Artificial intelligence is moving into the corners of industry that no horizontal platform has ever been able to reach: the scheduling logic of professional sports leagues, the procurement inbox of a global manufacturer, the permit workflows of a city government, the dispatch board of a plumbing franchise at 2 a.m. The companies doing it most consequentially are not building generalist tools and hoping someone finds a use case; they are building the precise operational layer that a specific industry has been running on manual workarounds for decades. From voice AI for home service trades to geospatial intelligence for state governments, from AI rings that capture your thinking to procurement agents that run on your ERP, these are the scale-ups rewiring vertical workflows from the inside out.
Companies are listed in alphabetical order. This list is non-exhaustive.
1. BROCCOLI
Headquarters: San Francisco, CA | Total Funding: ~$24.2M
The home services trades are one of the largest and most fragmented segments of the U.S. economy, and one of the most underserved by technology. Plumbing, HVAC, and electrical companies operate at high call volume, with customer interactions that follow predictable patterns: booking appointments, dispatching on-call technicians, qualifying emergency jobs, following up on open estimates, and renewing memberships. Most of this work still runs through human CSR teams that are unavailable after hours, slow during peak volume, and expensive to scale.
Broccoli builds AI voice agents designed specifically for the trades. Its platform handles inbound calls around the clock, books jobs directly into ServiceTitan and Housecall Pro, dispatches on-call technicians for after-hours emergencies, and runs outbound campaigns for membership renewals and estimate follow-ups, all in a voice the company describes as indistinguishable from a trained human CSR. The quality assurance layer reviews 100% of calls and scores performance, identifying lost revenue and reclassification opportunities across every interaction. With $24.2 million raised, Broccoli serves both individual operators and multi-location PE-backed platforms, where it functions less as a call center replacement and more as a complete lead management platform. One partner reports that weekend bookings increased 900% after deployment. For an industry where missed calls are missed revenue and after-hours availability is a direct competitive advantage, Broccoli is not improving a workflow — it is replacing the constraint.
2. DIDERO
Headquarters: San Francisco, CA | Total Funding: ~$30M
Global procurement runs on natural language. A manufacturer receiving a purchase order, a packing list, a supplier delay notification, or a quote revision is receiving unstructured communication that a human has to read, interpret, and manually enter into an ERP system before any downstream action can occur. At scale, this loop consumes enormous amounts of time from operations teams who could be solving actual problems rather than transcribing information between systems. The problem compounds with supplier diversity: each vendor communicates differently, through email, WeChat, WhatsApp, PDFs, and phone calls, with no standardized data format in sight.
Didero is the AI procurement agent that reads that communication and puts the workflow on autopilot. Its platform sits as an agentic AI layer on top of a company’s existing ERP, ingesting incoming emails, purchase orders, and supplier messages, and automatically executing the corresponding updates and tasks without requiring human transcription. Founded by CEO Josh Spencer, the company raised $30 million in a Series A co-led by Chemistry and Headline, with participation from Microsoft’s M12, in February 2026. Named customers include Footprint, the sustainable packaging manufacturer. Spencer’s framing of the problem captures why AI is uniquely suited to solve it: the information was always there, in natural language, moving through existing channels. Didero learns to read it and act on it.
3. FASTBREAK AI
Headquarters: Charlotte, NC | Total Funding: ~$53.2M
Professional sports scheduling is one of the most constrained optimization problems in applied mathematics. A league with 30 teams, 82 games, 30 arenas, broadcast windows, and strict rules about back-to-back games, travel equity, and arena availability is not a problem that any human scheduler can solve optimally. The traditional approach is a multi-month manual process producing results that are often suboptimal on revenue, fan experience, and player welfare simultaneously.
Fastbreak AI is the global leader in AI-driven sports scheduling, now computing fixtures for over 65 professional leagues worldwide including the NBA, NHL, AFL, Serie A, MLS, LaLiga, Ligue 1, and Eredivisie. Founded in 2022 by CEO John Stewart, the company raised $40 million in a Series A led by Greycroft and GTMfund in November 2025, with participation from the NBA, NHL, TMRW Sports, and athletes including Patrick Cantlay, Kurt Kitayama, Larry Fitzgerald Jr., and Luke Kuechly, bringing total funding to $53.2 million. Its cloud solver generates multiple optimized schedule versions in hours against weighted constraints, enabling leagues to treat their schedules as strategic assets for revenue and broadcast rather than operational necessities. The company is now expanding into the $55 billion youth and amateur sports market through Fastbreak Compete, bringing professional-grade scheduling infrastructure to an industry that has historically had none.
4. FLORA
Headquarters: San Francisco, CA | Total Funding: Undisclosed (early-stage)
Creative work has a tool problem that is distinct from the tool problem in other industries. The challenge is not just that creative teams use too many disconnected software tools; it is that the tools themselves are not designed around how creative people actually work. Ideation, iteration, feedback, and production happen in a nonlinear, highly contextual loop that current creative software handles at the task level but never at the level of the full creative process. The result is that creative professionals spend a disproportionate amount of their time managing the logistics of their workflow rather than doing the work that only they can do.
FLORA is building a new generation of creative tooling and human-computer interaction designed specifically for how creative work actually happens. Its platform combines AI-powered creative assistance with interface design principles drawn from HCI research, building tools that adapt to a creator’s working process rather than requiring creators to adapt to the tool’s architecture. The company operates at the intersection of AI and HCI in a space where the design of the interaction layer matters as much as the capability of the underlying model, and where the market has largely been underserved by productivity software that was not built with the creative professional in mind. FLORA is building for a user who needs AI that augments creative judgment rather than replacing it with output — a distinction the creative tools market has consistently failed to make.
5. FORERUNNER
Headquarters: San Francisco, CA | Total Funding: ~$39M
State and local governments manage millions of buildings, miles of infrastructure, and complex compliance workflows with systems designed for a world where climate risk was lower and data was simpler. The American Society of Civil Engineers grades U.S. infrastructure a C-minus, and the gap between rising hazard exposure and government capacity to track, inspect, and respond to it is growing. FEMA’s constrained future capacity is pushing more responsibility to municipal governments at exactly the moment those governments most need modern tools to handle it.
Forerunner is the AI-powered geospatial platform giving governments a unified system of record for the built environment. Founded in 2019 by CEO JT White and COO Susanna Pho, the platform combines location data, inspection workflows, permit management, code enforcement, grant tracking, and public transparency tools into a single map-driven system that agencies can use in the field. The company raised a total of $39 million in February 2026, comprising a $26.3 million Series B led by Wellington Management and a previously unannounced $12.7 million Series A led by Union Square Ventures, with participation from SE Ventures and Citi Impact Fund. Forerunner currently serves more than 190 city, county, and state agencies across 26 states. Wellington’s climate-focused investment thesis reflects where the product lives: at the intersection of infrastructure, risk, and government capacity that has never had adequate technology until now.
6. GOVDASH
Headquarters: New York, NY | Total Funding: ~$42M
The U.S. federal government spends more than $700 billion annually on contracts with private companies. Most of that spending is accessible to any qualified business, but the process of identifying opportunities, reading solicitation documents, building compliant proposals, tracking performance, and managing the post-award lifecycle is so time-intensive that small and mid-size companies are effectively shut out. The result is a procurement market dominated by a small number of large contractors who have the operational bandwidth to compete at scale.
GovDash is the AI-native platform that levels that playing field. Founded by CEO Sean Doherty alongside Timothy Goltser and Curtis Mason, the platform automates the entire government contracting lifecycle: opportunity discovery, capture, proposal generation, compliance matrix building, and post-award contract management. The company raised a $30 million Series B led by Mucker Capital in January 2026, following a $10 million Series A in April 2024, bringing total funding to $42 million. In the year between rounds, GovDash grew revenue 16x and its customer base 18x to nearly 200 companies, scaling from 3 to 45 employees. Y Combinator-backed, the platform has processed hundreds of millions of tokens of solicitation content daily to produce audit-ready proposals in days rather than weeks. For any business that wants to work with the U.S. government but has been blocked by operational complexity, GovDash is the infrastructure that removes the barrier.
7. HANOVER PARK
Headquarters: New York, NY | Total Funding: ~$27M
Private fund administration is one of the most operationally complex and least automated workflows in financial services. Venture funds, hedge funds, private equity vehicles, and other alternative asset managers generate enormous volumes of accounting work: balance sheets, waterfall calculations, capital account reconciliations, investor allocations, and regulatory reporting. Most of this work is still done by CPA teams working in spreadsheets, validating outputs manually, and operating at the pace of human review cycles rather than the pace the asset management industry demands.
Hanover Park is the AI-native platform modernizing private fund administration. Its system uses machine learning to automate data aggregation and accounting workflows including balance sheets and waterfall calculations, while licensed CPAs validate outputs in real time rather than performing the underlying work from scratch. The company raised a $27 million Series A led by Emergence Capital, with participation from Lux Capital and Susa Ventures, in March 2026. In the 12 months preceding the raise, assets under administration grew from $1 billion to $15 billion, a validation that the market’s appetite for accurate, fast fund administration extends well beyond early adopters. The platform targets the $100 trillion asset management market, and its model of AI automation paired with human expert validation is well-suited to the regulatory environment: the output is machine-fast, but the responsibility chain remains intact.
8. LIO
Headquarters: New York, NY | Total Funding: Undisclosed (early-stage)
Operational data in most enterprises is trapped in the gap between systems. ERP platforms, WMS systems, TMS tools, and production databases each hold a piece of the operational picture, but they were not designed to share data in a format that operations teams can act on in real time. The result is that the people closest to operational decisions — plant managers, logistics leads, ops analysts — are working with stale, partial, or manually assembled data rather than a live view of what is actually happening across their organization.
Lio is the operational data management platform closing that gap. Its system integrates across the operational technology stack, normalizes data from disparate sources in real time, and surfaces a unified view of operational activity that teams can query, monitor, and act on without requiring data engineering resources to build custom pipelines. For operations-heavy businesses in manufacturing, logistics, and distribution, Lio functions as the connective tissue between systems of record and the people who need to make decisions based on them. The platform is designed for operators, not analysts: the interface is built for the speed and directness of operational decision-making rather than the exploration patterns of business intelligence tools. In a market where the gap between operational reality and operational data is measured in hours and dollars, Lio is closing it.
9. MODE
Headquarters: San Francisco, CA | Total Funding: Undisclosed (early-stage)
Industrial operations have a safety and efficiency problem that sits at the intersection of data abundance and decision latency. Sensors, cameras, equipment telemetry, and production systems generate enormous volumes of operational signals, but the people responsible for acting on those signals are typically working with dashboards that surface data after the fact rather than systems that identify and flag risks before they become incidents. The gap between what operations data says and when the right person sees it is where safety failures and efficiency losses live.
MODE is the AI platform for operational safety and efficiency in industrial environments. Its system processes operational signals from sensors, cameras, and equipment systems in real time, applies AI models trained on operational risk patterns, and surfaces alerts and recommendations to the right people at the right time in their existing workflows. The platform integrates with operational technology infrastructure rather than replacing it, adding an intelligence layer that turns reactive monitoring into proactive intervention. For safety managers and operations leaders in manufacturing, energy, and industrial logistics, MODE represents the difference between a system that tells you what happened and a system that helps you prevent what is about to happen. In an environment where a single incident can cost millions in downtime, liability, and regulatory exposure, earlier intervention compounds in value with every avoided event.
10. NATIONGRAPH
Headquarters: San Francisco, CA | Total Funding: ~$22.5M
Government procurement at the state and local level is one of the most opaque and fragmented markets in the United States. More than 110,000 agencies including school districts, water authorities, county governments, and special districts make purchasing decisions on cycles and timelines spread across thousands of portals, unstructured documents, and local databases with no central source of truth. For companies that want to sell to these agencies, the information asymmetry is enormous: large incumbents with dedicated government relations teams have known for years what smaller suppliers can only discover after the opportunity has passed.
NationGraph is the AI-native intelligence platform making public sector procurement transparent. Its system continuously ingests data and purchasing signals from state, regional, and local agencies, normalizes it into a structured intelligence layer, and surfaces it to suppliers with context on budget cycles, past vendor relationships, contract renewal windows, and procurement patterns. The company raised $18 million in a Series A led by Menlo Ventures in February 2026, with participation from Perplexity’s Fund, XYZ Venture Capital, and Reach Capital, bringing total funding to $22.5 million. CEO Kimia Hamidi describes the founding insight directly: “We started NationGraph because we saw firsthand how information asymmetry determines who wins government contracts.” The company’s analogy to Shopify is instructive: in the same way that Shopify democratized access to e-commerce distribution, NationGraph is democratizing access to the government as a customer.
11. NEWO.AI
Headquarters: San Francisco, CA | Total Funding: ~$32M
Small and medium-sized businesses lose revenue every hour their phones go unanswered. For a dental practice that misses a booking inquiry after 6 p.m., a restaurant that cannot take a reservation during a dinner rush, or a home services company that fails to qualify an emergency call on Saturday night, the gap between available and unavailable is directly measurable in lost appointments and jobs. Traditional answering services are expensive and inconsistent. Legacy IVR systems are so universally disliked that customers hang up rather than navigate them.
Newo.ai builds production-grade AI receptionists that handle calls, SMS, and WhatsApp messages around the clock, booking appointments, qualifying leads, and routing calls using what the company calls a Zero-Hallucination Architecture: multiple AI agents running in parallel to verify responses before delivery. Co-founded in 2023 by CEO Luba Rein alongside David Yang PhD, Alex Novitsky, and Viacheslav Seledkin, the platform runs on Google Vertex AI with Gemini 2.5 Flash for subsecond response times. Newo raised a $25 million Series A led by Ratmir Timashev, founder of Veeam, in February 2026, bringing total funding to $32 million. More than 15,000 AI agents have been deployed on the platform, revenue doubled in the final two months of 2025, and a partnership with IONOS now puts the platform in reach of 6.2 million SMBs globally. One orthodontics practice generated an extra $400,000 in a single quarter by catching missed after-hours bookings. For businesses that cannot afford to miss a call, Newo is the receptionist that never sleeps.
12. NORTHSLOPE
Headquarters: Denver, CO | Total Funding: ~$22M
Palantir’s AIP, Foundry, and Gotham operating systems have become the preferred AI deployment environment for some of the most demanding organizations in the world: aerospace manufacturers, energy producers, healthcare systems, and defense-adjacent enterprises. But owning a powerful AI operating system does not automatically produce mission-specific applications. The gap between the platform and the production outcome requires Forward Deployed Engineering: deep, on-site technical work that builds the exact application for the exact workflow. Most organizations either lack that capability internally or cannot access it fast enough.
Northslope was founded entirely by former Palantir Forward Deployed Engineers and is the first and only company named Palantir’s Vanguard: Elite partner. CEO Bill Ward’s founding thesis is blunt: “World-changing organizations don’t run on off-the-shelf software.” The company raised $22 million in a Series A co-led by Friends & Family Capital, founded by former Palantir CFO Colin Anderson, and Goldcrest Capital, founded by Adam Ross, Palantir’s first independent board member, in January 2026, following a year in which revenue grew nearly 7x. Current customer applications span cancer detection tools for physicians, mission optimization for aerospace manufacturers, and renewable energy production optimization. Palantir’s Global Head of Commercial has publicly backed the vision of “the Northslope plus Palantir” stack as the enterprise AI architecture of the next decade. For organizations that cannot build mission-specific AI applications from scratch, Northslope builds them instead.
13. OPS AI
Headquarters: New York, NY | Total Funding: Undisclosed (early-stage)
Logistics operations have a coordination problem at their core. The data that drives dispatch decisions, route planning, carrier selection, exception handling, and customer communication exists across TMS platforms, carrier APIs, customer systems, and operations team inboxes. Pulling these together into a coherent, actionable view requires either significant manual coordination or expensive custom integration work that most logistics operators cannot afford or sustain. The result is that operations teams spend a significant portion of their time managing the flow of information rather than acting on it.
Ops AI is the logistics operations automation platform that changes that equation. Its system connects across the operational data sources that logistics teams depend on, automates the routine coordination work that consumes the most time, and surfaces the exceptions, risks, and opportunities that actually require human judgment. The platform is designed to amplify the work of operations professionals rather than replace them: the goal is not autonomous logistics but operations teams that are faster, better informed, and less burdened by coordination overhead. For freight brokers, 3PLs, and shippers operating on thin margins where operational efficiency is a direct financial lever, Ops AI is building the automation layer that turns operational data into operational advantage.
14. SANDBAR
Headquarters: New York, NY | Total Funding: ~$36M
Every interface paradigm shift in personal computing has redefined interaction with information: from command line to GUI, from desktop to touchscreen, from touchscreen to voice. Each transition moved the interaction point closer to natural human behavior. The current transition to ambient, always-available AI is running into a hardware problem: the form factors built for voice AI so far require intrusive activation or carry social friction that limits where people will use them. Rings are different. They are the oldest wearable form factor in human history, ergonomically comfortable, socially universal, and always present.
Sandbar is building the AI ring. Its Stream device, co-founded by Mina Fahmi and Kirak Hong who previously worked together at CTRL-labs before its acquisition by Meta on neural wristband research, is a private voice ring and conversational interface designed for thought capture, AI assistance, and ambient interaction without requiring a screen. A first batch of pre-orders sold out after in-person demo events. The company raised $23 million in a Series A co-led by Adjacent and Kindred Ventures in March 2026, bringing total funding to $36 million following earlier rounds from True Ventures, Upfront Ventures, and Betaworks. Stream is targeting a summer 2026 ship with an initial focus on note-taking and brainstorming before expanding to broader agentic use cases. Coverage from the Wall Street Journal, Bloomberg, Wired, and Fast Company reflects the breadth of interest in what Fahmi describes as technology that extends rather than replaces human agency.
15. THE INTERACTION COMPANY (POKE)
Headquarters: Palo Alto, CA | Total Funding: ~$15M | Valuation: ~$100M
Every major AI assistant today is locked to a specific interface. ChatGPT requires the ChatGPT app. Claude requires Claude’s interface. Meta AI lives inside Meta’s platforms. For users who want an AI that acts on their behalf, the current paradigm requires context switching at precisely the moment when the benefit of AI assistance should be highest. The phone’s native messaging layer is where most people already live: if AI cannot come to where users are, most users will not go to where AI is.
The Interaction Company’s Poke is the AI agent that lives inside iMessage, SMS, Telegram, and WhatsApp, accessible from wherever a user is already texting without any app download or interface shift. Co-founded by Marvin von Hagen and Felix Schlegel, Poke launched publicly in March 2026 after emerging from a prior email AI product. The company raised $15 million in seed funding led by General Catalyst at a $100 million valuation, with participation from Village Global, Earlybird, and angels from Stripe, Dropbox, and OpenAI. In June 2026, Poke became the first third-party AI agent approved by Apple to operate on the Messages for Business platform, a milestone that required months of trust and safety validation. User count has grown 10x in two months following public launch. For an AI industry that has been asking users to come to it, Poke is the company going to the users.
This was a brief overview of the rapidly evolving AI vertical workflow application landscape. If there is a company you think belongs on this list, reach out to our editorial team and we will make sure they are included on the next one.
