Labs64 GmbH

Software licensing is no longer just about generating and validating license keys. For modern ISVs, SaaS vendors, IoT platforms, fintech products, and AI-powered applications, licensing becomes part of the core business infrastructure: monetization, entitlement control, usage tracking, customer access, compliance, and automation. That is exactly where Labs64 NetLicensing is positioned. With 15+ years of production maturity, NetLicensing helps software vendors manage flexible licensing models across real-world enterprise environments. What makes it different? 🔶 Proven maturity 15+ years in production across ISV, SaaS, IoT, fintech, and enterprise software environments 🔶 Flexible licensing models 10+ models including subscription, metered usage, floating, offline, trial, quotas, and hybrid setups 🔶 API-first ecosystem REST APIs, OpenAPI contracts, SDKs, webhooks, MCP server, and agentic integration readiness 🔶 More than a license server Part of the Labs64.IO ecosystem with IAM, Audit Trail, Payment Gateway, Tokenization, and SaaS building blocks 🔶 Enterprise support SLA, priority support, managed operations, and architecture reviews for serious production use cases Licensing is becoming an important layer of SaaS and AI product architecture. NetLicensing gives teams the foundation to launch, operate, and scale licensing without building it all from scratch. #NetLicensing #LicensingAsAService #SaaS #SoftwareLicensing #EntitlementManagement #ISV #SoftwareMonetization #Labs64 #AgenticAI

Licensing platforms that don’t support metered entitlements will slow down your SaaS and AI roadmap. Most tools still think in on/off features. But today’s products run on usage: API calls, AI tokens (input/output), seats-hours, credits. If metering isn’t built into your licensing layer, you end up with messy token limits in gateways, services, and billing reports. Labs64 NetLicensing was built for this: flexible models, pay‑per‑use, and clean metering of things like AI token usage, wired straight into your product and billing 🤖 https://lnkd.in/ejjmWYb If you’re moving to token-based AI pricing, is your licensing stack ready for it?! #SaaS #AI #Licensing #NetLicensing #UsageBasedPricing #MeteredEntitlements #SaaSMonetization #AIProducts #TokenBasedPricing #Meetering

Everyone wants to be AI-first. Almost no one wants to fix the foundations. AI agents. LLMs. MCPs. A2A everywhere. Because that’s what everyone is talking about. CEOs push the “AI-first” narrative. More demos. More prototypes. More speed. Impressive on the surface. But what stands out to me is what’s missing underneath. Data quality. Culture. Skills. Clear ownership. The invisible layer. And nobody pays attention to what they can’t see… until it breaks. That’s usually when the polished POCs fail in production. The shift here is fundamental. AI doesn’t fail at the top. It fails because the foundation was never finished. This is where things change. Foundations aren’t boring work. They’re the only reason anything above them stays standing. So here’s the real question: Are you building AI for visibility… or building something that can actually last? #ArtificialIntelligence #AI #AITransformation #Leadership #FutureOfWork #Innovation

The "AI will kill SaaS" narrative has a fundamental problem. It treats SaaS as if it were one thing. It isn't. SaaS is a delivery and business model — not a product category. When people say AI will kill it, they're actually asking two very different questions: - Will AI change how enterprise software is delivered and priced? Probably yes. Consumption-based models and agent-driven interfaces are already reshaping that layer. - Will AI eliminate the need for the applications themselves? This is where the argument gets sloppy. After nearly four decades watching technology markets get called wrong at the moment of maximum noise — the mainframe, client-server, on-premises — I've learned to treat peak disruption panic as a signal. Not to ignore the threat. But to ask a more precise question. The survivability of any enterprise software company right now comes down to one thing: what kind of moat have they built? Horizontal workflow tools with no proprietary data and no network effects? Harder road. Vertical data powerhouses sitting on irreplaceable industry-specific data? AI doesn't threaten that moat — it deepens it. Systems of record embedded in compliance and governance workflows? These don't get replaced by systems that might hallucinate. And if SaaS is really being disrupted — where is the revenue going? We don't have a clear winner outside the existing ecosystem yet - and may not for a while. I've written up the full framework in my latest Substack https://lnkd.in/em46CNNW. The question isn't will AI kill SaaS. It's which SaaS companies built something worth keeping. [Link also in comments]

Only 9,000 VCs are active in the world. Out of 300,000 investors ever registered globally—only 200,000 are still active. And just 9,000 are venture capital firms: ➜ 35% are in the US ➜ 15% in Europe ➜ 9% in China ➜ 5% in the UK ➜ 4% in India — Here’s the full breakdown (active): ➜ 150,000+ Angels ➜ 9,000 Venture Capital Firms ➜ 2,500 PE Firms ➜ 500 Syndicates ➜ 350 Family Offices ➜ 50 CVCs — So here’s the punchline: The TAM for your startup’s fundraising is tiny. And it gets even smaller if: ➜ You’re not incorporated in the US/Europe ➜ You don’t have local operations ➜ You’re not building in a hot market ➜ You don’t have US/EU customer traction It’s not all about having the best pitch deck or warm intros. It’s about proximity. Proximity to capital. Proximity to markets. Proximity to narrative.

AI is changing how software is built, delivered, and consumed. Licensing must evolve at the same pace. Modern licensing for AI-driven products means 🔸 Usage-based and value-based models instead of static licenses 🔸 Real-time enforcement across cloud, SaaS, and on-prem environments 🔸 Seamless integration with AI services, APIs, data pipelines, and #AI #Agents 🔸 Full transparency, auditability, and compliance by design 🔸 Scalability from startup MVPs to global enterprise platforms The new AI era needs #licensing that is flexible, secure, and automation-ready. Licensing should enable innovation, not slow it down.