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.

Portfolio Spotlight: Trestle

Congratulations to our portfolio company, Trestle, on their recent investment led by ‌Camber Creek, a leading investor in the future of the built environment.

We first invested in Trestle alongside Lerer Hippeau, MetaProp, Alumni Ventures, The LegalTech Fund, Redbud VC, and Meridian Ventures after meeting co-founder & CEO Victor Zhang through a cold inbound pitch that immediately stood out. Victor’s 15 years in heavy construction, leading estimating and procurement teams on some of the largest projects in the country, gave him a clear, operator-led perspective on a problem the industry has long accepted as “just the way it is.”

Contractor prequalification is a critical step in construction, yet it remains surprisingly manual. General contractors still rely on static forms, spreadsheets, and disconnected systems to evaluate subcontractors’ insurance, safety, financials, and experience. This introduces unnecessary risk and friction into already complex projects.

Trestle is changing that.

The platform modernizes prequalification by centralizing subcontractor data, automating document review, and providing real-time visibility into vendor risk and performance. By replacing fragmented workflows with a dynamic, intelligent system, Trestle helps general contractors prevent millions in losses and proactively manage vendor compliance and performance risk with AI-powered automation, without adding overhead.

As construction continues its long-overdue digital transformation, solutions like Trestle are becoming increasingly essential. We’re excited to see this next chapter for the team and proud to continue supporting them as they scale alongside Camber Creek.

Congratulations to ‌Victor and the entire Trestle team on this milestone.

Founder Spotlight: Dan Pantelo (Marpipe)

Meet Dan Pantelo, Founder & CEO of Marpipe.

The son of Ukrainian refugees, Dan grew up with a deep appreciation for hard work, competition, and the opportunities created by building something from scratch. That mindset carried him from running early marketing businesses to founding Marpipe, where he’s helping brands and design teams take control of product catalogs and power the majority of performance-driven ecommerce advertising.