In Q1 2026, AI companies absorbed $242 billion in venture capital. That’s 80% of all global VC funding for the quarter. The money is going to startups that have identified specific, high-value enterprise workflows and are replacing them with autonomous AI agents.
The shift is structural. Previous generations of enterprise software added tools on top of existing processes. AI agents are being built to own the process outright. Customer service tickets get resolved without a human touching them. Legal contracts get reviewed before a lawyer opens the file.
Code gets written, tested, and deployed while the engineering team focuses on architecture. That last use case is either exciting or deeply unsettling, depending on how much of your job involves writing boilerplate.
Here are 30 startups making that shift, organized by the enterprise software categories they are targeting.
Coding and developer tools
1. Anysphere (Cursor)
Valuation: $29.3B. ARR: $500M.
Anysphere builds Cursor, the AI-powered IDE that has become the default coding environment for a large share of enterprise engineering teams. Founded in 2022 by a group of MIT graduates, it grew from a niche developer tool into one of the fastest-scaling software products in recent memory.
The product competes directly with GitHub Copilot but goes considerably further, handling multi-file edits, full codebase coordination, and integrated agent loops that can carry a task through from prompt to pull request.
2. Cognition AI (Devin)
Valuation: $26B.
Cognition builds Devin, the AI software engineer capable of planning, coding, testing, and deploying entire applications without human direction. The company made headlines in 2026 when it disclosed that 89% of its own production code is written by Devin.
That’s less a marketing claim and more an extraordinary proof of concept. Founded in San Francisco in 2023 by Scott Wu, Steven Hao, and Walden Yan, it counts Peter Thiel and the Collison brothers among its backers. The investor roster alone signals that serious people believe this is real.
3. Replit
Valuation: $9B in January 2026, up from $3B just four months earlier.
Replit’s browser-based coding environment lets users generate full-stack applications from natural language prompts, covering frontend, backend, databases, and deployment in a single session.
Founded in 2016 by Amjad Masad, Haya Odeh, and Faris Masad, it started as a tool for learning to code. It has since become a serious infrastructure for app development at scale. Tripling your valuation in a single quarter is, by most measures, a good quarter.
4. Blitzy
Valuation: $1.4B. Series A: $200M.
Blitzy modernizes legacy enterprise codebases at scale. The platform orchestrates thousands of AI agents working in parallel to understand, modify, and validate code across systems often built decades ago.
For enterprises sitting on aging infrastructure that nobody wants to touch, this sits somewhere between a technical solution and a therapy session. Either way, it addresses a genuine problem that conventional refactoring has been failing to solve for years.
5. Lovable
Valuation: $6.6B. ARR: $200M.
Lovable converts natural language descriptions into working software products. It targets the gap between people who have product ideas and people who can build them, and has found a substantial market on both sides.
The $200M ARR figure puts it among the fastest-scaling developer tools of the current cycle. The name may be optimistic, but the numbers are not.
Customer service and support
6. Sierra
Valuation: $15.8B. Raised: $950M. Series E.
Sierra was founded in 2024 by Bret Taylor, former co-CEO of Salesforce, and Clay Bavor, former VP at Google. It hit $100M ARR in 21 months, one of the fastest ramps in enterprise software history.
Sierra’s agents handle complex customer interactions across voice, chat, email, and WhatsApp, with pricing based on outcomes rather than seats. Customers include SoFi, Ramp, Brex, Cigna, and Rivian, spanning heavily regulated industries where agent errors carry real consequences.
Outcome-based pricing is either the future of enterprise software or the source of a very stressful quarterly review, possibly both.
7. Decagon
Decagon is Sierra’s closest competitor in AI-powered customer support automation. It targets enterprise support teams with agents designed to resolve tickets end-to-end, with a focus on the quality standards most enterprise buyers require before removing humans from the loop.
The company has attracted significant funding and is expanding across technology and financial services. In a category where the incumbent is valued at $15.8B, being the credible alternative is a reasonable place to be.
8. Intercom
Founded in San Francisco in 2011, Intercom built one of the dominant customer messaging platforms before the current AI wave. It has since integrated AI agents deeply into its product and made a more credible transition to an AI-first model than most companies in its cohort.
It’s the option most enterprise buyers reach for when they want production-grade agents without ripping out existing infrastructure. Sometimes the advantage of being around longer is simply that everyone already has your login details.
Legal
9. Harvey AI
Valuation: $5B. Raised: $600M+.
Harvey builds AI agents for legal professionals, handling research, document analysis, contract review, and drafting across major law firms. Founded in 2021 in San Francisco, it trained its models on legal-specific datasets to a depth that general-purpose LLMs do not reach.
Backed by Sequoia and Kleiner Perkins, with a client roster of top-tier firms, Harvey is the clearest category leader in legal AI. Law is a sector that has resisted automation for a long time. Harvey is making a persuasive case that the resistance was about capability, not principle.
10. Legora
Valuation: $5.55B. Series D: $550M.
Legora represents one of the largest funding rounds in legal AI to date, reflecting how seriously enterprise law firms and legal departments are taking agent deployment in production workflows.
The company focuses on research and drafting workflows that consume the most billable hours. The scale of funding signals that investors believe legal AI has moved past the pilot stage. At $550M Series D, the pilots are done.
11. Caseflood.ai
YC-backed.
Caseflood targets the operational and administrative layer of legal work, the work that sits below the billable hour. Its agents handle client intake, case analysis, and ongoing client engagement, replacing functions traditionally staffed by paralegals and junior associates.
For smaller and mid-size firms that cannot staff an AI team of their own, this is a meaningful cost reduction delivered without requiring a technology overhaul.
Healthcare
12. Hippocratic AI
Raised: $402M.
Founded in 2022 by Munjal Shah and clinical co-founders, Hippocratic builds AI agents for patient-facing healthcare workflows: appointment scheduling, post-discharge follow-ups, chronic disease management, and medication reminders.
The company has prioritized safety certification and HIPAA compliance from day one, which matters considerably in a sector where a hallucinating agent can cause genuine harm. Based in Palo Alto, it is one of the few AI companies that appears to take the phrase ‘do no harm’ literally.
13. Ambience Healthcare
Raised: $243M. Series C.
Ambience builds an AI operating system for clinical workflows, focused primarily on documentation. Clinicians spend a disproportionate share of their time on administrative writing rather than patient care.
Ambience agents handle that documentation burden in real time during consultations. The company is backed by OpenAI and has deployed across major health systems. Giving doctors their time back is, as pitches go, a fairly easy one to make.
14. Nabla
Valuation: $5.3B. Series E: $316M.
Based in Paris, Nabla takes an audio-first approach to clinical AI, recording and summarizing medical conversations to generate structured documentation automatically.
It has expanded aggressively across Europe and North America and is one of the few European AI health companies operating at this scale. The French origins make it a notable example of frontier AI development that did not require a San Francisco zip code.
15. Stedi
Raised: $50M.
Stedi handles the administrative plumbing of healthcare: the transaction processing layer connecting providers, payers, and clearinghouses. The company standardizes fragmented data flows and converts inconsistent inputs into usable formats.
The result is less manual reconciliation and faster payments. Less visible than clinical AI, but the healthcare system runs on this layer. Fixing it is about as glamorous as fixing the pipes, and about as necessary.
Finance and compliance
16. Corti
Valuation: $605M. Series C: $80M, led by IVP.
Corti was originally built for emergency medical dispatch, listening to calls in real time and surfacing clinical decision support. It has since expanded into healthcare claims processing, generating documentation to maximize approval likelihood automatically.
Based in Copenhagen, Corti is one of the stronger European entrants in healthcare AI. Starting in emergency dispatch and ending up in claims processing is an unusual trajectory, but the underlying skill, understanding high-stakes conversations in real time, transfers cleanly.
17. Variance
Series A raised.
Variance builds AI agents for compliance and risk workflows, ingesting regulatory documents, mapping requirements to internal policies, and monitoring compliance gaps in real time.
Compliance monitoring is one of the cleaner agent use cases: the inputs are well-defined, the rules are structured, and the cost of a missed requirement is measurable. It’s the kind of task that humans find tedious and agents find straightforward.
18. Resistant AI
Series B: $25M. 10x ARR growth since Series A.
Based in Prague, Resistant AI builds fraud and financial crime detection models for banks, fintech platforms, and AI agents operating inside financial workflows.
As AI agents gain the ability to initiate payments and transactions autonomously, detecting when those agents are being manipulated becomes a meaningful security problem. Resistant AI is one of a small number of companies working on that specific challenge before it becomes a headline.
Enterprise knowledge and search
19. Glean
Valuation: $7.2B. Series F: $150M.
Founded in 2019 by former Google engineers, Glean builds AI-powered enterprise search that surfaces information across more than 100 connected tools. It has since extended into action, with agents that execute workflows based on discovered context.
For knowledge workers spending hours each day locating information that already exists somewhere in the company, Glean addresses a genuine and quantifiable productivity problem. Finding the document is the job. This is the tool that does it.
20. Parallel
Valuation: $2B. Raised: $230M.
Parallel builds web-search infrastructure designed specifically for AI agents, providing the real-time retrieval layer that agentic systems need to access and act on current information.
As autonomous agents proliferate across enterprise workflows, a reliable and structured search layer becomes infrastructure rather than a feature. Parallel is building that layer for the agent-first era rather than retrofitting something built for humans.
Sales and GTM
21. Mercor
Revenue: $100M, reached in under two years.
Mercor builds AI recruiting agents that source, screen, and engage candidates autonomously, handling the full hiring workflow from initial search through to candidate engagement.
The revenue trajectory puts it among the fastest-scaling AI agent companies across any category. Recruiting has been slow and expensive for a long time. Mercor is one of the cleaner demonstrations of what happens when you automate a process people have tolerated rather than enjoyed.
22. Caretta
YC-backed.
Caretta’s AI agent joins live sales calls in real time and helps reps handle objections as they arise. It operates in the moment, surfacing competitive intelligence, pricing information, and suggested responses while the conversation is happening.
For enterprise sales teams dealing with complex, multi-stakeholder deals, that’s a meaningfully different kind of support from what post-call analysis tools offer. It’s the difference between a coach in your ear and a coach reviewing the tape the next morning.
Workforce and operations
23. Sona
Raised: $45M.
Sona targets frontline industries including retail, hospitality, and healthcare with AI-driven scheduling, forecasting, and payroll tools. The company addresses the operational complexity of large hourly workforces, where scheduling errors translate directly into labor cost overruns and coverage gaps.
It’s a good example of AI agents entering workflows that enterprise software has historically served poorly. The operational stakes are high, the data is messy, and the margin for error is thin.
24. Aisera
Founded in 2017, Aisera builds a multi-agent orchestration platform for enterprise IT, HR, and customer service, automating ticket resolution, employee self-service, and back-office workflows. It has been named a Gartner Visionary in the Magic Quadrant for AI applications in ITSM.
Production deployments at NJ Transit, OmniTRAX, and Big 5 Sporting Goods demonstrate the platform’s capacity for high-volume, governed workflows at scale. Being founded in 2017 is, in agentic AI years, practically ancient. The enterprise procurement credibility that comes with it is real.
25. Skygen AI
Skygen builds an agent platform for process automation that goes beyond trigger-based workflow tools. Its agents execute multi-step processes, apply AI-driven logic, and continue workflows autonomously across connected systems.
For enterprises that have already extracted most of the value from conventional no-code automation tools, Skygen represents the next tier of capability. The step from ‘if this then that’ to ‘figure out what to do and then do it’ is larger than it sounds.
AI observability and infrastructure
26. Braintrust
Raised: $80M.
Braintrust monitors deployed AI systems for reliability, drift, and quality degradation, building the observability layer that production AI agents genuinely need. Traditional APM tools do not understand model behavior.
Enterprises deploying agents at scale have largely been operating without adequate visibility into what those agents are actually doing. Braintrust is filling that gap at a moment when the need is acute and the alternatives are thin. The APM category was built for software that behaves predictably. Agents do not always do that.
27. Inferact
Valuation: $800M. Seed: $150M, backed by Andreessen Horowitz and Lightspeed.
Inferact commercializes vLLM, the widely-used open-source project for efficient LLM inference, making AI agents faster and less expensive to run in production.
As inference cost becomes a meaningful constraint on agent deployment at scale, the companies solving that problem become increasingly central to how the ecosystem operates. Faster and cheaper inference is the kind of improvement that benefits everyone downstream, which is a reasonable place to build a business.
Vertical and specialist agents
28. Rebar
Series A: $14M.
Rebar has built an AI operating system for commercial construction suppliers, using computer vision to analyze blueprints and automatically identify, categorize, and count equipment. It reduces quote generation time by 60 to 70%.
Rebar doubled its ARR in the first six weeks of 2026. Construction is an industry that has been largely untouched by modern software, where the baseline for comparison is a person doing this by hand with a spreadsheet. The improvement doesn’t require much selling.
29. Imbue.
Raised: $230M.
Founded by Kanjun Qiu, one of the few female CEOs leading an AI agent unicorn, Imbue builds coding agents designed around reasoning rather than pattern matching. The bet is that today’s agents fail not because they lack knowledge but because they cannot think through complex, multi-step problems reliably. Based in San Francisco, Imbue has NVIDIA and Founders Fund among its backers, which is a reasonable signal that the thesis has legs.
30. Denki.
YC-backed.
Denki automates internal auditing for SOX compliance and financial regulation, handling control processes, evidence collection, walkthrough interviews, and testing. Every step is recorded for full traceability.
It integrates with existing platforms, including AuditBoard, Workiva, and ERPs, removing the procurement friction that kills most compliance-adjacent software before it gets deployed. For any finance team staring down a SOX audit, the appeal is obvious. Nobody has ever described internal auditing as the fun part.
Final word
The common thread across every category is specificity. The companies attracting the most capital and hitting the fastest revenue milestones picked a single, high-value workflow, understood it deeply, and built agents that could own it end-to-end.
The horizontal platforms are coming. The vertical specialists are winning now.
For enterprise software vendors, the threat is structural. For the companies on this list, the opportunity is generational. Every AI leader watching from the sidelines should be asking not whether agents will reach their category, but whether they are ready when they do.
The $242 billion that went into AI in Q1 2026 is a bet on a new way of running enterprise operations. The 30 companies above are where a significant portion of that bet has landed.
The companies on this list are moving fast. The question is whether financial services is keeping up…
On October 1 in New York, the Agentic AI in Financial Services Summit brings together 300+ engineers, executives, and domain experts to work through exactly that. Production-grade deployment, model governance, regulatory-aligned architecture, and the real tension between moving quickly and staying auditable.
If the startups in this article are on your radar, this is the room where the people deploying against them in financial services will be.
