The Next Great Idea Is Already Looking for You

Throne Science

Throne Science just raised a $10M Series A to turn one of the most overlooked rooms in the house into a continuous health data layer.

Will Ventures led the round, with Emerson Collective, Workshop, LEAD, Salt VC, Accomplice, Moxxie Ventures, and other investors participating. The financing brings Throne's total funding to nearly $18M since its 2023 founding.

Throne One is a toilet-mounted sensor that uses optical and acoustic data to track stool form, bathroom patterns, hydration, and urinary flow. Its software transforms those signals into longitudinal health insights without asking users to log every meal, remember every symptom, or ship samples to a laboratory.

Health wearables succeeded by making measurement passive. The wrist became valuable because people could forget the hardware while the data continued to accumulate. Throne is applying the same principle to gut and urinary health, categories still dominated by snapshots, memory, and the deeply scientific phrase, "I think this started a few weeks ago."

Scott Hickle, CEO and Co-founder, launched Throne alongside Timothy Blumberg, CTO and Co-founder. John Capodilupo, Co-founder and Chief Product Officer, brings a decade of experience as WHOOP's Co-founder and former CTO, along with personal experience living with ulcerative colitis. This is a hardware, software, and behavioral design challenge centered on one of healthcare's largest data gaps.

The company says its computer vision pipeline uses a dozen models, several trained with practicing gastroenterologists. A beta Gut Health Coach connects daily readings with user-reported factors such as diet, sleep, and stress. Validation studies are underway with researchers at Harvard, Stanford, and the University of Chicago, according to the company.

The medical boundary is important. Throne is currently sold as a general wellness product rather than a diagnostic medical device. Its longer-term ambition is to identify changes that may serve as early warning signals for colorectal, bladder, and kidney cancers. That "smoke detector for colon cancer" vision remains under development and is not a capability of the current product.

The Series A will support consumer education, clinical channel expansion, and core research and development. The product will ultimately depend on earning consumer trust, establishing clinical credibility, and building a dataset rich enough to turn everyday bathroom behavior into something far more valuable than a punchline.

The funding provides Throne with the opportunity to prove that passive health monitoring can extend beyond wearable devices. The broader question is whether the next major category in digital health will be built not on what people choose to measure, but on signals they generate every day without changing their routine.

Olomon

Olomon just raised a $2.6M oversubscribed pre-seed round to build a financial system of record for complex households and their advisors. The company is targeting the layer beneath dashboards, planning tools, CRMs, and document vaults: one structured record of what a family owns, owes, controls, and needs its professional team to understand.

The challenge becomes more acute as wealth grows more complex. Accounts, real estate, private investments, trusts, LLCs, insurance policies, and estate documents live in separate systems. An advisor sees one slice, the attorney another, the CPA a third, while the family is expected to serve as the human API holding everything together.

Jeremy L. Bolls, Founder and CEO, has experienced both sides of that problem. Losing his father at 11 exposed what happens when an entire financial picture exists only in one person's head. Years later, after building Kindful and selling it to Bloomerang in 2021, increasing financial complexity revealed the same issue from the opposite direction: more assets and more advisors did not automatically create more clarity.

That is the opportunity Olomon is pursuing. Its platform models accounts, entities, documents, people, and relationships as connected financial objects, then gives households control over which advisors, attorneys, and CPAs can access and update them. The record belongs to the household rather than the current advisory firm, allowing continuity even when professional relationships change.

The funding will support three priorities: expanding product coverage, strengthening infrastructure for professional collaboration, and moving from invite-only early access toward general availability, which Olomon targeted for early Q3 2026. The company says its backers include entrepreneurs, operators, fintech investors, and financial services professionals, with several already using the platform. Investor names were not disclosed, and one allocation remains reserved for a potential strategic partner.

Olomon is betting that ownership, permissions, and continuity can become a category rather than another feature checklist. Advisors have CRMs. Financial planners have modeling tools. Custodians have account data. Families are still left carrying the integration burden through email, spreadsheets, memory, and hope. The challenge will be earning enough trust and professional adoption for this record to become the source every other system relies upon.

A $2.6M pre-seed round does not prove the thesis, but it gives Olomon the opportunity to demonstrate that complex households need infrastructure designed around their reality rather than another polished view of disconnected fragments.

Weave

Weave raised a $13.5M Series A led by Standard Capital, with Y Combinator, Moonfire, Burst Capital, IrregEx, and Agent Fund participating. That brings disclosed funding across its two announced rounds to $17.7M, but the more important number is what customers actually gained from all that AI spending.

Engineering is becoming the only department where adding more software makes the scoreboard harder to read. Coding assistants, autonomous agents, and token bundles are arriving faster than leaders can prove their return.

Weave is building the accounting layer for that uncertainty. Its platform follows work from prompt to production, connecting AI cost and usage with output, code quality, and software delivery so engineering leaders can see whether faster activity produced better software or simply a larger cloud bill. Token volume is not productivity. More prompts can represent real value, duplicated work, or senior engineers cleaning up output from a model that looked inexpensive until the rework arrived.

Adam Cohen, CEO, and Andrew Churchill, CTO, built Weave around a straightforward question: why does sales have one definitive performance metric while engineering is still evaluated on intuition? Their answer was to build the measurement layer first, then use that data to improve the decisions made above it.

The platform now spans engineering analytics, token intelligence, agent observability, and model routing. Weave distinguishes coding assistants from autonomous agents, connects cost to outcomes, and routes prompts without assuming lower-cost inference automatically produces better work. That is a more useful question than simply claiming AI makes developers faster. It examines where AI creates leverage, where it introduces friction, and when increased activity stops translating into meaningful progress.

Customers appear to recognize the need. Weave says more than 500 engineering organizations use its platform, the company's 16-person team serves customers including Robinhood, PostHog, Telnyx, and Reducto.

The Series A follows a $4.2M seed round announced in July 2025 and provides additional capital for product development and go-to-market expansion. Standard Capital is betting that AI spending has become too important, and too difficult to measure, to remain trapped inside vendor dashboards and executive guesswork.

The broader lesson reaches beyond one funding round. Before asking which model is cheapest, engineering leaders need evidence showing which work created value, what quality survived deployment, and whether the combined system of people and AI agents is actually improving. AI-assisted coding has changed how software gets built. Weave's latest financing suggests the next competitive advantage will come from proving what those changes are worth.

Birdai Labs

Birdai Labs, Inc. just raised a $4M Seed round to put a price on something onchain markets have long treated as too slippery to measure: the value that disappears between the order a trader sends and the fill the trader receives. Castle Island Ventures led the round, with Metalayer Ventures and The Venture Dept. participating. The funding will support senior engineering hires and continued investment in base-layer infrastructure.

A block explorer can show what settled. Birdai Labs is building the measurement layer for how it settled, who benefited from transaction ordering, and how much value leaked along the way. Its beta metric is designed to attribute that leakage across fees, extraction, and market impact, making execution quality measurable rather than a marketing adjective wearing a lab coat.

Kevin Farrelly, CEO, and Greg Scanlon, CTO, self-funded the initial infrastructure before raising outside capital. Kevin Farrelly previously co-founded Random Forest Capital, which Franklin Templeton acquired in 2018. Greg Scanlon brings quantitative trading experience from Citadel and blockchain venture experience from Franklin Templeton, where he later developed Birdai Labs' core technology.

James McClain, Founding Quantitative Researcher, adds another layer of expertise with a Princeton PhD and quantitative hedge fund experience. That team composition is part of the thesis. Crypto has never lacked opinions about fairness. It has lacked independently verifiable measurements.

Birdai Core, the company's free measurement layer, is now live, and Birdai Labs says its work is grounded in millions of decoded transactions. The platform targets traders, market makers, protocols, decentralized exchanges, and validators. Each sees a different part of the market, but all bear the cost when accountability ends with "the transaction went through."

The broader bet is that faster chains and multi-proposer designs will further fragment control over transaction ordering, increasing the value of neutral measurement. Traditional capital markets eventually built disclosure standards around execution quality because sophisticated investors always ask the same uncomfortable question: compared with what?

Castle Island Ventures is backing Birdai Labs as that question moves onchain. The opportunity is not simply to measure leakage, but to establish a verifiable standard for execution quality. If Birdai Labs succeeds, the next competitive advantage in DeFi may belong to the infrastructure that proves who delivered the better trade rather than who wrote the better narrative afterward. What happens when execution quality becomes something every protocol, trader, and investor can inspect instead of simply trust?

Procode Inc.

Procode Inc. raised a $10M Series A led by Health Velocity Capital. The interesting part is where the capital is going: two medical billing acquisitions, expansion across surgical specialties, and a push into ambulatory surgical center billing. That makes Procode less a software company than an operating thesis. Specialty billing firms own hard-earned expertise and long-standing provider relationships. Procode's strategy is to acquire that knowledge, then strengthen it with better coding, collections, reporting, and automation. The premise is not that AI replaces the business. It is that AI makes the business more valuable.

Founded in 2024 by Jeff Cripe, CEO, Kameron Rezzadeh, MD, FACS, Chief Medical Officer, and James Baez-Silva, Procode pairs operational leadership with clinical expertise. That matters because revenue cycle management is not an abstract challenge when a delayed claim or inaccurate code determines whether a practice gets paid.

Procode's platform combines surgical coding, Procollect for billing operations, and the Auctus Provider App for real-time financial visibility. Through its acquisition of The Auctus Group, the company says it now serves more than 350 plastic surgery and dermatology providers.

The company says it is on track to double Auctus revenue while increasing its EBITDA margin fivefold. Those company-reported targets help explain the investment thesis. Health Velocity Capital is backing software tied directly to collections, operating margins, and an acquisition-driven growth strategy.

A peer-reviewed retrospective study evaluated Procode's domain-specific system using 120 operative reports. According to the company, it achieved 100% exact code-set accuracy on low-complexity cases and 80% on both medium- and high-complexity cases. Overall accuracy reached 86.7%, compared with 42.5% for external professional auditors and 35.8% for the strongest general-purpose model included in the study.

Those findings deserve attention, but they also deserve context. Several authors were affiliated with Procode and participated in developing the system, while the dataset focused exclusively on plastic and reconstructive surgery. The results are encouraging evidence, not proof that every surgical coding challenge has already been solved.

The Series A brings Procode's company-reported total funding to $14M and provides additional capital to test whether its domain-specific AI can expand across specialties without losing the expertise that made each acquired billing business valuable in the first place.

The broader market signal is equally compelling. Healthcare AI companies may find their strongest path to scale by acquiring positions inside established workflows, proving value through measurable cash collection and operational performance, and allowing those results to speak louder than product demonstrations.

Healia Health

Healia Health just raised a $14M Series A to fix a health benefits problem hiding in plain sight: when two people in the same household both work, the insurance system still treats their choices like paperwork from separate planets.

111° West Capital led the round, with participation from Y Combinator, First Round Capital, Pioneer Fund, GoAhead Ventures, and North Coast Ventures. The financing brings Healia's total funding to $18M. The company says employers using its platform have delivered $33M in additional benefits to families.

Priyang Shah, Founder and CEO, built Healia around a practical observation. Dual-income households may have access to two employer-sponsored health plans but very little household-level analysis. Make the wrong choice, and families absorb higher costs while employers carry avoidable claims. Everyone pays for confusion, a remarkably expensive way to administer benefits.

Healia's Total Care Option changes that equation. The health reimbursement arrangement allows eligible employees to join a spouse's plan while their employer reimburses eligible premiums and out-of-pocket expenses. Healia manages plan comparisons, education, claims, and reimbursements, with AI-powered decision support showing household costs side by side.

The market is reinforcing the opportunity. KFF reported average family health insurance premiums reached $26,993 in 2025, up 6% year over year, while Mercer expects employer health benefit costs to increase another 6.7% in 2026. Meanwhile, both spouses worked in 49.1% of married-couple families last year. Households have evolved. Benefit design has largely stayed the same.

Healia says its model can reduce employer costs by as much as 76% per enrolled household while covering up to 100% of eligible family out-of-pocket expenses. Those are company-reported outcomes, but the incentive structure is straightforward: employers reduce costs, families receive stronger coverage, and HR teams spend less time managing benefit complexity.

Priyang Shah previously held early product roles at Root Insurance and Olive AI before founding Healia. The company now says it serves hundreds of employers nationwide while maintaining its operating headquarters in Ohio.

The Series A will support expansion across sales, engineering, and operations in Columbus. That aligns with a business built on software, education, claims administration, and trust. Healthcare rarely forgives broken handoffs simply because the technology looks modern.

The broader signal extends beyond one funding round. Many health technology opportunities are not about creating new healthcare dollars. They are about helping families and employers make better use of the dollars already moving through the system. Healia is betting that better decisions can become a meaningful competitive advantage.

Fish Audio

Fish Audio just raised $52M in seed funding after turning a single-GPU voice experiment into a company that says it reached $21M in ARR within one year. The round was led by Coreline Ventures and Capital Today. The more interesting number may be 22: the size of the team Fish Audio says built five audio models, attracted more than 8M users, and enabled the creation of more than 2M community voice models.

Shijia Liao, Founder and Chief Scientist, began the underlying work on a single RTX 4090 after deciding synthetic voices could pronounce the words but still missed the performance. Rissa Cao, CEO and Co-founder, brought experience from Amazon Alexa and Meta, while Jiahua Liu, CTO and Co-founder, helped transform the research into infrastructure that creators, developers, and enterprises could actually deploy.

Fish Audio did not begin with a polished enterprise sales motion. Game developers, anime fans, dubbers, and open-model builders pushed the product into edge cases that no conference-room roadmap would have uncovered. The community became distribution, product feedback, and a continuous preference loop.

Enterprise customers now reportedly generate roughly two-thirds of revenue. Fish Audio says production users include HeyGen, LiveKit, Retell, Sanas, and OpenArt AI. S2.1 Pro supports more than 83 languages and over 15,000 natural-language controls for emotion, pacing, and delivery. The value proposition has evolved from making text speak to making synthetic speech behave like a native part of the product experience.

The funding will support expansion into audio understanding, speech-to-speech models, developer tooling, APIs, and enterprise deployment. That means the next competitive challenge is no longer voice quality alone. It is latency, controllability, licensing, data retention, security, and whether the platform can satisfy enterprise procurement requirements.

Trust remains the harder problem. Complaints were reported from voice artists whose likenesses were uploaded without consent. Fish Audio says it automated takedowns, but reactive removal is not the same as verified ownership. At this scale, consent, attribution, and licensing need to become product capabilities rather than support-ticket workflows.

The broader business lesson is straightforward. Open models can accelerate distribution, communities can become a durable product advantage, and technical efficiency can create pricing leverage. Enterprise buyers, however, continue to purchase reliability, governance, control, and measurable outcomes. The seed round gives Fish Audio the resources to continue scaling its platform. The larger question is whether expressive voice becomes foundational infrastructure and whether the company can make trust scale as quickly as the technology itself.

ChipAgents

ChipAgents just put another $60M behind a blunt thesis: semiconductor engineering does not need another AI assistant offering suggestions from the passenger seat. It needs agents that can take on real work across specifications, RTL, verification, simulation data, and waveforms, then hand engineers something useful before the calendar starts collecting victims.

The Series A2 was led by B Capital, with Bessemer Venture Partners, Micron, MediaTek, Ericsson, ScOp Venture Capital, and other existing investors participating. The financing expands ChipAgents' Series A and brings total disclosed funding to $134M.

Chip development is where software optimism meets physical consequences. A design flaw that survives verification can consume time, capital, and an entire production schedule. ChipAgents is building autonomous agents that execute multi-step design and verification work instead of waiting for an engineer to prompt every action.

The commercial traction is becoming difficult to ignore. ChipAgents reports 6x ARR growth during the first half of 2026 and deployments at more than 120 semiconductor companies, including MediaTek and Micron. That compares with 50 deployments in October 2025 and 80 by February 2026. The growth curve says more than the marketing language.

William Wang, Founder and CEO, describes the platform as a move beyond copilots toward autonomous engineering agents. That distinction defines the business model. Semiconductor teams are looking to compress design cycles and automate repetitive verification work, not purchase more sophisticated chat interfaces.

The new capital will support customer deployments, engineering and go-to-market hiring, and continued platform development. The question is no longer whether AI can generate code. It is whether specialized systems can perform meaningful engineering work in environments where accuracy, security, and context are non-negotiable.

B Capital is backing more than another agent narrative. General Partner Daisy Cai brings semiconductor design experience to the ChipAgents board. Participation from Micron, MediaTek, and Ericsson adds direct industry context, while Bessemer Venture Partners and ScOp Venture Capital provide continuity from earlier rounds.

The broader signal extends beyond one financing. Capital is moving toward autonomous engineering inside one of technology's least forgiving disciplines. If ChipAgents continues converting that ambition into production deployments, electronic design automation may be judged less by how much software assists engineers and more by how much verified work it can reliably complete.

Adjuvia Therapeutics

Adjuvia Therapeutics just closed an $8M Series Seed to move ATI-105 toward the clinic. JLO Ventures led the round, with Portfolia and experienced biopharmaceutical leaders participating. The funding has a specific purpose: support a planned IND submission later this summer and a Phase 1 trial targeted to begin in fall 2026.

The challenge is more difficult than the financing announcement makes it sound. Mitochondrial dysfunction can drive oxidative stress, inflammation, and organ decline across rare and chronic diseases. Biology does not care how polished the pitch deck is. A molecule still has to reach the right tissue and produce a measurable therapeutic effect. That is the gap between an interesting formulation and a drug development program worthy of continued investment.

ATI-105 is Adjuvia's attempt to narrow that gap. The oral therapy uses a proprietary nanoparticle formulation of astaxanthin designed to cross the blood-brain barrier and reach multiple organs. Adjuvia says preclinical studies demonstrate activity across cellular and mitochondrial membranes, targeting oxidative stress and inflammatory signaling. The clinical data will determine whether that promise translates into patient outcomes.

The lead indication is Friedreich's ataxia, a rare inherited disease that progressively damages the nervous system and heart. The FDA approved Skyclarys in 2023 as the first treatment for the condition, but one approval neither simplifies the biology nor eliminates the unmet need. Adjuvia is betting that an orally administered, systemically distributed therapy can provide another path forward, with planned clinical work involving Children's Hospital of Philadelphia and UCLA.

Laura Hix Glickman, PhD, Co-founder and CEO, brings more than 30 years of experience spanning biotechnology research, intellectual property, and drug development. Tim Wilson, Co-founder and Chairman of the Board, adds life sciences operating and investment expertise, while Kelly Bryant, Chief Operating Officer, and Gurdyal Kalsi, MD, MFPM, Chief Medical Officer, are helping translate the platform into clinical execution.

The investor syndicate offers another signal. JLO Ventures previously backed Actym Therapeutics, another company co-founded by Laura Hix Glickman. Portfolia brings experience across women's health, active aging, and longevity, areas where mitochondrial function continues to attract scientific interest. This is repeat conviction supporting a milestone-driven development program. The investment thesis ultimately depends on execution rather than narrative.

The Series Seed provides capital for the next critical stage of development. From here, progress will be measured by IND clearance, trial registration, first-patient dosing, safety, pharmacokinetics, and biomarker data. The financing creates the opportunity to answer those questions. ATI-105 still has to earn the answers through the clinic.

Precise Behavioral

Precise Behavioral just raised $14.2M in venture funding, and the interesting part is not another healthcare company adding AI to a slide deck. It is the operating model behind the investment. A1 Health Ventures led the round, with Ziegler Link-Age Fund, Converge Capital Partners, and Granite Financial Holdings, an affiliate of Blue Cross of Idaho, participating.

Nitin Nanda, MD, Founder and CEO, has spent more than 20 years working inside this problem. He founded Precise Behavioral in 2022 after building Aligned Telehealth, which was acquired by Amwell. His new company approaches clinical coverage, fragmented workflows, patient follow-up, technology, and reimbursement as parts of a single operating system rather than isolated challenges.

Its Behavioral Health Operating System combines clinical delivery, operations, patient engagement, and revenue cycle management across inpatient, emergency, ambulatory, post-acute, and home settings. The platform includes modules for virtual psychiatry, measurement-based care, post-discharge engagement, and collaborative care.

Health systems do not need another dashboard that simply visualizes the problem. They need behavioral health capacity that fits existing care delivery, closes referral gaps, and still supports reimbursement. That is operational infrastructure, not another application hoping clinical workflows will reorganize themselves around new software.

According to the company, Precise Behavioral reached profitability in less than three years, delivered more than 100,000 patient encounters, and established a national clinical footprint. The company also lists CommonSpirit and Prime Healthcare among its partners. Those are company-reported figures, but they help explain why this financing looks less like an early experiment and more like capital flowing into an operating platform with demonstrated traction.

The new funding will support operational expansion, digital SaaS capabilities, AI-powered patient engagement, referral management, virtual care delivery, and analytics. In practical terms, Precise Behavioral is investing in the connective infrastructure between growing mental health demand and the complex healthcare systems required to meet it.

The investor syndicate also sends a signal. It combines perspectives from health systems, care delivery, providers, and health plans around a company that serves each of those stakeholders. This is capital backed by organizations that understand the workflows, purchasing decisions, and economic realities that determine whether healthcare technology succeeds in practice.

The broader market signal extends beyond a single funding round. Healthcare increasingly rewards platforms that unify fragmented operations rather than adding another disconnected point solution. Precise Behavioral is betting that an integrated behavioral health operating layer can become the default choice for health systems seeking coordinated care instead of managing an expanding collection of vendors.

InvestiFi

InvestiFi just raised $20M, and the investor list says almost as much as the financing itself. Vibe Credit Union led the round, with BankTech Ventures, ICCU, Navari, United Financial Credit Union, Coastal Credit Union, Mid Minnesota Credit Union, Truity Credit Union, and Southpoint Credit Union participating. That is not capital arriving from a safe distance. Much of it comes from institutions and partners close enough to the problem to understand the cost of leaving it unsolved. Members want to invest, but the traditional path often sends both their assets and the broader financial relationship to a third-party platform.

InvestiFi built its platform around that gap. It brings fractional stocks and ETFs, guided investing, IRAs, cryptocurrency, and stablecoins directly into a credit union's or community bank's digital experience. Its patent-pending Investing from Checking capability allows account holders to invest directly from deposit accounts without first treating their financial institution as a lobby on the way to someone else's app.

The commercial traction strengthens the thesis. InvestiFi says it expanded from four clients in 2024 to more than 60 signed financial institutions as of July 2026. Signed institutions are not the same as fully deployed customers, but the pace of adoption is still a meaningful demand signal.

Recent Cornerstone Advisors research found that 43% of Zillennials moved deposits into investment accounts during the previous year, while 66% of Zillennial investors reduced deposit balances in favor of fintech investing platforms. Owning the checking account is no longer the same as owning the financial relationship. Money has choices, and consumers have become increasingly comfortable exercising them.

Kian Sarreshteh, Co-founder and CEO, and Robert Hoffman, Co-founder and Advisor, recognized the distribution challenge before embedded investing became a boardroom discussion. Sean Coonce, Chief Technology Officer, now oversees a platform spanning securities, guided portfolios, cryptocurrency, and stablecoins without requiring institutions to manage a collection of separate vendors.

The new capital will support platform expansion and increased end-user adoption. Signing financial institutions demonstrates market access. Convincing account holders to actively invest through those institutions will determine whether the model delivers on its promise. The next phase is whether community financial institutions can turn investing into a reason for members to keep more of their assets, engagement, and long-term relationships under one roof.

The broader market signal extends beyond one funding round. Community banks and credit unions are increasingly competing for wallet share rather than simply deposits. Embedded investing is becoming less about adding another financial product and more about preserving the customer relationship before it migrates elsewhere.

ThreatLocker

ThreatLocker just locked down $190M in Series F funding. The round points to the next phase of enterprise security. Elephant led the round, with continued support from D. E. Shaw Ventures and Arthur Ventures, plus a significant new investment from Koch Disruptive Technologies. The syndicate reflects growing conviction in prevention while much of the cybersecurity industry continues to focus on what happens after an attacker gains access.

ThreatLocker has built its platform around a less theatrical idea: define what is allowed, deny everything else, and make that discipline practical enough for real organizations to operate. The attack surface is no longer a tidy collection of laptops behind a firewall. It now includes endpoints, cloud applications, remote users, mobile devices, and AI agents carrying permissions into systems that were never designed for machines acting on behalf of people.

ThreatLocker says the funding will support AI security controls, continued development of its Zero Trust Platform, and international expansion beginning with a new office in Reading, U.K. The company operates from Orlando, Dublin, Dubai, and Brisbane, and reports protecting more than 70,000 organizations worldwide.

The product strategy is expanding alongside the threat model. Allowlisting prevents unauthorized software and AI-generated code from executing. Ringfencing limits what approved applications and AI agents can access or modify. Network and cloud controls extend that same philosophy across internal infrastructure and SaaS environments.

The business lesson sits inside the architecture. Comprehensive protection is not enough. Security controls must also be deployable, manageable, and understandable for the teams responsible for operating them. Even the strongest security platform loses adoption when protection becomes a second operational burden.

Danny Jenkins, Founder and CEO, Sami Jenkins, Founder and COO, Co-founder John Carolan, Head of Quality Assurance, and Michael Jenkins, Chief Technology Officer, continue building on the company's original thesis rather than chasing whichever cybersecurity category happens to attract attention this quarter.

ThreatLocker previously announced a $100M Series C in 2022 and a $115M Series D in 2024. The Series F represents another significant investment behind the same core philosophy, now applied across endpoints, networks, cloud environments, and AI access.

The broader market signal extends beyond one financing. As enterprise environments become increasingly autonomous, prevention is becoming a foundational operating principle rather than a premium security feature. If ThreatLocker continues making deny-by-default easier to deploy and manage, the company's greatest advantage may be turning rigorous security into ordinary infrastructure.

Provable Markets

Provable Markets closed a Series B led by Charles Schwab, with DTCC joining and returning investors Dialectic Capital Management and INKEF participating. The amount and valuation were not disclosed. In market infrastructure, the cap table can reveal as much as the financing itself.

Charles Schwab sits close to the workflows this technology serves. DTCC operates at the center of U.S. post-trade infrastructure. Their investment backs a company modernizing securities finance without pretending the existing market can be replaced by a cleaner slide deck.

Provable Markets operates Aurora, a cloud-native, SEC-registered alternative trading system spanning securities finance. The platform combines multi-party order matching, lifecycle management, books-and-records support, and connectivity to NSCC, DTC, OCC, and tri-party agents. FIX, REST, and gRPC APIs are not glamorous, but neither are trade breaks, manual rerates, or trapped balance sheet capacity.

The timing reflects growing commercial adoption. Provable Markets reported 4.2M orders during Q2 2026, up 91% quarter over quarter, with $33B in executed notional across 398M shares. June alone reached $30.1T in order notional and $14.9B in executed notional, while first-half activity touched nearly 20,000 unique securities. Those are company-reported figures, but the network density is difficult to ignore.

That network expanded further with the addition of eSecLending, Goldman Sachs, ING, and State Street in July. DTCC's 2024 annual report also confirms that Provable Markets helped NSCC complete the first novation of a pre-existing bilateral stock loan into its Securities Financing Transaction (SFT) Clearing Service. This is the infrastructure work that makes markets more efficient after front-end innovation has captured the headlines.

Matt Cohen, Co-founder and CEO, brought deep trading and market structure experience to the company. Historical Co-founder Thomer Gil helped establish the business, while Ruben de Vries, CTO, contributed expertise in cryptography and open-source engineering. Together, the team built infrastructure designed to work with regulated market rails rather than treating them as obstacles.

The Series B follows an $8M Series A led by Dialectic Capital Management in 2024, with INKEF Capital and Anthemis participating. The new funding will support commercial, product, and engineering hiring, deeper connectivity, product expansion, and international growth.

The broader market signal extends beyond another fintech financing. Institutions responsible for brokerage and post-trade infrastructure are backing a platform designed to make securities finance less fragmented, more automated, and easier to clear. The next stage is no longer proving the infrastructure works. It is demonstrating how much of the market can move across it.

Pangram Labs

Pangram Labs just raised $9M in seed funding, with Menlo Ventures leading through the Anthology Fund. The company is pursuing a difficult promise: when language costs almost nothing to produce, people still need to know what came from a person, a machine, or a combination of both.

That promise has moved well beyond suspicious essays. Quora, Google Classroom, Substack, and LessWrong are among the users and integrations Menlo highlighted. NewsGuard uses Pangram in a system that identifies more than 3,000 AI content farms. The market is no longer asking whether synthetic text exists. It is asking who can measure it without turning an unusual sentence into a false accusation.

Max Spero, Co-founder and CEO, and Bradley Emi, Co-founder and CTO, have the right experience for that challenge. Max Spero led active learning initiatives at Nuro after building machine learning products at Google. Bradley Emi led deep learning research at Absci and worked on Tesla Autopilot's core computer vision team. They met as Stanford freshmen and built the company around a problem many platforms had overlooked.

The timing is notable. Pangram recently launched Pangram 4 alongside an image detection research preview. According to the company, the model identifies 99.66% of AI-generated documents on internal benchmarks while maintaining a 0.0041% false-positive rate across a 2M-document human test set. A University of Chicago study evaluating an earlier Pangram system also reported near-zero error rates within its testing framework.

That distinction matters because AI detection has spent years struggling with false positives. A single incorrect accusation can quickly turn technical performance into a human consequence. Pangram treats false positives as one of the highest-cost errors, continually retraining its models against the difficult edge cases that challenge detection systems.

The platform is evolving into an authenticity layer rather than a single-purpose detector. Pangram offers browser scanning, APIs, plagiarism tools, support for more than 20 languages, and integrations across education and recruiting. Pangram 4 also distinguishes fully generated text from AI-assisted and mixed-author writing, a closer reflection of how people actually create content today.

Menlo's investment thesis extends beyond text. Images and video represent the next frontier, and Pangram already has an image detector in research preview. The company now faces the challenge of keeping pace with frontier models, humanization tools, changing platform behavior, and users determined to test every boundary once detection becomes consequential.

The broader signal reaches beyond a single funding round. Investors are increasingly treating authenticity infrastructure as a foundational category rather than a supporting feature. As the internet learns to manufacture language at scale, the next competitive advantage may belong to the companies that can make provenance just as scalable.