all perspectives 2026

Baby, where the hell is my founder?

As brilliantly put by Raye, I've spent the last couple of months asking myself: "Baby, where the hell is my founder?" In a noisy early stage market, we are doubling down on human-first deal sourcing. 

Early stage investing is a bit messy these days. Company formations are surging with 2026 applications so far running 25.54% ahead of last year, and monthly formations now exceed a 435% jump from the monthly average in 2004. According to Carta, roughly 3,000 U.S. startups have already raised pre-seed capital in Q1 2026. The barrier to starting a company seems to have substantially been reduced.

And of course, most of these deals have something to do with AI, which intensifies the noise. Just a few years ago, AI startups received around 30% of all pre-seed dollars. By Q1 2026, they hit the 50% mark.

On the other hand, as we have written here before, the concentration of capital at the early stages is still strong. Only 11,672 SAFEs and convertible notes were issued in Q4 2025, a multi-year low, but dollar volume held steady at $2.62B, similar to recent quarters, meaning fewer rounds are happening at the same volume amount. More capital is concentrated into fewer perceived winners, creating a market where dozens of companies can look fundable at first glance, while true differentiation becomes harder to assess.

Add to that inflated early traction signals and you are in quite a jam. Building an MVP is cheaper and faster than it's ever been. Things look shiny at first, but when you look under the hood, you are often left uninspired. We are seeing more excitement and experimentation, but also more look-alike companies. We now routinely see dozens of near-identical businesses delivering $100K to $800K in ARR with a handful of customers within a few months, competing in the same space, making early traction a difficult signal for future success. The data is showing that as well. According to Carta, nearly half of all seed financings in Q1 2025 were bridge rounds rather than true progression rounds, while the median time between Series A and Series B stretched to a record 2.8 years. More companies are getting built, but fewer are breaking out.  

Don’t get me wrong: this is exciting. There has never been more experimentation. There has never been more company creation. But there has also never been more difficulty distinguishing durable insight from the noise.

In all the noise, serious founders building generational companies are becoming increasingly harder to find.

Some early stage investors seem to be adopting tools to find "pre-founders" coming out of "founder factories" and building increasingly elaborate automated outbound sequences sent to hundreds of founders who have no way to prioritize meeting requests. That approach is only making things worse, leading to AI-generated emails back and forth. 

At Laconia, we believe that investor-founder relationships remain personal. While we also take a proactive approach and do targeted, intentional manual outreach to founders who catch our eye (hello, to anyone who recently received a LI note from me out of the blue!), we have chosen to double down on our human-first strategy. Over the past decade, we have taken a grassroots approach to finding great founders early. Our “outside-in” approach drives us to invest our time in office hours, curated community events, educational initiatives, and programs like the Venture Cooperative. We also take cold inbound seriously through a structured intake and review process. 

True to Laconia’s values of transparency and accessibility, we believe that founders should understand us from afar. We’ve written openly about who we are, our investment philosophy and what entrepreneurs we want to back. More recently, we’ve shared how our thinking is evolving alongside the market.

So rather than adding another outbound sequence into the ecosystem, this is simply us putting up a signal flare for the founders we want to meet. If you see them, tell them they should holler.

Who we're looking for

Laconia invests in serious founders building must-have technologies in enduring industries. 

  • Investment Stage: Pre-seed and seed. Happy to meet very early in the company building process. 

  • Industry Sectors: Diversified, with companies spanning fintech, healthcare, retailtech, climate tech, proptech, and more. (We don’t typically invest in biotech, energy, military applications, hardware, or consumer tech)

  • Business Type: High-margin at scale, with capital-efficient market distribution; in practice, this tends to skew toward b2b software and companies with similar underlying attributes

  • Investment Size: $250,000 - $1 million checks

  • Geography: Primarily US and Canada, with openness to global companies entering the US market 

Our focus has stayed consistent for a decade: companies that bring systematic order to complex workflows, but what that may look like has evolved. In narrowing it down beyond the parameters above, these days, we get really excited about the following three things.

Serious builders, not bubble riders

We back smart founders who are building generational companies, not just riding the latest wave. The distinction matters now more than ever. In a market flooded with AI-enabled anything, we're looking for founders with earned insight who understand a workflow, customer, or market deeply enough to see something others don’t yet see.

Meaningful, venture-scale problems

We are looking for founders building meaningful and inspiring problems, leveraging deep expertise and a distinct entry point into a massive (often underestimated) opportunity. These companies could be vertical AI platforms with clear GTM wedges positioned between legacy incumbents and horizontal giants, or solutions for regulated industries like finance and healthcare where accuracy requirements, compliance frameworks, and workflow specificity demand more than general-purpose AI. 

Think tools helping miners explore uranium; platforms bridging the valley of death gap in medtech between FDA approval and full reimbursement; and companies solving the structural shortage in skilled nursing, and more. 

Structural defensibility

As Geri outlined in The Death of SaaS, in a time where building tech is fast and cheap, now more than ever, we are looking for companies that are thinking about their “structural defensibility” from day one. 

The default assumption can no longer be that software margins alone create defensibility. If a product can be replicated by a foundation model provider or absorbed into a horizontal platform roadmap, that risk has to be accounted for.

Defensibility can come in different forms: 1) “Software +” businesses: Software companies + human in the loop; or Software + services; 2) Companies that have clear data advantages/moats such as unique data collection, proprietary data access, or exclusive partnerships that create structural advantages that can't be easily replicated; 3) Distribution advantage or clear understanding of the workflows, change management and buying decisions of the customer and/or market. 

The archetype we love: a vertical-specific product that is specialized enough that hyperscalers can't match its domain expertise, and up against legacy incumbents too slow to deliver a modern product experience. To that, one should add structural defensibility in the form of distribution, data or tech+ Moat, and we are interested. 

What you should know about us

We run an efficient, transparent process, and we turn it on its head. First, instead of running a long due diligence process ending in an IC meeting, we prioritize a full investment team meeting early on. This helps us get to "no" as fast as possible when it's not right and only proceed to diligence when everyone is genuinely excited. Second, our due diligence includes a workshop that stress-tests the financial model, pipeline, and go-to-market strategy, giving us a view of how the founding team thinks. At the same time, founders get a glimpse of what working with us is like. Lastly, rather than contacting a company’s existing customers, who are already early believers taking risks by working with an early stage startup, we validate value propositions by activating our extensive network of prospective customers, experts, and co-investors, adding value whether or not we invest.

Our structured due diligence maintains the human element that is so key to Laconia’s core thesis. Our front-loaded fund construction and dedicated focus to pre-seed and seed investing align our incentives with founders and drive better outcomes between seed and series A. Over the past decade, 97% of our portfolio companies have successfully raised subsequent funding rounds, and over 70% of our portfolio companies are either still active or have completed successful exits. In a power law-driven world where investors often treat early stage investments as lottery tickets, we take founders’ life work seriously. And we are excited to partner with more founders with this promise in mind.


"If you see him, tell him —
he should holler."

— with apologies to Raye

If this sounds like you, and you’re looking for someone like us, we want to hear from you! 

Reach out directly here or apply here.

Portfolio Spotlight: Bluefish

We’re excited to announce that our portfolio company Bluefish has raised a $43M Series B co-led by Threshold Ventures and New Enterprise Associates (NEA), with participation from Laconia, American Express VenturesTIAASalesforce Ventures, Bloomberg Beta, Swift Ventures and Crane. This brings total funding to $68M.

We’ve worked with Bluefish from the earliest days, investing at pre-seed and previously backing CEO Alex Sherman and COO Jing Feng in their prior company PromoteIQ (acquired by Microsoft). From the start, the team was building toward a world where AI becomes a primary interface for how consumers discover and evaluate products.

Since launching in 2024, Bluefish has become a core platform for Fortune 500 brands building agentic marketing capabilities, already used by ~10% of the Fortune 500 across more than 15 industries.

As AI systems like ChatGPT, Google AI Overviews, Claude, Perplexity, and Amazon Rufus increasingly shape discovery, Bluefish provides a unified platform to monitor, influence, and measure how brands are represented. Its Agentic Marketing Platform connects insights to execution, helping teams improve performance with clear, measurable outcomes.

The company is led by Alex ShermanJing Feng, and Andrei Dunca, a team with a track record of building category-defining platforms.

At Laconia, we invest in founders building the infrastructure required for how markets are evolving. Bluefish is doing exactly that for enterprise marketing in an AI-driven world.

We’re proud to continue supporting the team as they scale and define this category.

Read more here.

Founder Spotlight: Baptiste Bouvier (Daptic)

Meet Baptiste Bouvier, Founder & CEO of Daptic.

Raised across Japan, Australia, and the UK by parents who built their own business from scratch, Baptiste developed an early appreciation for hard work, education, and global perspective, an experience that shaped how he approaches complex problems. That path led him to build Daptic after firsthand exposure to how regulatory bottlenecks slow product development, creating a platform that helps manufacturers navigate compliance and bring products to market faster.

The Death of SaaS

Over the past few months, public software stocks have experienced sharp corrections: the BVP Emerging Cloud Index (EMCLOUD) down 20-30%, with individual names dropping 20%+ on frontier model announcements from Anthropic and OpenAI. Investor communities are asking: “Has AI killed SaaS?”

Our view is that AI is accelerating a bifurcation that was already underway. Undifferentiated software products without defensible data, distribution, or domain expertise face compression. Meanwhile, specialized applications with tangible moats are using AI to compound their advantages. The companies that fail won't fail because AI exists; they'll fail because their solution wasn’t durable enough in the first place.

AI capabilities such as data synthesis, pattern recognition, and code generation deliver real productivity gains. But enterprise deployments, particularly in regulated industries, still require accuracy guarantees, workflow integration, and institutional trust that general-purpose platforms simply can't provide. This gap creates the opportunity.

At Laconia, we focus not on the capital-intensive infrastructure-building portion of AI (i.e. frontier AI labs) but instead on the capital-efficient, scalable, specialized software application and platform opportunities. These are the investments where we can repeatably identify high upside opportunities with structural entry points that fit our seed-focused strategy. As we enter 2026, we are reflecting on what opportunities emerge as a result of both the capabilities and the limitations of AI. What's different, what's the same, and where are the diamonds in the rough?

What's Different

Faster time-to-product expands and crowds the opportunity set. Building an MVP is cheaper and faster, making previously unviable niche products economically feasible. This increases total experimentation and, eventually, venture-scale opportunities. But it also means:

  • Supercharged competition: We see dozens of near-identical businesses, often with $100k-$800k in ARR, across a few to a few dozen customers, within a few months of incorporation. With this landscape, defensible differentiation and strategic vision matter much more than early traction or market signal.

  • "Execution plays" are dead, and companies need structural defensibility. There used to be a whole category of businesses with no long-term moat where it was not unreasonable for investors to bet that the founders would win simply through superior operational execution — better sales, faster shipping, stronger fundraising. AI makes this investment proposition untenable as competition for low-hanging fruit is lethal. Without a clear structural advantage that competitors can’t replicate – proprietary data sources, exclusive distribution partnerships, deep domain expertise in regulated industries, or multi-year technical moats – software companies face a race to the bottom on price. Pure operational execution remains necessary but insufficient. AI has made the distinction between "doing the same thing better" and "doing something others can't do" the line between viable and non-viable seed investments. Here are a few examples from our portfolio:

  • Ocrolus (Fund II): Human-in-the-loop verification combined with machine learning delivers near-perfect accuracy in financial document analysis. This operational moat can't be replicated with prompts alone. Interestingly enough, the “human-in-the-loop” element was one of the most frequent reasons that investors passed on Ocrolus in the early days, and it has proven to be one of its biggest advantages.

  • Messium (Fund III): Messium combines exclusive hyperspectral satellite imagery with multi-season ground-truth soil data and strong channel relationships. The data advantage and distribution are slow to replicate.

  • Every startup’s competitive set now includes hyperscalers. The evergreen VC cliché of "What if Google (or Microsoft, or OpenAI, or Anthropic) builds this?" is real now. Software startups are not just up against non-technical incumbents like publishers or taxi companies anymore; they are up against the most sophisticated and well-capitalized technology businesses in history. One archetype that works well is a vertical-specific product that is 1) specialized enough that larger tech platforms can't match relevant market expertise and 2) up against legacy incumbents that lack the technical capability to deliver a compelling product experience. Add an underrated market size and a go-to-market Trojan horse wedge that reduces existing vendor lock-in, and you might have a winner.

  • Business models are shifting. Pure subscription revenue is declining; usage-based, metered, or workflow-integrated pricing better aligns with AI value delivery.

  • "Software+" models are viable. When software was a bottleneck to product development, there was only so much that a company could tackle at once. AI lowers the software-building constraint, making targeted combinations of software + hardware or human-in-the-loop economically viable, assuming the unit economics trend toward software margins at scale.

What Hasn't Changed

  • Value accrues to solutions, not tech stacks. Lasting adoption requires clear ROI, workflow-native design, deep customer understanding, and product simplicity. If software businesses fail, it won't be because AI now exists – it'll be because they didn't get the experience right.

  • Teams drive outcomes. Judgment, speed of learning, rigorous processes, and leadership quality remain the key attributes that we seek.

  • Unit economics are non-negotiable. Gross margins, payback periods, and retention matter as much as ever.

  • Capital strategy shapes outcomes. Entry valuation, ownership, and fundraising trajectory must match not only the company’s operating needs but also each fund’s specific strategy. Not every good business is a good investment, and fund managers need to nail both.

Where We're Focused

Previously "too niche" opportunities are now viable at venture scale. Our focus areas include:

  • "Software+" models where AI makes hybrid approaches (software + physical data sources, software + human-in-the-loop) economically compelling, provided they trend toward software margins.

  • Proprietary data moats where multi-year data collection, proprietary data access, or exclusive partnerships create structural advantages that can't be easily replicated.

  • Regulated industries (finance, healthcare) where accuracy requirements, compliance frameworks, and workflow specificity demand more than general-purpose AI. Human-assisted verification remains necessary; specialized products that nail the workflow win.

Vertical-specific platforms positioned between legacy incumbents (technologically weak, often PE-owned, universally disliked) and horizontal tech giants (lack domain expertise). These startups have a wedge: legacy providers can't build modern tech, and platform companies don't understand the nuances. With a GTM-focused founding team and a thoughtful strategy, these can be winners.

If this resonates with what you’re building, we’d love to learn more. Email any of us directly or share your info here: bit.ly/laconiapitch

Geri Kirilova

Announcing Laconia’s Pitch Practice

At Laconia, we have always prioritized mentorship, accessibility, and education in our community-building efforts. Over the past decade, we have met thousands of founders one-on-one, at accelerators, through community office hours, and at events.

We are launching a new initiative to scale these efforts: Pitch Practice.

Pitch Practice is designed for B2B software founders who are gearing up to raise a pre-seed or seed round. Our investment team will set aside a few hours each month to host structured mock pitch sessions, with time reserved for direct, concrete feedback.

Format

Each session will be one hour and include two 30-minute pitches.

Each 30-minute slot will follow the same structure:

  • 15–20 minutes: pitch and discussion

  • 10–15 minutes: feedback

Sessions will be led by a member of Laconia’s investment team and held as a Zoom webinar.

One Additional Element

Our Venture Fellows will be invited to observe these sessions.

With the launch of Cohort 10 of the Venture Cooperative, our community now includes more than 1,700 Venture Fellows globally. Through this format, founders will not only meet with the Laconia team and receive candid feedback, but they will also gain visibility in front of a broader network of angel investors, operators, potential customers, and prospective hires.

Building a startup is difficult. We hope that members of our ecosystem may be able to support participating founders along the way.

Selection Criteria

We are currently accepting applications from companies that meet the following criteria:

Business Model: B2B software
Stage: Preparing to raise a pre-seed or seed round
Geography: Based in or commercially targeting the U.S. market
Sector: Agnostic (e.g., fintech, retail tech, proptech, healthcare)
Traction Requirements: None

Please note that we typically do not invest in biotech, life sciences, hardware, or cybersecurity.

Submission Process

To be considered for the first batch of sessions in late March, please submit the Google Form by:

March 15, 2026 at 11:59 pm ET

The form will request:

  • Company name

  • Website

  • Deck (optional)

  • Founder LinkedIn profiles

  • Elevator pitch (3–5 sentences)

  • Capital raised to date

  • Capital currently raising (or preparing to raise)

We look forward to meeting you.

Apply Here.