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Executive Summary: Top American AI Companies to Watch [2026]

  1. Nvidia: Advanced GPUs and AI Chips
  2. Microsoft: Cloud and Enterprise AI Solutions
  3. IBM: AI Apps via Watsonx & Hybrid Cloud
  4. Google (Alphabet): AI-Enabled Chrome Enterprise Solutions
  5. Amazon: Cloud-Based AI Services via AWS
  6. Meta: Open-Source Language Models
  7. Adobe: AI Tools for Creative Automation
  8. Arista Networks: Cloud Networking for AI Workloads
  9. Elise AI: Conversational AI for Real Estate & Healthcare
  10. OpenAI: Generative AI Models (e.g., GPT)
  11. Anthropic: Ethical Language Models for Enterprise
  12. Perplexity: AI-Powered Search & Q&A Platform
  13. Runway: Generative AI Tools for Creatives
  14. xAI: Artificial General Intelligence (AGI) and Alignment-Safe AI Systems
  15. DataRobot: Enterprise Automated ML Platform
  16. SambaNova: Integrated AI Hardware & Software
  17. Cerebras: Wafer-Scale AI Hardware Systems
  18. Mythic: Low-Power AI Inference Hardware for Edge
  19. H2O.ai: Open-Source AutoML Platforms
  20. Scaled Cognition: AI Agents for Decision Support
  21. Gaxos.AI: Scalable Cloud & AI Infrastructure
  22. Two AI: Privacy-Preserving AI for Document Processing
  23. Truewind: AI-powered Accounting Automation
  24. Ultravox: Enterprise Speech AI Platforms
  25. Pin AI: On-Device Personal Intelligence Platform
  26. Patronus AI: AI Risk & Compliance Validation
  27. Resolve AI: Workflow & Conversational Automation
  28. Boon: AI Logistics Platform for Commercial Fleets
  29. Contextual AI: Context-Aware NLP for Enterprise Search
  30. Braintrust: LLM Observability & Prompt Management

 

 

Frequently Asked Questions (FAQs)

1. Which American AI companies lead the global market in 2026?

Nvidia, Microsoft, OpenAI, Google, Amazon, and Meta lead global AI innovation through advancements in chips, foundation models, and enterprise platforms.

2. What differentiates American AI startups from established tech giants?

American AI startups focus on specialized domains like evaluation, agentic systems, and on-device AI, while tech giants dominate foundational infrastructure. Startups like Anthropic, Perplexity, and Runway attract large funding due to focused, high-value applications.

3. How are American AI companies addressing safety and regulation concerns?

US-based AI companies are prioritizing model transparency, data provenance, and responsible deployment practices. Anthropic, OpenAI, and IBM have established internal alignment frameworks and external partnerships to comply with evolving standards like the US AI Executive Order (2025).

How We Selected these 30 American AI Companies & Startups

The data in this report comes from StartUs Insights’ Discovery Platform, covering over 9 million startups, scaleups, and tech companies globally. We identified the 30 companies in this list based on founding year, technology readiness, and employee count.

We further evaluated each company based on estimated revenue, total money raised, and proprietary innovation metrics that reflect their real-world influence within the global tech ecosystem. The final list combines established leaders shaping the industry’s direction and emerging challengers making headlines with breakthrough innovations.

30 Growing American AI Companies & Startups to Watch in 2026

1. Nvidia – Full-stack AI Solutions

Technology company Nvidia offers full-stack AI solutions that combine enterprise-grade software, faster infrastructure, and better pre-trained models into a single, cloud-native platform. It combines GPU-accelerated computing in data centers and edge locations for AI workflows to go from start to finish, including training models, making predictions, and deploying them.

 

 

Nvidia NIM lets developers deploy generative AI models faster without updating any existing codebases. Its inference technologies make processing faster and more efficient.

Nvidia’s cybersecurity AI offers improved threat identification with scalable, real-time inference that goes beyond older solutions. The company offers a foundational platform for trusted, scalable AI adoption in a dynamic market. This makes it easier to deploy workloads and get insights quickly.

For the fiscal year 2025, the company’s revenue was USD 130.5 billion, up by 114% from a year ago. Founder and CEO Jensen Huang attributes this to the high demand for the Nvidia Blackwell GPU, as reasoning AI scales up the need for more computing power.

2. Microsoft – AI-enhanced Software Services

Tech giant Microsoft offers AI-powered software services through a set of apps and platforms that use generative artificial intelligence. The software solutions make the workflows of consumers, developers, and businesses easier.

The Copilot ecosystem lets users create, summarize, analyze, and give instructions in Word, Excel, PowerPoint, Outlook, Teams, Windows, and Edge. This makes it possible for all of these business tools to function together.

Azure AI‘s enterprise infrastructure offers document intelligence, optical character recognition, and proprietary data extraction. This allows businesses to use safe, compliant, and scalable AI models.

Further, Microsoft’s Power Platform uses AI-powered agents, low-code tools, and built-in visualizations to help users who aren’t specialists quickly create automated workflows and analytics apps for corporate operations.

The company is using its investment in OpenAI to advance AI development. Moreover, OpenAI’s recent transition to for-profit pushed Microsoft’s valuation to reach more than USD 4 trillion. This strengthens Microsoft’s position as a leader in the creation of AI-enhanced work and productivity products.

3. IBM – AI-based Enterprise Applications

  • Location: Armonk, NY
  • Notable News: Patent licensing brings in around USD 400 million for IBM

IBM‘s watsonx platform and hybrid cloud architecture provide AI-based corporate apps. These applications provide businesses the tools to design, deploy, and manage AI models on a large scale.

watsonx.ai enables model creation, and watsonx.data regulates lakehouse data management. IBM combines AI development workflows with a safe, collaborative space that links trusted business data. This automates model lifecycle procedures and enforces rules for training, tuning, deployment, and monitoring for regulated sectors to use AI in production.

The company also utilizes a hybrid cloud backbone built on IBM z17 and LinuxONE 5. On-chip AI acceleration and optimized system design let it do up to 450 billion AI inference operations per day with low-latency replies for both transactional and analytical workloads.

IBM z17 also has autonomous security AI that finds and responds to threats. Additionally, agentic orchestration capabilities with hundreds of automation agents enable IT and business operations to run more smoothly.

Further, IBM holds the most AI intellectual property, with 1211 AI utility patents in 2023 and a long-term portfolio that brings in around USD 400 million a year from patent licensing. This makes the company more defensible and trustworthy in mission-critical deployments.

4. Google (Alphabet) – AI-enabled Products

  • Location: Mountain View, CA
  • Notable News: Plans to invest USD 15 billion to develop AI infrastructure in Vishakapatnam, India.

Tech giant Google provides AI-enabled enterprise software through Chrome Enterprise. It integrates the Chrome operating system, browser, devices, and the Gemini platform to deliver secure and efficient workplace computing.

 

 

The technology combines cloud-based management with Gemini’s advanced multimodal AI models. This allows employees to automate workflows and analyze large volumes of enterprise data from diverse business apps.

Gemini facilitates the orchestration of custom and prebuilt agents for research, coding, and administrative tasks. This offers a no-code workbench for employees across different departments to create and deploy agents tailored to their needs.

Moreover, Google enables scalable and personalized AI-driven productivity, grounded answers, and seamless automation, while enforcing strong security and compliance controls.

This protects sensitive business data and streamlines business operations. Consequently, it empowers organizations to accelerate outcomes and transform workflows through trusted generative AI agents.

Google plans to invest USD 15 billion to develop AI infrastructure in Vishakapatnam, India. This includes a gigawatt-scale data center, new subsea cables, and clean energy to power India’s AI future.

Additionally, Google announced a two-year plan to invest USD 5 billion in Belgium to improve the country’s AI infrastructure.

5. Amazon (AWS) – Cloud-based AI Services

  • Location: Seattle, WA
  • Notable News: AWS doubles its investment in the AWS generative AI innovation center with USD 100 million.

Amazon develops a suite of cloud-based artificial intelligence services through Amazon Web Services. The company’s offerings enable enterprises to build, deploy, and scale intelligent applications across diverse domains.

The platform features tools like Amazon SageMaker for model training and deployment, and Amazon Bedrock for generative AI development. Amazon Comprehend is an NLP tool. All tools are accessed through a unified cloud environment.

The company’s technology orchestrates data storage, compute power, and pretrained models within AWS infrastructure. This allows developers to integrate AI capabilities directly into business workflows.

AWS is doubling its investment in the AWS generative AI innovation center, with USD 100 million to continue innovating alongside customers.

6. Meta AI – Open-Source LLM

  • Location: Menlo Park, CA
  • Notable News: Meta landed USD 29 billion to finance its large-scale AI data center buildout across the US.

Technology company Meta provides an open-source LLM platform. The company’s LLM enables the comprehension and generation of natural language for a range of applications like image generation, accurate information provision, and inquiry resolution.

 

 

The platform streamlines operations for users across various industries by processing vast amounts of textual input and generating relevant, context-aware outputs in real time. It utilizes Meta’s most recent Llama model.

Llama improves the time-to-value by allowing users to complete duties more efficiently while maintaining flexibility through open-source architecture and scalable deployment options.

Meta landed USD 29 billion to finance its large-scale AI data center buildout across the US. This is one of the largest financings in the sector as demand for AI-ready infrastructure surges.

7. Adobe – AI-powered Creative Space

  • Location: Mountain View, CA
  • Revenue: USD 5.87 billion in the second quarter of 2025

Software company Adobe offers AI tools to create an AI-powered creative area. Adobe Sensei and Adobe Firefly are two of these tools that use AI and machine learning to automate difficult tasks like object detection, image tagging, and content personalization.

 

 

The company also adds smart features to creative tools like Photoshop, Illustrator, and Acrobat – like subject selection and predictive analytics.

Adobe Firefly also incorporates a generative AI platform for users to make photos, movies, text effects, and 3D designs from basic text prompts. It supports easy idea generation and safe content creation for businesses through corporate APIs.

The platform speeds up the creative process with accuracy and control. The Firefly Boards enable collaborative brainstorming, turning images into videos, AI-powered video editing, and new bulk image editing tools.

Adobe recorded a record revenue of USD 5.87 billion in the second quarter of the fiscal year 2025. This represents an 11% year-over-year (YoY) growth. Adobe’s CFO, Dan Durn, reiterates the company’s continued investments in AI innovations across customer groups.

8. Arista Networks – Cloud AI Infrastructure

Arista Networks offers cloud networking solutions that enable large data centers, campuses, and dispersed routing environments to connect to data at high speeds and scale.

The company’s platform uses a cloud-native operating system that gives users real-time visibility of their network and programmable automation. It also provides full security through the use of data analytics and software-driven controls.

Arista Networks provides the 7800R4 Series modular switches for accelerated computing, large-scale virtualized and cloud networks, and service provider backbones. They enable dense 800 Gbps network systems and 3.2 Tbps hyperports for ultra-capacity distributed AI clusters and large data center environments.

The R4 portfolio, which spans fixed and modular routers, also supports scalable two-tier leaf-and-spine architectures. It integrates the EOS operating system for Layer 3 features and enables EVPN, VXLAN, MPLS, and SR/SRv6 protocols to optimize for AI and high-throughput workloads.

Arista client-to-cloud model further lets on-premises, hybrid, and cloud environments to work together without issues. It also supports dynamic workloads and multi-site deployment with low-latency switching and routing.

The company’s total revenue grew to USD 2.3 billion, up 27.5% YoY, amid the AI and cloud expansion.

9. Elise AI – AI for Healthcare & Property Management

EliseAI offers a multi-channel conversational AI platform that automates tasks for housing and healthcare organizations.

The startup leverages proprietary machine learning to handle voice, text, email, and chat communications. It allows users to schedule appointments, ask questions, engage with leads, book tours, and follow up on payments 24/7.

In the last year alone, EliseAI managed 11 million leads and facilitated nearly 70 million leasing communications for over 415 property owners.

Elise integrates with existing electronic health record (EHR), practice management system (PMS), and revenue cycle management (RCM) systems. This ensures safe and accurate patient data with HIPAA and SOC 2 Type II compliance, without disrupting the existing workflow.

EliseAI enables businesses to run more smoothly, save money on payroll and other costs. It also replaces human, repetitive communication with accurate and context-aware automation to enhance customer experiences in both sectors.

The startup raised USD 250 million in Series E funding led by Andreessen Horowitz (a16z). It also includes participation from new investor Bessemer Venture Partners and existing investors Sapphire Ventures and Navitas Capital.

10. OpenAI – Conversational AI

OpenAI develops advanced AI models for a variety of applications, from natural language understanding to text and image generation. The startup received the innovation spotlight in the AI ecosystem after releasing its AI conversational interface, ChatGPT, built on generative pretrained transformers (GPT).

It processes natural language inputs to generate coherent and context-aware responses. The GPTs rely on large-scale machine learning models trained on diverse datasets to understand intent, infer meaning, and produce human-like dialogue across different domains.

OpenAI generated USD 3.7 billion in annual revenue last year and is projected to bring in USD 12.7 billion this year in revenue.

With the large data processing requirements, OpenAI is expanding its capabilities by teaming up with Oracle and Softbank to build five new data centers in the US. This is also part of its Stargate initiative set up in January 2025 with the purpose of investing USD 500 billion over four years in AI infrastructure, primarily in the US.

11. Anthropic – AI Model Developer

  • Founding Year: 2021
  • Location: San Francisco, CA
  • Funding: Completed a series F funding round with USD 13 billion

Anthropic is an AI safety and research startup that develops AI systems that focus on reliability, interpretability, and control. Anthropic’s family of AI models under the name Claude includes an AI conversational system that answers questions, generates content, assists with reasoning, and more.

https://www.youtube.com/watch?v=FDNkDBNR7AM

The company builds models that respond to human feedback and adhere to clear reasoning processes. This reduces the risks of unwanted outputs. The AI models follow a constitutional AI framework and evaluate their output against a set of principles that guide the AI’s behavior.

Anthropic completed a series F funding round with USD 13 billion. This financing valued Anthropic at USD 183 billion post-money.

Recently, Microsoft included Claude models in its 365 Copilot. This brings Claude to millions of enterprise users through Microsoft’s productivity platform.

12. Perplexity – AI-based Search Engine

Perplexity builds an AI-powered search engine that takes questions in natural language and returns answers synthesized from web sources, with citations. It combines NLP and retrieval-augmented generation (RAG) to search trusted online sources and synthesize concise answers.

 

 

The engine continuously updates results to reflect current information and enhances reliability by prioritizing evidence-based data. This reduces the time spent on manual research while ensuring that outputs remain transparent and verifiable.

Further, Perplexity released its Comet browser that combines its AI search engine with the highly familiar browsing experience offered by Google’s Chrome browser. Comet’s Chromium framework supports popular extensions and bookmarks while introducing intelligent tools to enhance productivity, research, and multitasking.

Perplexity’s valuation reached USD 18 billion after the latest funding round that raised USD 100 million.

13. Runway – Audiovisual Generator

Runway offers an audiovisual generator platform that allows subscribers to use multimodal AI systems to make videos using text, photos, or video clips. The platform enables producers to add different types of materials and then use AI to make changes.

It allows changes like changing the lighting, the art direction, the style of the subjects, or eliminating things from the video clip. The platform also enables virtual staging, character performance mapping, virtual try-on capabilities, and node-based workflows.

These features enable users to chain together various creative phases and provide fine-grained control over a wide range of content kinds. As a result, it enables teams and individuals to improve content creation workflows and access cutting-edge design tools for easier and faster creative processes.

Runway recently released its Gen-4 AI generator that enables precise generation of consistent characters, locations, and objects across scenes.

The company also secured over USD 300 million in Series D funding led by General Atlantic with participation from Fidelity Management & Research Company, Baillie Gifford, NVIDIA, and SoftBank Vision Fund 2.

14. xAI – Conversational AI

  • Location: Burlingame, CA
  • Funding: Latest funding round raised USD 10 billion at USD 200 billion

xAI develops Grok, a conversational AI model that adds advanced reasoning and multilingual capabilities to real-time search functions and a wide range of application contexts.

The startup features native tool use, rapid performance, and accuracy across languages. It also offers scalable access tiers like SuperGrok and Grok 4 Heavy, which have higher rate limitations and more intelligence for more demanding use cases.

xAI enables scientific discovery and broadens understanding through AI-driven products that improve research outcomes, decision-making, and productivity. Simultaneously, Grok For Government customizes its suite to meet the needs of the US government.

The company’s latest funding round raised USD 10 billion at a USD 200 billion valuation. It was backed by investors like Valor Capital, Qatar Investment Authority, and Prince AI.

15. DataRobot – Enterprise AI

DataRobot offers an AI lifecycle platform that allows businesses to create, deploy, and manage AI solutions on a large scale. It combines automated machine learning procedures, continuous model monitoring, and governance tools.

The platform supports advanced analytics and AI governance that makes it easy for technical and business teams to work together while staying compliant. It reduces the need for human interaction and improves decision-making processes in complicated business settings by automating model construction and operationalization.

DataRobot was valued at USD 6.3 billion based on the Series G funding that closed in 2021. Secondary marketplaces indicate the DataRobot valuation has shrunk substantially to USD 500 million as of Q1 2025.

 

 

16. SambaNova – Reconfigurable Dataflow Unit Chips

  • Location: Palo Alto, CA
  • Notable News: Intel is in talks to acquire SambaNova to expand its AI capabilities

SambaNova offers an AI platform, SambaNova Suite, that enables businesses and governments to set up large-scale generative and agentic AI models.

The platform combines proprietary Reconfigurable Dataflow Unit (RDU) chips with software tools like SambaStudio for managing the AI ecosystem and SambaNova Composition of Experts (CoE) model architecture.

The SambaNova Suite enables high-speed inference on big models and scalable performance with automated workload management. It also offers safe data handling with private model ownership.

The startup lets businesses handle both structured and unstructured data in one place and deploy it easily on-premises or in the cloud. This allows companies to get faster, more accurate, and cheaper AI operations while keeping complete control of their AI infrastructure.

Intel is in talks to acquire SambaNova to expand its AI capabilities.

17. Cerebras – Inference Cloud

Cerebras develops Inference Cloud, a fast AI inference platform that provides real-time answers for generative AI workloads and complicated language models. It utilizes proprietary hardware, like the Wafer-Scale Engine and CS-3 system, which handle more than 3000 tokens per second. This allows faster processing than GPU-based solutions for latency and scalability.

The company’s platform speeds up the deployment process and allows customers to launch complex open-source models like Llama, Qwen, and GPT-OSS with rapid API access. It also supports whole reasoning chains in less than one second for more advanced applications.

The startup gets rid of the complexity of distributed computing and maintains accuracy with 16-bit precision. It provides businesses, academic institutes, and governments with the tools they need to design and run powerful AI applications quickly and easily.

Cerebras raised USD 1.1 billion Series G at a USD 8.1 billion valuation. The funding round included participation from investors like Tiger Global, Valor Equity Partners, and 1789 Capital.

18. Mythic – Analog Matrix Processors

Mythic leverages proprietary analog compute-in-memory technology to speed up AI applications with a single hardware and software platform. The company’s M1076 analog matrix processor puts AI parameters directly on the chip to avoid memory bottlenecks and speed up inference.

The processor achieves up to 25 TOPS per chip for edge deployment, which makes it possible to quickly and efficiently process neural networks in robotics, defense, and consumer sectors. The platform uses up to 3.8 times less power, works 2.6 times faster, and costs 10 times less than traditional digital inference chips.

The startup raised USD 13 million, led by investors like Atreides Management, DCVC, and Lux Capital.

19. H2O.ai – AI Democratization

H2O.ai offers an enterprise AI platform that combines generative and predictive AI. It enables businesses to make secure, purpose-driven GenAI apps using their own private data.

The platform uses agentic workflows, which use both structured and unstructured data. It deploys autonomous agents that reason, predict, and optimize across areas including customer care, fraud detection, regulatory reporting, and workflow automation.

The platform allows deployment in the cloud, on-premises, or air-gapped. It also offers compliance-friendly safeguards, automatic human-in-the-loop oversight, and real-time risk and transparency features due to its open-source design.

These characteristics make it easier to connect to existing business systems using APIs and allow implementation in regulated fields like finance, telecom, and government.

The company raised USD 72.5 million in a Series D funding round, bringing the total funding to USD 147 million.

20. Scaled Cognition – Agentic AI

Scaled Cognition offers logical, manageable AI models that substitute as topic experts in real-world situations. It builds smart foundation models that work as dependable digital agents, doing specific jobs in a variety of fields while including factual reasoning and interpretability.

The startup makes sure that everything is in line with business needs and regulatory norms by allowing direct control and modular modification at scale. This makes decision-making clear and operations more efficient.

Scaled Cognition gives businesses the tools they need to speed up value discovery, lower risk, and make addressing complicated problems easier by giving them strong AI models.

The startup raised USD 21 million in a seed funding round led by Khosla Ventures.

21. Gaxos.AI – AI-powered Gaming & Entertainment

  • Location: Roseland, NJ

Gaxos.AI uses blockchain and AI to offer a gaming platform. It uses AI to make gameplay unique for each player. The platform allows players to customize their avatars, gain achievements, and play games that are connected to each other in a virtual world.

Gaxos.AI’s platform enables AI-driven game progression that includes challenges that change based on how well players do and blockchain integration. This protects the ownership of in-game items and awards while opening up new monetization channels for game developers and publishers.

This way, the platform improves player engagement and makes the most of revenue potential by merging AI with blockchain. This will create a dynamic and secure gaming ecosystem that is good for both players and producers.

22. Two AI – Multilingual Language Models

Two AI provides a multilingual language model, SUTRA. The model makes inferences in over 50 languages.

SUTRA utilizes a dual-transformer architecture, which combines small, distilled second-layer models, to improve performance and save costs across dispersed applications.

It also uses quantitative and domain-specific modeling to assist with conversational, instructional, reasoning, and search tasks. The startup makes it easy to automate tasks, deploy them in modules, and engage with them in real time. This enables businesses to run more smoothly and make decisions faster.

The startup raised USD 20 million in a seed round with investments from Jio and NAVER.

23. Truewind – AI-powered Bookkeeping

Truewind offers an AI-powered bookkeeping and financial modeling solution for startups. It automates transaction coding, reconciliation, and workpaper production. The solution links directly to live general ledger data to keep user finances up to date and correct.

Further, it automatically sorts transactions, marks exceptions with low confidence, and gives complete audit-ready accrual packages with explanations and confidence scores for review. This cuts accounting time and aids in matching deposits.

Truewind raised USD 13 million in Series A funding co-led by Rho Capital and Thomson Reuters Ventures. It also has participation from Pathlight Ventures. This brought Truewind’s total funding to over USD 17 million.

24. Ultravox.ai – AI Voice Platform

  • Location: Seattle, WA

Ultravox.ai provides an open-weight spoken language model that understands and responds to voice input in real time by processing speech directly instead of turning it into text. It cuts down on system components to speed up and make conversation more natural.

The startup’s technology performs better than old cascaded pipeline voice systems by lowering latency and operational expenses. It provides developers with a simple stack for making AI agents. This enables them to get documents to learn more and perform better.

25. Pin AI – Personalized AI

Pin AI builds a decentralized on-device personal intelligence platform that turns each person’s digital footprints into personalized executive assistance. It utilizes hybrid models that combine local device processing with secure cloud computation to keep interactions private and personalized.

The platform allows users to give permission for different data sources, like emails, calendars, and messages, to be accessed. Its large language model and knowledge graph organize and analyze this information to find insights and actions relevant to the situation.

Pin AI keeps an open and user-controlled environment where people have the capability to take back control of their data and get AI services that are both safe and very relevant.

The startup raised USD 10 million in pre-seed funding with participation from the venture capital firm Andreessen Horowitz.

26. Patronus AI – AI Evaluation Platform

Patronus AI provides an automated AI evaluation platform for enterprise teams. It uses real-time and offline evaluation workflows to verify the performance of large language models, create adversarial test cases, and compare LLMs.

The platform combines ready-to-use assessment models and custom assessors for users to score and improve generative AI products. It finds hallucinations, toxicity, PII leaks, and context quality of various datasets and domains.

Additionally, the platform identifies comprehensive issue modes and automatically produces explanations. It offers flexible hosting options for both cloud and on-premise needs. It also has enterprise-level security and API response times as low as 100 ms.

Patronus AI ensures measurements are accurate and in line with human judgment. It provides comparisons and trace summaries for LLM systems and facilitates scalable iterative development.

The startup raised USD 17 million in Series A funding led by Notable Capital with participation from Lightspeed Venture Partners and Datadog.

27. Resolve AI – Autonomous Software Development

Resolve AI offers an AI Production Engineer that automates software operations by mapping environments and linking data from application code, infrastructure, and observability tools.

The platform looks into incidents on its own by linking real-time operational signals and quickly creating root cause analysis. It also responds to alarms by performing just-in-time automated runbooks and taking actions to fix the problem that are backed up by evidence.

The product offers a dynamic knowledge graph that refreshes with every deployment or system modification. It works with cloud and telemetry systems and fixes problems in just a few minutes.

The startup offers engineering teams more time to come up with new ideas. This lowers the mean time to resolve (MTTR) and the amount of work that needs to be done.

Last year, Resolve AI raised USD 35 million in seed funding led by Greylock.

28. Boon – AI Agent for Construction Management

Boon provides an AI workflow platform for commercial fleets. It automates logistics tasks, including data entry, dispatch, and load sourcing.

The platform integrates with current software systems to make workflows more efficient and reduce human errors. It also learns how to do things by hand and takes over repetitive chores in just a few days. This frees up teams to focus on more important projects.

Further, the platform features fuel optimization, automated billing cycles, and compliance agents that check data in real time. These capabilities save costs and time spent on order processing and audits for fleet owners. It also automates backhaul recommendations and improves customer satisfaction.

The startup raised a total of USD 20.5 million in funding backed by Marathon and Redpoint.

29. Contextual AI – Enterprise AI with Context

  • Location: Mountain View, CA
  • Funding: USD 80 million in Series A funding

Contextual AI builds enterprise language models that reduce hallucinations to offer businesses accurate and context-aware AI capabilities. The company ensures high accuracy through a unified context layer that connects enterprise-specific data, documents, and workflows to LLM reasoning.

The startup’s technology uses proprietary retrieval-augmented generation (RAG) and contextual grounding to create dynamic and personalized AI agents. These agents perform complicated tasks like technical support, policy Q&A, and engineering operations.

The startup’s platform retains complete auditability, strong data encryption, and security measures that meet industry standards and compliance certifications. Contextual AI thus allows businesses to customize AI solutions while keeping operations safe, trusted, and open.

Contextual AI raised USD 80 million in Series A funding led by venture capital firm Greycroft.

30. Braintrust – AI Observability Platform

Braintrust provides an AI observability platform to create and test apps that use LLMs. It allows developers to perform thorough evaluations, manage prompts, and monitor data pipelines.

Braintrust’s architecture offers automated and human-in-the-loop evaluation, batch testing across data sets, and live performance monitoring. The platform also offers versioning, error tracking, and cost analysis that make each deployment more open and manageable.

The Loop agent speeds up rapid optimization and synthetic data generation. At the same time, integrations with nine main frameworks and a browser-based workflow make it easier to log ingestion, granular permissions, and compliance needs.

The startup raised USD 36 million in Series A funding, bringing the total funding to USD 45 million.

Explore the Latest AI Startups & Scaleups to Stay Ahead

With billions of dollars in funding and widespread usage across enterprise, creative, and operational processes, the companies featured in this report serve as examples of how AI is being monetized at scale. With thousands of emerging technologies and business innovations, navigating the right investment and partnership opportunities that bring returns quickly is challenging.

With access to over 9 million emerging companies and 20K+ technologies & trends globally, our AI and Big Data-powered Discovery Platform equips you with the actionable insights you need to stay ahead of the curve in your market. Leverage this powerful tool to spot the next big thing before it goes mainstream. Stay relevant, resilient, and ready for what is next.