ARCHIVE
October
| 10/26 Moonshot AI Limitless Labs Sizeable Energy Bricklayer AI Casium | 10/19 Dialogue AI Fundamento Chara Technologies | 10/12 AnyTeam Claimy Greylabs AI 375ai Focal Lunos AI | 10/5 Payment Labs Harvey |
10/26/25
In the fast-moving startup ecosystem of late October 2025, seed rounds under $10 million are no longer just about “build and hope.” This week’s five featured companies are tackling big-ticket problems—web growth automation, prediction markets, long-duration clean-energy storage, AI-driven cybersecurity, and global talent mobility—with serious capital behind them. Join me as we dive into the details of each raise, how the founders are positioning for scale, and what these moves say about where tech infrastructure is headed.
Moonshot AI raised $10 million to build what it calls “living” websites — sites that rewrite themselves in real time, test new layouts automatically, and basically operate like autonomous growth agents instead of static marketing pages. The round was led by Mighty Capital with Oceans Ventures, Uncorrelated, Garuda Ventures, and Almaz Capital also in the deal. The company positions itself as no-code performance automation for founders: you describe the business outcome you want (more conversions, more paid signups, better onboarding), and the site iterates itself toward that result without a human growth team babysitting it. Moonshot AI says the new funding will scale its platform in both New York and Tel Aviv and push deeper into full-stack, AI-run digital storefronts, not just landing pages.
Underneath the pitch is a bigger bet: marketing gets eaten by agents. Traditional web is frozen in time — design → publish → pray. Moonshot’s take is that sites should behave more like trading algorithms, constantly testing and reallocating attention toward whatever converts. If they’re right, “web design” becomes less about pretty hero images and more about closing a feedback loop between traffic, revenue, and on-the-fly personalization. That’s a direct threat to creative agencies and CRO consultants, and it’s also the first credible “AI growth team in a box” we’ve seen come out swinging with real capital and real investors behind it.
Pulling in a $10 million seed round led by 1confirmation, with participation from F-Prime, DCG, Arrington Capital, and others, Limitless Labs (often just “Limitless”) will scale a Web3-native prediction market. Their product focuses on ultra-short-term contracts — think fast, event-driven wagers and markets that settle almost immediately instead of dragging on for weeks. The startup frames this as “real-time price discovery for reality,” not gambling, and says the funding will go toward licensing and compliance work globally ahead of an upcoming token launch. It’s also notable that Limitless is Ukrainian-founded, and still managing to raise meaningful U.S.-backed crypto capital in a market that’s been brutal for anything that smells like tokens.
The bigger story here is regulatory velocity. Prediction markets are a political lightning rod because they sit at the intersection of finance, speech, and speculation, and most players either go fully offshore or get shut down trying to operate in the open. Limitless is openly talking about licensing and global rollout at seed stage, which signals they’re going for legitimacy, not shadow volume. If they thread that needle, they won’t just be another degen casino — they’ll be infrastructure for forecasting, hedging, and trading sentiment in real time. That’s a category that legacy finance wants, but can’t move fast enough to build.
An Italian-born climate tech startup, Sizable Energy, raised $8 million to do something that sounds like science fiction: store clean energy under the ocean. Their system is a form of offshore pumped hydro — instead of building giant reservoirs in the mountains, they use flexible underwater tanks and the pressure of deep water to hold surplus renewable energy and then release it back as needed. The new money will fund real-world testing so they can prove they can deliver multi-hour and long-duration storage without depending on scarce land, rare earth batteries, or onshore permitting battles. Investors are effectively betting that long-duration storage at sea is cheaper, faster, and more politically scalable than building new battery farms in somebody’s backyard.
Why this matters: renewables don’t lose because of generation anymore — wind and solar are cheap. They lose because the grid can’t bank that energy until prime time. If Sizable Energy’s underwater reservoirs work at commercial scale, you get clean baseload-style reliability without digging lithium out of the ground and without fighting neighbors over where to put giant containers of batteries. That is the kind of infrastructure moonshot climate funds love: if it works, it slots directly into national energy security narratives and becomes a geopolitical asset, not just a green feel-good story.
Bricklayer AI closed a $5 million seed round led by Tech Square Ventures, with follow-on checks from Sovereign’s Capital, Dreamit Ventures, and BlueWing Ventures. The company is pitching “agentic cybersecurity”: AI agents that plug into a Fortune 500 security stack, watch everything, and handle large chunks of incident response work automatically. Bricklayer says its recurring revenue is already up 14x year-to-date, and that its platform is actually deployed inside big enterprises today, not just living in pitch decks. The raise was oversubscribed, which in 2025 only happens if buyers (not VCs, buyers) are screaming for the product.
Zoom out and you see two converging forces: the cybersecurity talent gap and the explosion of machine-speed threats. Old-school SOC teams drown in alerts and burnout; attackers now use automated tooling that never sleeps. Bricklayer is basically saying, “Let software be Tier 1 and Tier 2 analyst,” and let humans step in only for judgment calls. If they keep proving out inside large regulated companies — which is the hardest sandbox in security — this isn’t just a point solution, it’s a reshuffle of who does the work during a breach.
Casium, a Seattle startup focused on immigration and global mobility, raised $5 million in seed funding led by Maverick Ventures with backing from AI2 (Allen Institute’s incubator), GTMfund, Success Venture Partners, and others. The product is straight to the pain point: U.S. work visas, compliance, and cross-border hiring are still handled like it’s 1998 — spreadsheets, lawyers, panic. Casium wraps that into an AI-driven workflow that tries to prevent problems instead of reacting to them, positioning itself as an “outcome-based” immigration service for employers that need to move talent across borders quickly and legally. The company frames itself less as a law firm and more as automated infrastructure for workforce mobility.
It’s quietly a huge market. Every fast-scaling company with global talent hits immigration bottlenecks, and HR teams are not built to manage visa risk at scale, especially with governments tightening scrutiny and increasing fines. By treating immigration as software — tracking status in real time, flagging risk, auto-generating filings — Casium is basically trying to become “Gusto for visas.” The $5M round is early, but if they keep landing enterprise accounts, this becomes a wedge into compliance, relocation, tax exposure, and even compensation benchmarking for cross-border hires. That’s sticky, high-retention revenue if they execute.
Put all of this together and there’s a clear vibe in late October 2025: sub-$10M rounds are no longer about “let’s build an MVP and see.” They’re about attacking core infrastructure — how we sell on the internet, how we store clean power, how we defend corporate networks, how money prices information, and how companies move talent across borders — with AI or AI-adjacent automation baked in from day one. The check sizes are still technically “seed,” but the narratives are grown-up: regulation, compliance, energy resilience, enterprise security. That’s the signal for us at Coolture.club — the frontier is getting institutional faster, and founders are raising to scale and legitimize, not just to prototype.
10/19/25
In a venture scene getting crowded with mega-rounds and “moonshot” headlines, the most interesting deals this week are modest in size but sharp in focus. They tackle specific pain points—voice AI, deeptech manufacturing, market research workflows—and do so with clear product-market fit, early traction, and tightly defined markets. These rounds may not headline the news, but they often signal where durable infrastructure gets built. Below are five companies deserving attention for their focused ambitions and investability.
Led by Lightspeed Venture Partners, with participation from other prominent investors, Dialogue AI raised $6 million in seed funding. The startup is focused on transforming the global market research industry (~$140 billion) by building an AI platform that can automate study design, recruit participants, and conduct thousands of real-time interviews via an AI interviewer. Early clients include Nextdoor, Square and Wayfair, who report meaningful time savings in survey and insight workflows. The company is still small (≈10 employees) but plans to double in the next 12-18 months, signaling that this funding is as much for build-out as for validation.
Dialogue’s strength lies in marrying AI automation with a long-established process (market research) that has been ripe for efficiency gains. Instead of building general-purpose tools, they are embedding deeply into the insight workflow—participant recruitment, interview scripting, realtime analysis—so the value proposition is quantifiable. With the new capital they’ll scale both engineering and marketing efforts and aim to expand into “synthetic user” research models by mid-2026. If they deliver consistent cost savings and turnaround time improvements, they may redraw how enterprise research teams operate.
Fundamento secured $1.9 million in funding led by IIFL Fintech Fund, with participation from Players Fund, Venture Catalysts and Lead Angels. The startup builds an agentic voice AI platform—enabling organizations to deploy voice-powered workflows where spoken orchestration and tasks replace purely manual or text-based processes. The raise signals growing investor interest in voice AI, beyond chat UIs, into domains where spoken instruction, understanding and response are required.
Fundamento is targeting workflows that still rely heavily on voice—for example call-centers, service agents, or voice-driven commands—where automation has been harder to apply than text or GUI-based tasks. The funding will support technological development and scale-up of their voice agents, likely focusing on languages and markets with underpenetrated voice AI. If they execute well, they could be early to a frontier where voice becomes an input modality as important as chat or touch.
Chara Technologies raised $6.2 million in a round led by Arkam Ventures, with support from Exfinity, Kalaari Capital and IIMA Ventures. The startup is developing motors and manufacturing processes that avoid reliance on rare-earth materials—a significant supply-chain and sustainability issue in many industries today.
The promise here is dual: cost reduction (rare-earth magnets are expensive and geopolitically constrained) and sustainability (less environmental and supply-risk exposure). Chara is applying advanced manufacturing and materials science to build differentiated motors that appeal to industrial, EV and robotics applications. With this raise they’ll likely scale production, refine materials, and validate performance with early customers. If successful, they could become a key supplier in sectors looking to de-risk magnet supply chains.
What stands out this week is not simply the amount of capital raised, but how it is being deployed: into voice AI, real-time research workflows, and deep materials/manufacturing innovation. Each of these companies attacks a specific, meaningful bottleneck rather than chasing broad “AI everywhere” narratives. That kind of specificity—paired with early traction, defensible domains and narrow focus—is what seed investors are looking for right now. As your column tracks these trends, keep paying attention to deals where the scope is tight, the problem is painful, and the team can deliver. They may not always be the biggest rounds, but they often become the most resilient engines of growth.
10/12/25
AI continued to dominate—but the most interesting checks weren’t the mega-rounds. They were the sub-$10M financings aimed at concrete, high-friction problems: on-device sales workflows, voice AI in contact centers, decentralized real-world data capture, and vertical productivity tools for finance and law. These teams are shipping practical systems that tuck neatly into existing stacks rather than forcing wholesale change, which is exactly why they’re clearing investment committees right now. Here are five to watch from the past week.
San Francisco–based AnyTeam raised $10M (seed) led by SignalFire with participation from Crosslink Capital and dozens of go-to-market operators. The company is positioning itself as an AI-native operating system for sales reps, aiming to automate tedious CRM updates, note-taking, follow-ups, and account research so sellers can spend more time, well, selling. Early previews emphasize on-device performance and privacy—useful for field teams and regulated accounts—and a workflow that plugs into the tools reps already live in. The announcement surfaces a broader pattern this fall: “agentic” assistants moving from demos to daily, revenue-adjacent work.
The bet is that context-aware, lightweight agents will outperform generic copilots by living closer to the rep’s actual workflow (email, calendar, calls) and by minimizing back-and-forth with heavy CRM UIs. With fresh capital, AnyTeam can deepen integrations, widen early-access cohorts, and prove lift on hard KPIs like pipeline created, conversion, and rep time saved. If it nails data governance and avoids “noisy bot” syndrome, an AI-first “sales OS” could become the layer that standardizes best practices across teams without heavy change-management. It’s a classic wedge: start with automation around revenue work, earn trust, then expand.
Claimy recently raised €1.5 million (≈ USD $1.8 million) in a funding round targeting the complex problem of unclaimed music royalties. The company has built an AI platform that cross-references metadata, publishing contracts, PRO (performance rights organization) collections, and playback monitoring services (e.g. BMAT) to detect discrepancies between what should have been paid and what actually was. It currently operates in the UK and France markets, and claims to manage €6 million in rights across ~160,000 musical works. The platform is positioned not as a replacement for collecting societies, but as a complementary audit tool that surfaces missing payments backed by evidence.
Claimy’s approach emphasizes automation and transparency in a notoriously opaque space. Their algorithm compares catalog data with PRO reports and usage logs, generating claims for mismatches and offering insight into when and where tracks were used but not paid. The startup also handles edge cases such as remixes, slowed or sped versions, live adaptations, and alternate masters—not just straightforward original works. Their clients include rights holders, publishers, and artist teams, and they cite involvement with high-profile catalogs (e.g. works tied to Céline Dion). With fresh funding, Claimy plans to expand coverage, improve model accuracy, and scale support for additional territories and rights types.
Bengaluru-based GreyLabs AI secured ₹85 crore (~$10M) Series A led by Elevation Capital, with participation from existing backer Z47 (ex-Matrix Partners India) and angels. GreyLabs provides speech analytics and agentic voice AI for banks and insurers, promising better intent detection, compliance monitoring, and automated after-call work. The raise comes alongside plans to scale deployments from dozens to hundreds of institutions and to expand presence in India’s key financial hubs. It’s a timely thesis: voice remains the highest-friction channel in BFSI, and measurable AI improvements in call handling directly hit cost and CSA
Strategically, GreyLabs is leaning into vertical depth—training models on regulated, domain-specific language and compliance patterns rather than chasing a horizontal contact-center platform. That should translate to faster time-to-value and cleaner audits in a sector where accuracy and explainability matter. The capital is earmarked for product scale-up, enterprise onboarding, and footprint expansion; if execution matches plan, the company can become a default layer for voice QA and guidance across India’s BFSI. The ceiling gets higher as the product moves from analytics into real-time agent assistance and resolution.
375ai raised $10M led by Delphi Ventures, Strobe Capital, and HackVC to expand a Solana-based DePIN network that captures physical-world data via vehicle-mounted sensors. The project’s thesis: create a decentralized data layer for cities—traffic flows, footfall, environmental signals—and make it accessible to developers and enterprises that need fresh, granular telemetry. Recent coverage highlights initial deployments in Los Angeles, New York, and Miami, with an international push on deck. In a market thirsty for trustworthy, up-to-date real-world inputs, a networked, incentive-aligned approach could beat siloed data vendors on freshness and cost.
The hard part isn’t just hardware—it’s data quality, governance, and developer UX. 375ai is investing proceeds into expanding sensor fleets and building the platform side (APIs, SDKs, dashboards) so customers can query signals without wrestling with raw streams. If the team proves defensible coverage and reliable labeling, it can become essential plumbing for mobility analytics, retail site selection, urban planning, and even insurance. The DePIN angle isn’t a gimmick; it’s a go-to-market mechanism to scale capture where traditional networks stall.
Focal raised $5M (seed) to build an AI-powered productivity platform for RIAs and wealth managers. Rather than being another point tool, Focal aims to be the central workspace: client context, meeting prep, tasking, compliance-friendly notes, and follow-ups—integrated with the custodians and CRMs advisors already use. The promise is a measurable lift in AUM per advisor and time-to-follow-up, as assistants generate summaries, next-best actions, and standardized documentation for audits. In wealth, where minutes compound into missed opportunities, “fewer tabs, more outcomes” sells.
The round gives Focal runway to expand integrations and build the policy guardrails compliance teams require—key to enterprise RIA adoption. If it can demonstrate hard ROI in pilot cohorts (e.g., higher meeting throughput, reduced NIGO, faster prospect conversion), the platform can move from “nice to have” to mandated tooling. The advisor stack is crowded, but there’s room for a home-base product that stitches AI into daily motions without breaking supervision rules. Execution here is about workflow empathy as much as models.
New York–based Lunos AI closed a $5M pre-seed to automate accounts receivable using agentic workflows (invoice matching, collection nudges, dispute triage). The company is targeting the overlooked back-office mess where teams juggle spreadsheets, PDFs, and emails, and cash flow gets tied up in preventable delays. For mid-market finance orgs, even single-digit improvements in DSO translate into meaningful working-capital wins. Investors here are betting that voice + workflow agents can turn AR from reactive to proactive.
The near-term roadmap emphasizes ERP/CRM connectors,templated playbooks, and guardrails that keep agents inside finance policies. That’s critical for trust; CFOs will happily accept automation if it’s auditable and reversible. With the raise, Lunos can scale pilots across verticals (SaaS, B2B marketplaces, logistics) and quantify lift in cash recovery and team throughput. If it lands those proofs, AR is a logical beachhead into broader order-to-cash automation.
This week’s theme is simple: AI that does the work—not just suggests it. From sales and service calls to city telemetry and balance-sheet health, each company here earns its keep by removing drudgery and surfacing dollars (revenue captured, costs reduced, working capital freed). That’s why these sub-$10M rounds matter more than their size: they’re the earliest signals of category tools that can quietly become indispensable across stacks.
10/5/25
In a week where headline-grabbing mega rounds dominate news feeds, the more modest seed deals reveal where scrappy innovation and vertical specialization are still very much alive. Investors continue pouring capital into startups that tackle domain-specific bottlenecks — payments, legal, workforce enablement — rather than going wide too early. The companies below may fly under the radar, but they’re building tightly wound solutions with real infrastructure potential.
Los Angeles fintech Payment Labs closed a $3.25 million seed round, led by Aperture Venture Capital, with Capital Eleven, ESPMX and others participating. The company specializes in payment orchestration and payout systems tailored for creators, sports, esports, and other domains with complex revenue share needs. With customers like Microsoft, SEGA, X Games, The Snow League, AVP and others, the platform has already processed over $50 million in payments. By packaging tax compliance, multi-method disbursements, and reporting into one stack, Payment Labs relieves operators from stitching together multiple fintech vendors.
What makes this raise notable is how Payment Labs is leaning into vertical complexity as a moat. Unlike general payment processors, it offers domain-specific logic — royalties, micro-payouts, split revenue — baked in from day one. The fresh capital will go into scaling sales, expanding integrations (especially international rails), and enhancing compliance tooling (e.g. tax withholdings). For creators and events that manage thousands of payees across geographies, frictionless payout operations can make or break scaling. If Payment Labs delivers reliability plus transparency, it has the chance to become a default operating piece in creator/sports fintech stacks.
Los Angeles’s Harvey announced a $5 million funding round for its AI-enabled legal software platform. The startup offers tools designed to help legal practitioners—especially in firms and in-house teams—draft, review, and manage legal documents more efficiently. Early product features include clause generation, redlining suggestions, and contract analysis that surface risk and missing terms. It’s a bet that law firms increasingly need AI augmentation but demand domain-specific accuracy and legal domain safety.
Harvey’s strength lies in balancing innovation with trust: legal professionals are notoriously cautious about AI hallucinations or incorrect language. By focusing tightly on contract law language and building checks, Harvey positions itself for cautious adoption in real-world, billable work. The funding will go into expanding model accuracy, adding integrations with practice management and document systems, and investing in user feedback loops from law firms. If Harvey can avoid the “AI fantasy vs legal rigor” trap, it may capture share in the slow-moving but high-margins space of lawtech.
These two deals reaffirm a theme: verticalized infrastructure is where early capital still flows. Instead of broad “AI for everything” bets, these companies build for domains where domain knowledge matters deeply: payments in creator economies, legal workflows in law firms. They lean into complexity as their advantage, not as a barrier. As your column tracks these shifts over time, keep an eye on founders who resist horizontal scale in year one and instead double down on a domain dice roll.
ᴀɪ ᴅɪꜱᴄ ᴊᴏᴄᴋᴇʏ 