Top Tech Startups in Silicon Valley in 2026

GAOTek Inc. is a leading US based supplier of test and measurement equipment for fiber optic, telecommunications, networks, PSTN, CATV, environment, chemical and bio-medical test and measurement instruments.

AirJam's current products provide low-code components for web services. With just 3 lines of javascript code, you can add features like graphs, store locator, calendar bookings, and more to your website

We're an early stage security startup founded by 2 experienced technical leaders from Tessian (former Head of Eng and former Lead Architect). Our product helps security teams quickly and accurately detect intrusions in their cloud environment using canaries. We're Series A stage and about to ramp up the company from 24 to 32.

Agentic Operating Procedures for your ERP. Execute at machine speed, learn from every exception, and improve with every transaction.

Karlon Group provides enterprise-grade fractional finance & accounting, data analytics and investor relations support services to bootstrapped, venture-backed, and private equity owned companies at various stages of growth. We bring decades of strategic and operational finance & accounting experience, partnering with businesses across a range of industries, from SaaS to consumer to financial services. Our fractional CFO franchise prioritizes close partnership, excellence, and integrity above all in our approach to advising clients on their most critical finance & accounting challenges.

Amigo partners with healthcare organizations to deploy robust AI infrastructure that directly serves patients and providers. Our agents handle clinical workflows and patient engagement across the entire journey: pre-visit intake, care navigation, post-visit care plans, patient monitoring, and more. We own outcomes, not just delivery. For our customers, we're responsible for agent performance: clinical safety, continuous improvement, measurable patient outcomes. Agents operate autonomously within bounded clinical domains, with clear scope and handoff protocols. That scope expands as we validate performance across populations. We're backed by Tier 1 investors like General Catalyst, GSV Ventures, SVA, and CohoVC. Our work is validated with leading academic medical institutions. Our agents have reached 3M+ patient encounters and are on track to 10x this year.

Vision: At Living Stones Foundation, we envision a world where every individual and community thrives with hope, dignity, and opportunity. Our vision is rooted in the belief that through sustainable initiatives, collaborative efforts, and a commitment to positive change, we can create a global landscape where socio-economic disparities diminish, and the inherent potential of every person is realized. Mission: Our mission at Living Stones Foundation is to empower communities, inspire change, and foster innovation. We strive to be a catalyst for positive transformation by actively engaging in sustainable projects, strategic partnerships, and leveraging our diverse expertise. Through a holistic approach that transcends conventional boundaries, we aim to uplift and empower individuals, organizations, and churches, making a lasting impact on the fabric of society.

Prime Intellect democratizes AI development at scale. Our platform makes it easy to find global compute resources and train state-of-the-art models through distributed training across clusters. Collectively own the resulting open AI innovations, from language models to scientific breakthroughs.

Ando is building AI-native workforce infrastructure for shift-based work, starting with highly accurate AI-generated demand forecasting and autonomous labor allocation. Labor is one of the largest and least modernized systems in the economy. Most workforce tools are static, rules-based, and UI-driven. They create schedules, but they do not understand demand, uncertainty, or real-world tradeoffs. The result is wasted labor, constant manual intervention, and unstable hours for workers. This is not a scheduling UI problem. It is a systems problem: forecasting under uncertainty, constrained optimization, feedback loops, and learning from noisy production data. Models must operate in the wild, adapt continuously, and balance business, worker, and operational constraints. Our core intelligence layer combines demand modeling, optimization, and human-in-the-loop signals to improve allocation decisions over time, compounding into a persistent labor graph across skills, availability, reliability, and performance.