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Working with and investing in early stage enterprise software companies at Aspenwood…
Articles by Lars
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The Series “AI” Funding Gap
The Series “AI” Funding Gap
A few weeks back I was at the Bank of America technology and CIO event thanks to an invite from my friend, Tom…
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AI Data Governance - trust you need so you can scale revenue
AI Data Governance - trust you need so you can scale revenue
Over the past year, I’ve spent a lot of time talking with founders / execs about the pace of AI adoption inside the…
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Product Review for Salesforce CRM
Product Review for Salesforce CRM
What do you like best? I use SalesforceIQ (the RelateIQ product that they may have renamed again..
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Activity
13K followers
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Lars Leckie reposted thisLars Leckie reposted thisCanadian startups raised C$2.69 billion in the first half of 2026, up 17% over H1 2025. Early stage took 44% of it, C$1.18 billion across 68 deals. The line everyone will quote: U.S. investors participated in 28% of all Canadian venture deals, up year over year but still below the 2021 peak of 36.7%. Here is the number nobody reports. How many dollars did Canadian companies import from U.S. investors? CVCA counts deals by investor geography, not dollars. The closest proxy is their own syndicate analysis, and it is telling. In rounds under C$5 million, Canadian-only syndicates supply about 70% of the capital. In rounds above C$50 million, Canadian-only syndicates supply 12.7%, while Canadian and U.S. syndicates together supply 67.5%. Canada funds their own seed rounds, but it imports scale-up funds. That distinction matters more this week than last. DC just moved to 50% tariffs on Canadian autos, parts and steel. Ottawa is matching dollar for dollar starting September 8. Goods have a border. Capital, so far, does not. Participation rates tell you who showed up. Dollars tell you who is load-bearing. Canada should publish the second number. CC: Chris Albinson Lars Leckie #VentureCapital #Canada
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Lars Leckie reposted thisLars Leckie reposted thisToday, Astralis is live: runtime governance that controls how every model, agent, and system uses enterprise data, in real time. For six years we’ve argued that data governance controls belong in data infrastructure, not spreadsheets and static reviews. In the AI era, it's not even an argument anymore. This is the only way to build trust at scale. Built on Fides, the world's most adopted open-source governance ontology, Astralis gives regulated enterprises a way to leverage AI quickly and confidently, without trading ROI for risk. Here's what Astralis can do: ✅ Take AI risk assessments that used to take weeks and complete them in the flow of work, regulator-ready and audit-trailed ✅ Enforce data-use policy by purpose, not just role, at the exact moment a model, agent, or query reaches for data ✅ Produces a complete, machine-readable audit trail across every system data touches, without a human required at every step The New York Times, Ramp and Condé Nast already trust Ethyca to navigate global regulation. Astralis is our next evolution, built for an era where AI's ability to reach across data boundaries is exactly what makes it valuable, and exactly what makes it hard to govern. Runtime governance for empowered AI. Available now. https://fid.es/4xjF3Do
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Lars Leckie shared thisSo fabulous to see - congrats to the team at Ethyca for this milestone.Lars Leckie shared thisToday we’re releasing Astralis, an end-to-end platform for runtime data governance in the AI era. It’s built on our open-source ontology Fides, and it’s the end goal of six years’ work to make enterprise technology systems more trustworthy. In 2019, weeks after starting this company, we wrote an internal document with a vision of the future: the way enterprise did data governance - people filling in workflow tools to produce point-in-time reports for regulators - would collapse under the scale of the software it was meant to govern. The collapse is happening now, and AI is what caused it. The old compliance model assumed a person could stand between the rules and the data. AI removes the person, and acts at a speed and volume no team can review. So, governance does the only thing it can: say "no." It blocks access, stalls the AI initiative, and protects the company by preventing it from using its own data. In doing so, it blocks innovation. Meanwhile the business is asking, reasonably, why millions invested into AI initiatives aren't producing the expected outcomes. This can't be fixed by more people watching machines. The fix is machines watching machines, applying the company's actual policy at the moment data is used, everywhere. That's Astralis in one sentence. Its open-source foundation, Fides, already runs inside the New York Times, Condé Nast and Ramp. Here are things Astralis lets you do: - Impact assessments in real time: These prove to regulators your new data processing activity took consideration of user preferences and varied local regulations in advance. They’re an essential piece of governance frameworks, and they can take literally months for a large enterprise initiative. With Astralis, the same assessment can be completed in minutes, in the flow of work. The time and cost savings are staggering. - Purpose Based Access Control (PBAC): This ensures data is always available to business users and technologies, provided the intended purpose of use matches businesses policies and regulatory context. Enforcement runs in real time at every consumption point across the enterprise. You get the same policy across pipelines, agents, MCP servers, SQL clients, and users. I'm very grateful to the Ethyca team and our pilot partners who have led us to this moment. This is the one we've been building toward. If you want to check it out for yourself, feel free: https://lnkd.in/ePKiSRYN
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Lars Leckie reposted thisLars Leckie reposted thisGreat post from Linus on the Linux Kernel Mailing list on the use of AI. I wish all communities had this level of clarity. Sadly, may have not (e.g. Game Development).
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Lars Leckie shared thisWhat a special event - great to see the reception from the customers and early users.Lars Leckie shared thisLast night felt so special. We announced Sonora GA in a warm company of our early customers, advisors, investors and post-sales leaders who are navigating AI in post-sales. Watching the room at The Conservatory fill up was a moment Paul Friedman and I won't forget. Highlight of the night: the fireside on the future of post-sales with four operators who've actually done this work at scale. Ishmeet Singh, a close friend and CCO at MuleSoft. Michael Blank, COO at Retool, and someone we're working hard to win over. And two customers we're lucky to work with: Anna Prell, VP of CS at Ivo, and Vikas Dua, President & COO at Ocrolus. We'll be sharing the fireside video soon. Special thanks to Rod Cherkas for signing copies of REACH and sending everyone home with something to read. To everyone who came: you made it feel special. Photos below. This is day one. More to come. 🚀
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Lars Leckie shared thisLooking forward to celebrating at the launch party tonite - it’s been a fun journey so far and an impressive pace to watch the team move at….Lars Leckie shared thisToday we're announcing our $3.2M seed, led by Aspenwood Ventures 🎉 Those of you close to our journey know we actually raised this round in July last year. It didn't feel right to make a big deal out of it then. Raising capital wasn't the milestone we were ready to celebrate. Shipping was. One year ago, Sonora was two of us and a Notion doc. Today: GA product, over 1M agents deployed in the last six months, and customers like Merge, Ivo, and Ocrolus running their post-sales on Sonora. Sonora is an agentic revenue platform that runs your post-sales. The bet behind it: AI is collapsing specialized roles back into one. CS and account management are merging into a single person directing a fleet of agents across renewals, expansion, escalations, and health. Less grinding through work. More directing it. More on sonora.cx Huge thank you to Lars Leckie and the Aspenwood team for backing us when this was just an idea.
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Lars Leckie reposted thisExcited to moderate the fireside at Sonora's GA launch in SF on Jun 10th. If you run CS, Revops, Account Management and are in the Bay, come over.Lars Leckie reposted thisA year ago we set out to rebuild the GTM stack for post-sales. Today, we're weeks away from GA. To mark the occasion, we're throwing a big launch party on June 10 in San Francisco. Fireside with Michael Blank (COO, Retool), Anna Prell (VP CS, Ivo), and Vikas Dua (President & COO, Ocrolus) on the future of CS, moderated by Ishmeet Singh (CCO, MuleSoft). Rod Cherkas signing copies of REACH. Live demos, cocktails, and the team. If you lead CS, AM, or RevOps, join us. RSVP: https://luma.com/zgm3oh57
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Lars Leckie reposted thisLars Leckie reposted thisAt every AI governance conference I've been to in the last 18 months, the discussion gets to the same place, how to fill in a questionnaire. We're using manual questionnaires to evaluate technology meant to replace manual work, that’s an oxymoron. There's a better conversation worth having: * What data is the AI allowed to consume. * What policies travel with our data to enforce rights, regulations and commitments in real-time. * In short, what happens to reduce AI risk once an assessment is signed? Real AI governance at AI speed has to be engineered infrastructure, not just authored. If you'd rather talk about technical governance than faster assessment templates, DM here.
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Lars Leckie reposted thisExcited to join Sonora's GA launch in SF on June 10. On a panel with Anna Prell (Ivo) and Vikas Dua (Ocrolus), moderated by Ishmeet Singh (MuleSoft), on the rebuild happening across post-sales right now. @Sonora is tackling a real problem. Excited to be in the room for this one. If you lead CS, AM or RevOps in the Bay, come hang. RSVP: https://luma.com/zgm3oh57Lars Leckie reposted thisTwo weeks out to GA 🚀 Three operators who've run post-sales at scale, on one stage: Michael Blank (COO, Retool). Vikas Dua (President & COO, Ocrolus). Anna Prell (VP CS, Ivo). Ishmeet Singh (CCO, MuleSoft) moderating. If you lead CS, AM, or RevOps, this is the conversation to be in the room for. Plus: Rod Cherkas signing REACH, live demos, and the Sonora team showing what we've built. June 10, 6PM. The Conservatory, SF. Space is limited. RSVP before it fills up. https://luma.com/zgm3oh57
Lars Leckie commented on a post
1mo
best of luck on the new challenge....
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Lars Leckie liked thisLars Leckie liked thisEdition 25 of our WunderGraph Community Newsletter shares details on our upcoming conference talk with Alexandr Aniska, Principal Engineer at SoundCloud, plus more insights from our Router and People team. It may involve cake. See for yourself 🍰 👀
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Lars Leckie liked thisLars Leckie liked thisEnterprises have petabytes of customer data and all the AI models too. The gap today is a *harness* that will let them safely run their data through the models in ways that yield ROI for the business. Ethyca are operating at that fault line. When an AI model and your data are just thrown together, what comes out the other end is likely to be incomplete, of marginal value, and worst of all, unsafe/uncompliant to use. Regulators aren't going to let you do this for much longer. For several years after GDPR in Europe, there was a honeymoon period when every company was non-compliant, but the regulators were forgiving because they were giving them time to get their house in order. That time has come and gone now, as anyone who has seen the long list of legal cases and fines that have been racking up over the past couple of years knows. Again, the EU has led the way on this, but the enforcements are getting heavier in the US too. See the billion-dollar enforcements by Texas against Meta and Google, and this year alone, General Motors, Disney, Healthline Media and Sephora all hit with million-dollar-plus fines in the US. Throw AI into the mix (and a lot of companies are literally throwing AI into the mix) and you’ll find models everywhere ploughing through unimaginably large datasets with reams of unmapped PII. This creates a massive risk surface. Governance leaders are understandably doing what they can to stop this...in the form of putting the brakes on AI initiatives that could drive the business forward if governed properly. Even apart from regulation, if the data being used isn’t properly AI-ready, it just isn’t going to deliver any of the insights and innovation that was the entire business case for the AI investment in the first place. Variations of this are happening everywhere right now. Massive regulatory risk through improper or barely governed use of data, a lot of it delivering nowhere close to what those companies wanted. Astralis is the layer that sits between the AI model and your data. At Ethyca we’ve been working on this for seven years, and the moment has arrived to close this fault line once and for all. It’s the only way AI can actually deliver on its promise.
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Lars Leckie liked thisLars Leckie liked thisWe asked our customers one question: what problem does Sonora solve for you? Merge needed full observability into a large book of business. Ariya Patel, CSM, walked into a customer account on Sonora and saw it all in one place. No switching tabs. No reconstructing what happened six months ago. Ivo had calls full of signal and no system to capture it. Anna Prell now pulls insights from calls, emails, Slack, and product data into one place. No stitching things together in-house. Ocrolus was playing whack-a-mole with support tickets. Vikas Dua, President, and Mike Masters, VP of Account Management, wanted a holistic picture of how each customer is actually doing. Now their team spots trends instead of reacting to noise. Reza Shafii at Kong needed a direct line from product investments to ARR. Someone asked if his company had pharma accounts. He opened Slack, asked Sonora, and got the answer in front of the room. Different teams. Different challenges. Same shift: all the signals that matter live in different systems. Sonora brings them together into one view that's grounded, objective, and actually useful. Watch the full stories 👇
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Lars Leckie liked thisLars Leckie liked thisAI has a pricing problem: usage, cost and value no longer move together. Customers don’t care about tokens. They care about what they get and what they pay. Yet there’s no single pricing model for AI. Subscriptions, usage, credits, tiers and outcomes are all in play. The direction is hybrid: subscription + consumption by value. Credits can make complex AI consumption easier to buy. But what should you actually measure? Tokens? Actions? Workflows? Outcomes? The closer pricing gets to value, the more complex monetization becomes. There’s another problem: AI costs can move fast. By the time traditional billing detects excessive consumption, the cost may already be incurred. The result? Margin erosion, unexpected charges and AI bill shock. These problems aren’t entirely new. Telecom and cloud have spent years learning how to meter, control and monetize consumption in real time. What is new is the speed, scale and unpredictability of AI. There may never be one perfect AI pricing model. The winners will be those with the agility to keep changing how they package, price, control and monetize AI. Our latest article explores what that means for billing and what enterprises should demand to be AI-monetization ready. Read: “To Monetize AI, Enterprises Need to Rethink Their Billing Approach” → https://bit.ly/46muiob #Telecom #AIBilling #UsageBasedPricing #BillingForAI #AIMonetization #BSS
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Lars Leckie liked thisCongratulations to Jason Smith and the entire Klue team!Lars Leckie liked thisKlue is now a verified connector in Claude's directory. Inside Claude, sellers get real-time, cited answers on positioning, objections, and what to do next in deals that are live right now. PMMs can analyze win-loss patterns and competitive signals, research voice of buyer, and update Klue content directly without leaving the conversation. Proud that Klue is the only competitive intelligence and win-loss platform to earn that verified status from the Anthropic team. One step toward a bigger goal: Klue becoming the compete and buyer data engine every organization plugs into its LLMs. Customers, go take our MCP for a spin - would love to know what you're building!
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Lars Leckie liked thisLars Leckie liked thisJoin DefectDojo's Principal Solution Architect, Tracy Walker, this Wednesday for our next training webinar! On August 26 at 12PM ET / 9AM PT, Tracy will walk attendees through three ways AI and DefectDojo Pro work together: - The built-in DefectDojo MCP server which gives LLMs like Claude, ChatGPT, and Gemini secure, structured access to your findings data. - AI-generated custom report templates and dashboards built on the fly from your findings. - DefectDojo Sensei for auto-remediation with human-approved pull requests and AI threat modeling before a single line of code is written. Ready for a practical training that shows real AI use cases for security teams ready to move faster? Register here: https://buff.ly/QRCsYnV #VulnerabilityManagement #ASPM #Cybersecurity #DefectDojo #AIAI Use Cases with DefectDojo Pro: Maturing Vulnerability Management OvernightAI Use Cases with DefectDojo Pro: Maturing Vulnerability Management Overnight
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Lars Leckie liked thisLars Leckie liked thisIt’s quite cool and a bit frightening to watch Claude react when our platform tells it “no, you can’t use that data you want.” Safe to say Claude doesn’t take our directive lying down. It immediately starts scheming about how to potentially override the denial of request for data access by rephrasing its request. Cheeky Claude. Reading the LLM’s internal monologue when dealing with Purpose Based Access Control constraints is fun if you’re a geek like me, but it also shows how strong your technical foundation needs to be for doing AI governance at speed and scale. With Ethyca’s Fides ontology, company data policies live at row and column level in the warehouse. PBAC is then able to evaluate, decide, and enforce a decision on the data in that row or column at agent or model runtime. So in this case, once Claude was prompted and its gears started spinning, it went to try to pull data out of the warehouse and ran straight into Ethyca’s PBAC waggling its finger and saying “don’t touch”.Pretty cool! On the other hand, if you have a written document somewhere talking about how this or that database should or shouldn’t be used for different kinds of activities, well good luck. Claude is going to eat your data policy for lunch.
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Lars Leckie liked thisLars Leckie liked thisCanadian startups raised C$2.69 billion in the first half of 2026, up 17% over H1 2025. Early stage took 44% of it, C$1.18 billion across 68 deals. The line everyone will quote: U.S. investors participated in 28% of all Canadian venture deals, up year over year but still below the 2021 peak of 36.7%. Here is the number nobody reports. How many dollars did Canadian companies import from U.S. investors? CVCA counts deals by investor geography, not dollars. The closest proxy is their own syndicate analysis, and it is telling. In rounds under C$5 million, Canadian-only syndicates supply about 70% of the capital. In rounds above C$50 million, Canadian-only syndicates supply 12.7%, while Canadian and U.S. syndicates together supply 67.5%. Canada funds their own seed rounds, but it imports scale-up funds. That distinction matters more this week than last. DC just moved to 50% tariffs on Canadian autos, parts and steel. Ottawa is matching dollar for dollar starting September 8. Goods have a border. Capital, so far, does not. Participation rates tell you who showed up. Dollars tell you who is load-bearing. Canada should publish the second number. CC: Chris Albinson Lars Leckie #VentureCapital #Canada
Experience & Education
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System and method for land-leveling.
Issued US 6880643
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Adjustment of vehicle-implement trajectories to compensate for lateral implement offset
Issued US 6804587
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Rapid adjustment of trajectories for land vehicles
Issued US 6643576
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