Tech Industry Acquisitions

Everyone's obsessed with AI models. Smart money is buying something else. News about Salesforce buying Informatica for $8B made me research the data management space. Informatica cleans, governs, and ensures data quality. A critical piece that makes AI application reliable. Speaking to senior leaders about their AI initiatives, the data topic keeps coming up. AI is only as smart as the data you feed it. And right now, enterprise data is a disaster. Most companies operate like this: Customer data sits in Salesforce. Financial data lives in SAP. Marketing runs through Adobe. Product analytics in Mixpanel. Each system speaks a different language. None talk to each other properly. When they try to build AI applications on this mess, it fails. The AI makes bad predictions, gives wrong answers, and leaders lose trust. 80% of AI projects never make it to production. The reason: poor data infrastructure. What we're witnessing mirrors the railroad wars of the 1860s. Back then, whoever controlled the rails controlled commerce. Towns lived or died based on railway access. Fortunes were made not by producing goods, but by owning the infrastructure that moved them. Today's rails are data pipelines. And two competing visions are fighting for dominance: The Integrated Stack Players (Private Railways): Microsoft ($3T): Azure + Dynamics + OpenAI partnership Oracle ($500B): Database to applications to cloud Google ($2.3T): BigQuery to Vertex AI Salesforce ($210B): MuleSoft + Informatica These players want to own your entire journey. From data creation to AI outcomes. Like the railroad monopolies, they promise efficiency but want lock-in. The Open Ecosystem Players (Public Railways): Databricks ($62B): Betting on open standards Snowflake ($50B): Independent data cloud for everyone Elastic ($8B): Search and analytics across any platform Confluent ($7B): Real-time data streaming for all These players are betting on interconnection. Like public railways that any business could use, they promise freedom but require you to manage complexity. Consider what happened with cloud computing. AWS started open, then slowly made leaving more expensive. Enterprises learned that lesson. Many now insist on multi-cloud strategies. We could see similar hybrid strategies playing out. For smaller companies not yet trapped in this mess, two urgent actions: First, audit your data now. Count how many systems hold critical data. Map which ones connect. The mess compounds daily. Second, invest in data quality immediately. Whether you choose Salesforce or Snowflake, clean data is what makes AI work. Dirty data breaks everything. In the railroad era, smart leaders didn't just bet on faster trains. They secured the best routes. Today, the way to do that is with better data infrastructure. It's your foundational competitive advantage. Don't get distracted by shiny AI models. Invest in your rails first. Your company's competitive edge depends on it.

Five recent mergers and acquisitions highlight how cybersecurity vendors are converging technology with services to capitalize on the US$10 billion MDR opportunity, which Canalys (now part of Omdia) is forecasting to grow 16% in 2025: • Sophos’ US$849 million purchase of Secureworks, which closed in February, giving it 2,000 enterprise accounts, and expanding MDR with XDR and SIEM assets, and DFIR and advisory services. • Arctic Wolf’s US$160 million purchase of Cylance Inc., which also closed in February, giving the MDR provider EDR and AI assets, and a customer base to migrate. • The merger between Cybereason and Trustwave, announced in November, bringing together Cybereason’s EDR with Trustwave’s MDR, DFIR and consulting. • WatchGuard Technologies’s purchase of ActZero for an undisclosed sum in December, which expands its existing MDR offering with automated threat response and third-party integrations. • N-able’s US$266 million acquisition of its XDR/MDR tech partner Adlumin in November. This is a highly competitive market with others like Alert Logic (acquired by Fortra), Bitdefender, Check Point Software (aquired rmsource), CrowdStrike, eSentire, OpenText (acquired Pillr), ReliaQuest, SonicWall (acquired Solutions Granted), ThreatLocker and Trend Micro and many more scaling offerings. The path to MDR emerging as a category has been gradual, yet inevitable. On the demand side of the equation is the threat landscape. More attackers are targeting smaller and midsized organizations that have less cybersecurity resources. On the cybersecurity supply side of the equation, the widening skills gap and growing complexity. Moreover, businesses need help securing their environments, and technology alone cannot fill the gap. The recent acquisitions highlight the direction of MDR services. For SMBs, scalable, low-touch, and automated services that go beyond managed EDR with poorly defined response services to managed XDR and risk management services, compliant with cyber insurance. For larger customers, more tailored offerings, with broader integrations, custom playbooks, threat hunting, and extensive DFIR. As a result, there will be more M&A between cybersecurity vendors and MDR providers. However, more than 90% of cybersecurity spending is to, through and with partners. Invariably, vendors will increasingly find themselves competing with their partners. The most successful vendors will be those that take a partner-first approach, enabling those that just want to resell or refer to do so without friction, and enabling more service-led partner to co-sell and co-deliver.

Tech M&A is heating up, with 2025 on pace to match or beat previous annual highs for aggregate deal valuation as AI and $100M+ deals drive momentum. At the top, it's an arms race among giants. Meta broke its two-year acquisition drought to grab TWO voice AI startups. NVIDIA bought CentML for $400M. Apple's CEO signaled openness to large M&A for the first time in company history. For others, this isn't just about adding features anymore; it's about survival. With AI threatening to obsolete entire business models, companies are buying their way out of irrelevance. The incumbents have heard the death knell, and they're buying the bell ringers. The numbers tell the story: ↳Public SaaS acquisitions of AI startups will more than double YoY in 2025 ↳By year-end, they'll surpass 2022, 2023, and 2024 combined ↳AI startups are exiting 6 years faster than peers Can incumbents buy their way out of disruption? With deal sizes nearly doubling, companies are betting everything on yes. The other side of the M&A boom sees a PE roll-up renaissance. Private equity is salivating over the flood of companies that raised in 2021. They see complementary products ripe for bundling, overlapping costs ready for elimination, distressed assets, opportunity to create super-platforms, and of course, the opportunity to make everything "AI-first". The punchline: Whether it's strategics buying innovation or PE rolling up the wounded, tech M&A's new wave is just getting started.

Seems like the End-of-Season Sale in Data Land and enterprise players brought their wallets. 🛍️ Yesterday, Snowflake bought Crunchy Data for $250m. Days ago, Databricks bought Neon for $1b. Last week, Salesforce bought Informatica for $8b. Week before, ServiceNow bought data.world. That's nearly $10B in infrastructure M&A in 4 weeks. So what did we learn? ⚠️ Spoiler: all AI roads lead back to data. 🛠 Postgres, but Make It AI The idea is that AI agents are going to do things. They’re not just going to generate text; they’ll take actions, update systems, remember things. That means they need infrastructure that doesn’t just store data passively, but participates in workflows. Enter: Postgres, long the Swiss Army knife of databases - now making a comeback as AI’s new memory layer. ▪️Databricks bought Neon, which is Postgres but ephemeral, serverless, API-based and mostly used by other computers. That is: it’s Postgres for when your AI agent wants to create a database, use it for 12 seconds, and delete it before lunch. ▪️Snowflake bought Crunchy Data, which is Postgres but rugged, enterprise-grade, DoD-hardened, for when your AI agent is acting on behalf of a regulated healthcare company and someone somewhere has to audit it six months later. So yes, both are Postgres. But also, one is a trampoline, and the other is a tank. What unites them: the shift from dashboards and batch jobs to autonomous, read/write, real-time systems - built not just for humans, but for agents.  🧠 Metadata Is the New Moat Meanwhile, up in the application layer - where agents are expected to resolve tickets, update CRMs, and route workflows - the problem isn’t memory. It’s meaning. AI agents can pull data. But can they understand it? Can they tell whether two customer records are the same person? Whether an SLA has been breached? Whether an approval is missing? To do that, they need context. And that’s what these deals deliver. ▪️Informatica gives Salesforce deep trust infrastructure - lineage, MDM, governance - so agents don’t hallucinate financial statements. For when your AI agent needs to know who a customer is, what their name is, and whether that name has legal implications in Luxembourg. ▪️data.world gives ServiceNow a semantic layer - knowledge graphs that help agents infer relationships, not just fields. For when your AI agent needs to escape the infinite loop of IT ticket escalation. These meta-data plays are moves to own the semantic scaffolding agents need to operate with alignment, not just intelligence. The model layer is flattening. Everyone has an LLM. The differentiation now lies in: what the agent knows, what it can do, and what it’s allowed to touch. These acquisitions go beyond building intelligence, they're about building the container that intelligence runs inside without breaking things. 📦

🚨 Stripe just made its THIRD crypto acquisition: Valora. Maker of crypto wallets. This is firmly an acqui-hire. The war for stablecoin talent is just starting. Stripe's previous acquisitions were about building blocks - Bridge ($1.1B) for stablecoin orchestration - Privy for embedded wallet infrastructure (75M+ accounts) This one is about talent and experience Valora's team have mobile-first emerging markets expertise --- The talent math is brutal right now. Heads of stablecoin strategy command $250-400k base salaries. One recruiter estimated 80% of his placements in recent months were stablecoin-related. --- Jackie Bona, Valora's CEO, brings 15 years of go-to-market experience from Google, Twitter, Spotify. Her team built for the hardest payments corridors: - Philippines - Nigeria - Argentina. Places where traditional finance fails and stablecoins actually solve problems. But also places that are hard to build for and where local knowledge matters. [Disclosure: I work for Tempo; Stripe is an investor in Tempo]

Crypto firm Ripple just offered $10Bn (a previous $5Bn offer was rejected) to acquire Circle, the issuer of the USDC stablecoin. What are the potential benefits and drawbacks of such a union for both these crypto powerhouses? 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐟𝐨𝐫 𝐑𝐢𝐩𝐩𝐥𝐞: ➕ Instant Stablecoin Scale: Gives Ripple control of USDC, the second-largest stablecoin with a $61.7Bn market cap, instantly making Ripple a dominant stabelcoin player. ➕ Regulatory Legitimacy: Circle's strong regulatory relationships would boost Ripple’s profile with regulators and institutions, especially after its own legal battles with the SEC. ➕ Payments Synergy: Potential for a powerful, all-in-one payment and liquidity ecosystem, combining Ripple’s cross-border infrastructure with USDC’s stablecoin utility. ➕ Competitive Edge: By consolidating client bases and technology, Ripple can better compete against other stablecoin giants and expand its reach in traditional finance. 𝐃𝐢𝐬𝐚𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞𝐬 𝐟𝐨𝐫 𝐑𝐢𝐩𝐩𝐥𝐞: ➖ High Cost and Integration Risk: Merging two large and very different organizations with some overlapping products, would be highly expensive and complex. ➖ Regulatory Scrutiny: Would likely attract intense regulatory attention, potentially delaying or derailing the deal. ➖ Potential Backlash: Centralizing stablecoin power under Ripple could alienate the decentralization believers in the crypto community. 𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐟𝐨𝐫 𝐂𝐢𝐫𝐜𝐥𝐞: ➕ Capital Injection: Provides Circle with significant capital for global expansion, R&D, and deeper partnerships, especially in emerging markets. ➕ Operational Maturity: Can leverage Ripple’s operational expertise and infrastructure to streamline its own business, and potentially renegotiate costly revenue-sharing agreements (such as with Coinbase), improving profit margins. ➕ Faster Global Expansion: Ripple’s established network and resources can accelerate Circle’s overseas ambitions and product development. 𝐃𝐢𝐬𝐚𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞𝐬 𝐟𝐨𝐫 𝐂𝐢𝐫𝐜𝐥𝐞: ➖ Loss of Independence: Circle would lose the autonomy to pursue its own vision of becoming a foundational payments player. ➖ Uncertain Strategic Fit: Ripple’s focus has historically been on cross-border payments not stablecoins. Circle’s plans may conflict with Ripple's priorities. ➖ IPO Opportunity Cost: The offer undervalues Circle, which believes it can achieve a higher valuation through an IPO. A Ripple–Circle merger would create a stablecoin powerhouse and reshape the digital payments landscape, but also contains significant financial, strategic, and regulatory risks for both sides. We'll have to see if there's any offer Circle would agree to. 🤔 #crypto #blockchain #web3 #ripple #circle

📣 Salesforce + Informatica just turned the platform into the most complete AI operating system for the enterprise.  For years, companies have been buying “AI” without fixing the hard problems underneath. Most organisations still struggle with three things:  ❌ Fragmented systems  ❌ Untrusted or poorly governed data  ❌ AI that works in demos, but collapses in real workflows Salesforce now owns the only stack where all three layers work as one:  • MuleSoft → Integration  • Informatica → Data governance + quality  • Agentforce → Autonomous AI execution This matters because real enterprise AI isn’t about chatbots or copilots.  It’s about AI that can reason, act, and take responsibility across business processes safely. What this unlocks for enterprises:   1️⃣ A unified digital nervous system:   Every event, signal, record, and workflow becomes machine-readable and immediately actionable. No stitching. No fragile automation. No “integration spaghetti.” 2️⃣ Trusted data becomes the default  Cleanliness, lineage, policies, MDM, observability, and governance, all applied before AI ever touches the data. That’s how you get audit-ready AI decisions instead of hallucinations. 3️⃣ Real AI agents not copilots pretending to be agents  Most “AI agents” today can only reply to text.  With this stack, agents can:  • Start workflows  • Update systems  • Trigger transactions  • Coordinate between apps  • Enforce policy and controls as they act   This is the first enterprise platform where AI doesn’t just generate an answer. It carries the action all the way into the systems that run your business.    4️⃣ A single metadata layer across the enterprise:   This is the piece most leaders underestimate. Metadata is the context AI needs to be useful.   Salesforce now owns end-to-end metadata:   → APIs, data lineage, relationships, rules, identity, and usage patterns.   → That’s the foundation for explainable AI, governed automation, and cross-system intelligence. 5️⃣ A composable enterprise ready for 2026 and beyond:   The next competitive edge won’t come from apps. It’ll come from AI that can safely orchestrate processes across applications. Salesforce is positioning itself as the OS that runs that future. My take?  This is no longer about CRM, integration, or analytics.  It’s the architecture for autonomous enterprises.  MuleSoft brings the connectivity  Informatica brings the trust  Agentforce brings the intelligence If you’re shaping your 2026 roadmap, this is the moment to rethink:  • how your data flows  • how trust is enforced  • how AI will act across your systems  Because the companies that get this right won’t just automate tasks, they’ll redesign how their business works.   Why this is a game-changing move:    ✅ Slack brought the interface.   ✅ MuleSoft brought the integration.   ✅ Tableau brought the insight.   ✅ Convergence will smooth autonomous execution.   ✅ Informatica now brings the data backbone.  MuleSoft Community

Met Yat Siu recently. Brief, straightforward insight rather than hype. Animoca Brands is in the process of going public on Nasdaq via a proposed reverse merger with Nasdaq-listed CURRENC Group Inc. (Nasdaq: CURR), targeting a closing in 2026. Under the current term sheet, Animoca shareholders would own ~95% of the combined entity and the merged company is expected to operate under the Animoca Brands name once completed. This structure allows Animoca to access U.S. public markets without a traditional IPO, leveraging CurrenC’s existing listing while avoiding the time-intensive regulatory and underwriting process. From a structural perspective, the proposed merger has three key implications 1. Public Market Access: Animoca regains a U.S. listing after being delisted from the ASX in 2020, providing broader capital access. 2. Shareholder Control: The deal is designed so existing Animoca shareholders retain dominant equity (~95%), preserving valuation leverage. 3. Diversified Exposure: The combined entity is positioned as a public digital asset conglomerate spanning gaming, DeFi, AI, RWA tokenization, and infrastructure, rather than a single product company. One practical detail Yat mentioned in passing (not a quote, but observable in how he works), his calendar is built around execution and coordination, not appearances, meeting partners, capital allocators, regulators, and ecosystem operators across regions. That operational discipline matters in deals of this complexity. For anyone tracking crypto capital formation and structural evolution, this isn’t about FOMO, it’s about how a blockchain investment vehicle intersects with public markets infrastructure

Salesforce announces purchase of Informatica to accelerate its move into an AI-first world 🌍 After talks fell apart for a $10B+ acquisition of Informatica in 2024, Salesforce is now acquiring the company for $8B, a 30% premium to Informatica's current market valuation. Salesforce was early in its realization that owning the data layer was going to be the scaffolding for the entire enterprise software stack, and this acquisition is the next big move in owning that. The real story is how this acquisition fits into their AI operating system strategy, especially around Data Cloud and Agentforce, Salesforce's fastest-growing segment at 120% YoY. Going a bit deeper: For AI agents to work safely and autonomously, you don’t just need more data. You need clean, contextualized data that comes with best-in-class access management and security. Guess where Informatica shines? Enterprise-grade data governance Master data management capabilities Deep pipelines into legacy systems and cloud environments Tools for unifying data across silos In its next act, Salesforce aims to go beyond being a system of record and deploy autonomous agents that act across workflows, including sales, service, and marketing. Doing that with trust and scale requires a real-time, governed, enterprise-wide data layer. There is an argument that this is the final piece of the stack: MuleSoft integrated systems. Tableau visualized them. Data Cloud centralized them. And now, Agentforce will act on them. Informatica will make those actions safe and reliable. While there will be tons of work between now and that vision becoming a reality, you can see a path to Salesforce becoming the first true enterprise AI operating system. Strong move #CRM!