Which AI apps are getting acquired now?

Which AI apps are actually getting acquired right now?

AI apps that own a valuable workflow are getting acquired most aggressively right now, especially in customer support, coding, sales, productivity, finance, healthcare and AI security.

The overall acquisition market is clearly active enough to separate a pattern from a handful of flashy deals. CB Insights counted 782 acquisitions of private AI companies in 2025, more than 50% above the previous year. Another 266 AI M&A transactions closed in the first quarter of 2026, up 90% year over year.

Those totals include infrastructure companies, model developers and talent deals, so they exaggerate the number of ordinary AI applications changing hands. Once we isolate software that people actually use to do work, though, the same types of products keep appearing.

Salesforce acquired Fin in customer support. Cognition acquired Windsurf in coding. Zoom acquired Common Room in sales intelligence. Asana bought StackAI for enterprise agents. Superhuman acquired Fathom for meetings. Genesys bought Pinkfish for customer-experience automation.

Across very different categories, buyers keep choosing AI products that already sit inside a useful workflow and can be plugged into a much larger distribution machine.

Recent AI acquisition area	Examples	What buyers were really adding
Customer support	Fin, Forethought, Pinkfish	Automated resolution and workflow execution
Coding	Windsurf, Astral	Developer workflow and existing adoption
Sales	Common Room, Aampe	Customer signals and revenue actions
Productivity	Fathom	Meeting context and daily usage
Enterprise agents	StackAI	Agents connected to company systems
AI security	Portkey	Governance of models and agents
Vertical AI	Kaia Health, Bonsai Health	Industry workflow, customers and specialized distribution

Why are customer-support AI apps getting bought so often?

Customer-support AI is currently one of the clearest acquisition categories because buyers can measure exactly what the software is supposed to replace or resolve.

Salesforce's Fin deal is the biggest example. When Salesforce completed the acquisition, it said Fin served more than 30,000 companies and was averaging a 76% resolution rate across customer interactions. Salesforce was buying a product that could already handle support through channels including chat, email, WhatsApp, SMS and voice.

Zendesk reached a similar conclusion with Forethought. By the time Zendesk agreed to buy the company, Forethought said its technology was handling more than one billion customer interactions per month and was being used by companies including Upwork, Airtable, Grammarly and Datadog.

Genesys then acquired Pinkfish to push further into autonomous customer-service workflows. Pinkfish connects AI agents to the systems where the actual work gets completed.

Three major customer-experience companies independently buying this type of software tells us more than one large transaction would. Support AI has moved beyond summarizing conversations and suggesting replies. The more valuable products can now resolve the request and trigger what happens next.

Are AI agent apps actually being acquired now?

Yes. AI agent apps are getting acquired, especially when the agent can take actions inside real company software.

Asana paid $75 million for StackAI, whose platform lets companies create agents connected to enterprise systems and internal data. Genesys bought Pinkfish for a similar reason in customer service. MoEngage acquired Aampe, which uses AI agents to decide how individual customers should be contacted. ModMed acquired Bonsai Health to automate patient reactivation and scheduling.

The wording changes from deal to deal, but the product behavior is remarkably similar. These systems read company context, make a decision and then do something.

A useful test is whether a buyer can explain the acquired product with a specific verb: resolve, schedule, reconcile, qualify, contact, update or execute.

Apps that mainly provide another chat window have a much harder acquisition story.

Are AI coding apps still among the hottest acquisition targets?

AI coding remains one of the strongest acquisition categories today because some coding products reached serious revenue and enterprise adoption extraordinarily fast.

Cognition's acquisition of Windsurf remains the cleanest example. At the time of the deal, Cognition said Windsurf had reached $82 million in annual recurring revenue, more than 350 enterprise customers and hundreds of thousands of daily active users.

The combination also made strategic sense at product level. Windsurf gave Cognition an AI-native development environment used while programmers actively write code, while Devin handles longer autonomous software tasks. Instead of relying on one interaction model, Cognition ended up covering more of the software-development workflow.

The performance after the acquisition makes the deal even more interesting. Cognition later said combined enterprise ARR rose more than 30% within seven weeks. More recently, the company has reported annualized revenue approaching $900 million across the broader Cognition business.

OpenAI's acquisition of Astral points in the same direction from another angle. Astral built widely used Python tools such as uv and Ruff. Buying Astral gave OpenAI access to a developer workflow that already existed rather than forcing Codex to create that habit from scratch.

Coding currently shows what an especially attractive AI acquisition can look like: heavy usage, fast-growing revenue, enterprise customers and a product sitting directly where work gets done.

Why are AI sales apps getting acquired?

AI sales apps become much more attractive when they own buyer data and customer signals rather than simply generating outreach messages.

Zoom's acquisition of Common Room makes that distinction clear. Common Room combines information coming from CRM systems, product usage, marketing activity and other customer signals. Zoom can then connect that intelligence to its broader revenue platform and AI agents.

MoEngage's acquisition of Aampe followed a related strategy. Aampe had reportedly grown revenue by about 150% over the previous year, while its software made engagement decisions for individual users rather than relying entirely on broad marketing segments.

Banzai's acquisition of ConnectAndSell adds another useful comparison. ConnectAndSell entered the transaction with about $14.7 million in annual revenue, an 86% gross margin and roughly 4.8 million live sales conversations facilitated each year.

The important asset in these deals sits around the generated message. Buyer history, product activity, customer identity, existing integrations and the path from recommendation to revenue are much harder to reproduce than AI-generated sales copy itself.

Are AI meeting apps still worth buying now that transcription is everywhere?

AI meeting apps can still be valuable acquisition targets, although plain transcription has become far less interesting on its own.

Superhuman's acquisition of Fathom shows where the value has moved. Fathom records, transcribes and summarizes meetings, but Superhuman wants that meeting history to become context for AI working across email, documents, calendars and other applications.

Fathom had already reached hundreds of thousands of companies before the deal and became HubSpot's most-used marketplace app in 2025. That existing habit is important. Building another meeting transcript feature would be easy compared with recreating years of customer adoption and accumulated conversation context.

Meeting software is becoming part of a broader contest over company memory. The buyer gets decisions, objections, commitments, relationships and action items that happened in conversations, all attached to a product people already use.

Do AI productivity companies want whole apps or just their features?

Productivity companies are increasingly buying entire AI apps because an established app gives them users, context and a place in the workday at the same time.

The series of acquisitions around Superhuman is unusually revealing. Grammarly first acquired Coda and later the Superhuman email app before reorganizing the combined business under the Superhuman name. The company subsequently moved into AI detection through GPTZero and meetings through Fathom.

Taken together, those products touch writing, documents, email, meetings and content provenance. Each additional application gives Superhuman's AI access to another part of a user's working context.

That is why apparently replicable apps can still attract buyers. The engineering team at a large software company may be able to reproduce a feature in months. Reproducing the app's customers, integrations, habits and historical data usually takes much longer.

Are AI security apps becoming acquisition targets too?

AI security and governance apps are becoming a serious acquisition category as companies deploy more agents inside their own systems.

Palo Alto Networks' acquisition of Portkey is one of the clearest examples. Portkey operates an AI gateway that helps enterprises route, observe and govern traffic between applications and AI models. Before the deal, Portkey said the platform was already processing trillions of tokens per month.

Cisco's acquisition of Astrix Security addresses another emerging problem: AI agents and other non-human identities can receive access to sensitive applications and data. As companies create more automated actors, security teams need to understand what those actors can access and what they are doing.

GPTZero shows a more application-oriented version of the same trend. When Superhuman agreed to acquire the company, GPTZero had roughly 19 million registered users and was reported to be generating around $30 million in ARR. Its product had expanded beyond basic AI-text detection into plagiarism, AI-image detection, citation verification and authorship tools.

The AI boom is creating acquisition demand on both sides of the equation. Companies want software that lets agents do more work, while security and governance products are being bought to keep that work under control.

Are vertical AI apps in healthcare and finance getting acquired?

Vertical AI apps are getting acquired today, and specialization can make them particularly attractive when it comes with customers, regulation or industry-specific data.

Sword Health's $285 million acquisition of Kaia Health is a strong example. Kaia brought millions of eligible members, employer and health-plan relationships and access to Germany's digital-health reimbursement system, which covers more than 70 million people.

ModMed's acquisition of Bonsai Health was smaller but followed the same logic. ModMed already sells software to specialty medical practices, and Bonsai added AI-driven patient reactivation and scheduling directly into that customer base.

MoonPay's acquisition of Entendre provides a finance example. Entendre automates reconciliation, bookkeeping, treasury, reporting and financial close for companies dealing with digital assets.

These businesses have something general-purpose AI companies often lack: they already understand the workflow, terminology, integrations and constraints of one industry. In regulated areas such as healthcare and finance, those advantages can become especially expensive for a buyer to recreate internally.

Does an AI app need its own model to get acquired?

No. Owning a proprietary model can help, but recent acquisitions show that buyers frequently care more about the workflow, customers and data surrounding the model.

Fin does have purpose-built models for customer service, which Salesforce highlighted in its acquisition. Other important transactions look very different. Common Room connects information from existing customer systems. StackAI helps companies orchestrate agents across enterprise data and software. Fathom captures meetings. Portkey governs interactions with multiple model providers.

An application can therefore rely heavily on models built elsewhere and still become strategically valuable.

The harder question is what remains unique once every competitor can access comparable foundation models. Recent deals keep pointing to the same answers: proprietary customer context, deep integrations, an established distribution channel, trusted industry positioning and a workflow people use constantly.

Are generic AI wrappers actually getting acquired?

Generic AI wrappers currently have a much weaker acquisition case unless they have already built a real business around the underlying model.

Acquire.com's recent guidance to sellers reflects the change clearly. The marketplace says buyers now scrutinize whether AI products are actually defensible because software has become much faster and cheaper to build. Buyers increasingly want retention, recurring cash flow and some reason the product will remain difficult to replace.

A survey by Software Equity Group found the same fear among more than 200 private-equity investors, strategic acquirers and SaaS executives: 85% named AI-driven commoditization as the biggest risk facing SaaS companies.

The contrast with successful acquisitions is useful. Fathom has a meeting habit and a large customer footprint. GPTZero reportedly reached around $30 million ARR and 19 million registered users. Windsurf had $82 million ARR. Fin had more than 30,000 business customers.

For an AI wrapper, access to a good model may help create the first version of the product. Buyers now want evidence that something valuable accumulated after that first version.

Do AI apps need huge revenue before they get acquired?

AI apps can get acquired well before reaching large revenue, although the reason for the acquisition changes dramatically with scale.

Some companies are bought mainly for technology and people. Anthropic acquired Vercept for computer-use technology, and Vercept's existing product was scheduled to close afterward. Harvey acquired the team behind Hexus with a strong emphasis on engineering and enterprise-product expertise.

Other acquisitions look much more like purchases of mature software businesses. Windsurf had $82 million ARR when Cognition bought it. GPTZero was reportedly around $30 million ARR when Superhuman agreed to acquire it. ConnectAndSell had $14.7 million in annual revenue. Fin brought more than 30,000 business customers.

There are two distinct markets operating at the same time. Strategic capability deals can happen extremely early. Acquisitions based on the economics of the business demand far stronger commercial proof.

Type of AI acquisition	What usually needs to exist	Typical rationale
Talent/capability deal	Strong team or unusual technology	Acquire expertise quickly
Strategic product deal	Useful workflow and integrations	Fill a gap in a larger platform
Growth-company acquisition	Strong adoption and revenue growth	Gain a scaled product and customers
Small SaaS acquisition	Reliable profit and low owner dependence	Buy cash flow and operate the business

Does profitability matter for smaller AI apps?

Profitability matters a lot for smaller AI apps because buyers at that end of the market are currently underwriting cash flow rather than AI hype.

Acquire.com's latest closed-deal analysis covered more than 136 transactions with reported multiples and sale prices. The standard range was about three to five times annual net income. Businesses producing less than $100,000 of annual net income averaged around 3.7 times profit, while businesses between $100,000 and $1 million averaged about 3.9 times.

Acquire.com also says nearly all acquisitions currently closing on its marketplace involve profitable companies. Buyers are looking closely at margins, year-over-year growth, operational independence and the likelihood that earnings survive after the founder leaves.

This gives smaller AI founders a very different route to an exit than the venture-backed examples dominating the headlines. A modest AI SaaS generating reliable profit may be easier to sell than a fast-growing product with weak retention and large operating losses.

Acquire.com closed-deal evidence	Recent level
Typical transaction range	3–5× net income
Under $100k annual net income	3.7× average
$100k–$1m annual net income	3.9× average
Typical time on market	80–90 days
Buyer priority	Cash flow first

Are buyers purchasing AI apps for their technology or their customers?

Customer distribution is showing up again and again as one of the hardest assets for AI acquirers to reproduce.

Salesforce has enough engineering capacity to build more customer-support AI, yet acquiring Fin immediately added more than 30,000 company customers and an established support product. Cognition already had Devin when it bought Windsurf, but Windsurf contributed hundreds of thousands of daily users and more than 350 enterprise customers.

Sword Health already had sophisticated digital-health technology before buying Kaia Health. Kaia added members, payer relationships and reimbursement access. Superhuman could build meeting summarization internally, while Fathom already had adoption across hundreds of thousands of companies.

Even much smaller deals show the pattern. Pipedrive acquired Outfunnel after the product had become the highest-rated app in Pipedrive's own marketplace and was being used by more than 500 companies.

Distribution has become especially valuable in AI because the underlying technical capabilities are spreading quickly. A functioning product with customers who already trust it can save an acquirer years of go-to-market work.

Why are so many standalone AI apps ending up inside larger software suites?

Standalone AI apps are increasingly being absorbed into larger suites because combining several sources of customer context makes the resulting AI much more useful.

Zoom can connect Common Room's buyer intelligence with meetings, conversations, outreach and forecasting. Salesforce can connect Fin's support automation with CRM records, customer data and Agentforce. Asana can connect StackAI agents with work-management data. Superhuman can combine meetings from Fathom with email, writing and documents.

These combinations create a strong incentive to consolidate apps that previously operated separately. A sales agent performs better when it can see product usage and CRM activity. A support agent becomes more useful when it can read customer history and trigger actions elsewhere. A productivity assistant improves when it knows what happened in both email and meetings.

This is one of the deeper forces behind AI app acquisitions right now. The acquired company may be perfectly viable on its own, yet its data and workflow can become more valuable inside a platform that already owns adjacent context.

Are consumer AI apps getting acquired too?

Consumer AI apps are getting acquired, although the pattern is far less consistent than in enterprise workflow software.

Cognition's acquisition of Poke gives us one useful example. Poke is a personal AI agent built around messaging, and Cognition said users had exchanged more than 100 million messages with it within three months. The attraction was partly the way people interacted with the product: conversational, proactive and persistent over time.

Consumer-facing acquisitions become easier to understand when the product has unusually strong engagement, subscriptions or another asset beyond raw downloads. Grab's acquisition of Stash illustrates the economics from fintech: Stash had more than one million paying subscribers, around $5 billion in assets under management and positive adjusted EBITDA and cash flow.

What we see much less often today is the purchase of interchangeable consumer chatbot interfaces solely because they reached a large download number.

Enterprise AI remains the cleaner acquisition market because buyers can attach value directly to revenue, workflows, customer contracts and cost savings.

Are acqui-hires making the AI acquisition boom look bigger than it really is?

Yes. Talent and licensing deals inflate the headline number of AI acquisitions and need to be separated from real purchases of operating apps.

Windsurf provides the most dramatic illustration. Before Cognition acquired the remaining business, Google entered a roughly $2.4 billion licensing and hiring arrangement that brought Windsurf's CEO, co-founder and key researchers to Google. Cognition later purchased the product, intellectual property and remaining team.

Anthropic's Vercept acquisition also leaned heavily toward technology and talent because the existing consumer product was scheduled to shut down. Harvey's Hexus deal similarly focused on bringing the team into Harvey.

CB Insights found that AI companies acquired by Big Tech in the first quarter of 2026 were only 4.5 years old on average, compared with 7.6 years for AI acquisition targets overall. That gap fits what we see in individual transactions: large technology companies are prepared to buy expertise long before a startup looks like a conventional mature SaaS company.

So the record AI M&A totals are real, but they should never be read as evidence that hundreds of ordinary AI apps are finding buyers every quarter.

What makes an AI app especially attractive to a strategic buyer?

The strongest AI acquisition targets currently fill a specific hole in a buyer's existing product rather than merely offering impressive technology.

Zoom had meetings and communications but lacked Common Room's cross-channel buyer intelligence. Superhuman had email and documents but wanted Fathom's meeting context. ModMed already served medical practices and added Bonsai's patient-reengagement workflow. MoonPay already handled digital-asset infrastructure and added Entendre's finance-operations layer.

The recurring question for a strategic buyer is fairly simple: does this acquisition let us offer something meaningfully better to customers we already have?

Apps score especially well when the missing capability would take years to reproduce because it includes integrations, customer trust, specialist data or an established user habit.

That is why relatively narrow AI products can become attractive targets. They do not have to become giant standalone platforms first. They need to own a piece of the workflow that somebody larger wants badly enough.

Which AI apps are most likely to keep getting acquired?

AI apps tied to real business workflows are the clearest acquisition targets today, while generic model wrappers are facing a much tougher market.

The strongest recurring categories are customer support, coding, sales intelligence, productivity and meetings, enterprise agents, AI security, finance automation and specialized vertical software such as healthcare.

Across the deals we reviewed, five characteristics appear repeatedly: the app already has customers, sits directly inside a useful workflow, holds context or data the buyer wants, connects deeply with other software, and produces an outcome a business can measure.

Revenue changes the route rather than the basic logic. A strategic buyer may acquire a young company mainly for technology. A company such as Windsurf can attract a buyer after reaching tens of millions in ARR. At the smaller end, Acquire.com's data shows profitable SaaS businesses currently clearing at roughly three to five times annual net income.

The weakest position today is a product whose main advantage can disappear as soon as another developer gets access to the same model capability.

The apps being acquired now have usually accumulated something harder to regenerate: customers, workflow ownership, proprietary context, industry access, trust or cash flow. That is the clearest line running through the current AI acquisition market.