence: revenue, usage, customer adoption, funding with context, or a product move that changes its category position.
If you want more recent data on this point, please see our latest agentic AI market report.
This chart, included in our agentic AI market deck, compares the main business model options for autonomous AI agent platforms
So, who are the top startups in agentic AI right now?
Cursor, ElevenLabs, Harvey, Sierra, Glean, Cognition, Legora, Decagon, Vapi, LangChain, Browserbase, Rogo, Factory, Hebbia, and Perplexity are the startups that stand out most consistently today.
Cursor is the overall leader because it has the best mix of revenue scale, product habit, and category ownership. ElevenLabs is the clearest voice-AI platform leader because it combines huge ARR with a move toward interactive agents. Harvey is the legal AI leader, while Legora is the emerging legal challenger moving unusually fast. Sierra leads customer-service agents, although Decagon is the challenger to watch and Vapi may own a key voice infrastructure layer underneath the whole category.
Glean and LangChain matter because agentic AI needs foundations. Glean gives enterprises a permissioned context layer. LangChain gives developers an engineering layer. Browserbase and Composio show the same logic in narrower infrastructure slices: browser automation and tool integrations.
Cognition, Factory, Rogo, Hebbia, and Perplexity fill out the map. Cognition is the most ambitious autonomous coding-agent challenger. Factory is the enterprise coding workflow upstart. Rogo and Hebbia are the most interesting finance/document-workflow names. Perplexity is not a pure agent startup, but its revenue and task-execution push make it impossible to ignore.
The final ranking comes from aggregation.
If we rank only by revenue, Cursor and ElevenLabs dominate.
If we rank by vertical workflow ownership, Harvey, Legora, Sierra, Rogo, and Hebbia become more important.
If we rank by infrastructure leverage, LangChain, Browserbase, Composio, Glean, and Vapi move up.
The best current answer is therefore a layered one: Cursor, ElevenLabs, Harvey, Sierra, and Glean are the clearest scaled leaders; Legora, Decagon, Vapi, Browserbase, Rogo, Factory, and Manus are the emerging names where the freshest signals changed the story.
| Category | Startups selected and why |
|---|---|
| Revenue-backed leaders | Cursor leads by far on reported annualized revenue; ElevenLabs has the strongest voice-AI ARR; Harvey and Legora prove legal AI is already monetizing; Sierra and Glean show enterprise agent revenue beyond coding |
| Coding agents | Cursor is the commercial leader; Cognition is the autonomous-engineer challenger; Factory is the enterprise workflow upstart; Magic and Augment need fresher proof |
| Legal agents | Harvey remains ahead on scale and elite adoption; Legora is the fastest-rising challenger, with $100M-plus ARR less than 18 months after launch |
| Customer-service agents | Sierra leads the application layer; Decagon is repricing fast as a focused CX challenger; Vapi matters because phone automation needs dedicated infrastructure |
| Voice agents | ElevenLabs wins on revenue scale; Vapi wins on production-agent usage; Retell, Bland AI, PolyAI, and Parloa stay on the watchlist |
| Finance and research agents | Rogo is strongest for finance workflow outputs; Hebbia is strongest for document-heavy analysis; Glean and Perplexity matter as broader knowledge and research layers |
| Agent infrastructure | LangChain leads agent engineering; Browserbase owns a painful web-agent infrastructure problem; Composio handles tool integrations; LlamaIndex and CrewAI remain important builder tools |
| Valuation discipline | Cursor and ElevenLabs look most grounded by revenue; Harvey and Legora are expensive but credible; Sierra and Cognition need continued revenue proof; Decagon needs more public ARR transparency |
| Emerging watchlist | Legora, Decagon, Vapi, Browserbase, Rogo, Factory, and Manus are the names where recent signals changed the market map most |
| Famous but less hot today | Adept, Magic, Augment, Retell, Bland AI, CrewAI, and LlamaIndex remain relevant, but current public evidence does not put them ahead of the leaders |
OUR METHODOLOGY
The agentic AI market is difficult to rank from intuition alone because different companies look strong through different lenses. Some are winning on reported revenue, some on usage, some on enterprise deployment, some on workflow ownership, and some on infrastructure leverage.
To make the answer clearer, we broke the market into practical analytical dimensions: coding, legal, customer service, voice, finance and research, infrastructure, valuation discipline, emerging momentum, and famous names with less fresh evidence. For each dimension, we looked at recent public signals and weighed them together rather than treating any single datapoint as decisive.
The signals we prioritized were the ones that showed real market pull: reported ARR or annualized revenue, customer counts, usage milestones, enterprise partnerships, funding rounds with context, valuation changes, product launches, and evidence that the product is being used inside actual workflows. We used valuation mainly as a stress test, not as proof of leadership.
That structured aggregation is what shaped the final answer. The result is not a single vibe-based ranking, but a layered view of which agentic AI startups are already scaled, which are gaining momentum, which own important workflow categories, and which still need fresher public proof.
Key sources used for this analysis include: Forbes on Cursor’s reported annualized revenue, ElevenLabs on its Series D, TechCrunch on ElevenLabs’ funding and valuation, Harvey’s official funding announcement, PR Newswire on Harvey’s funding round, Legora on its ARR and customer milestone, Business Insider on Legora’s revenue milestone, TechCrunch on Sierra’s funding and valuation, Axios on Sierra’s Kraken partnership, Decagon on its tender valuation, TechCrunch on Decagon’s valuation step-up, Yahoo Finance on Vapi’s Series B and call milestone, TechCrunch on Vapi’s enterprise deployment, Glean on its Series F and ARR milestone, TechCrunch on Factory’s enterprise coding round, The Wall Street Journal on Factory’s enterprise positioning, Rogo on its Series D, LangChain on its Series B, PR Newswire on Browserbase’s Series B and Director launch, SiliconANGLE on Composio’s funding and agent-tool integrations, and TechCrunch on Adept’s Amazon licensing and talent deal.
This chart, featured in our agentic AI market deck, shows the share of revenue generated by each customer segment in the agentic AI market
Related blog posts
- How strong is fundraising in the agentic AI market right now?
- The startups that have raised the most funding in the agentic AI market
- The most highly valued startups in the agentic AI market
- Where is the money in the agentic AI market?
- Is Prometheus really worth $41B?
