YC data · 6,352 companies · October 22, 2026
Formation · First surfaced Fall 2025

Agentic AI Platforms

All formations
Accelerated · Fall 202589% confidenceObserved October 22, 2026Source: Description cluster · description-only
The count
2.50×

24/802 → 46/615; +4.49 percentage points of formation share.

S14W19S22F24W26F26
The companies behind the signal — 46
Fall 2025
Hypercubic

Agentic AI for Mainframe Operations and Modernization. Hypercubic is an AI-native platform for mainframe operations and modernization. We help enterprises understand and modernize their mission-critical legacy systems. About 70% of the Fortune 500 companies still rely on them to run their core business applications in banking, insurance, telecom, airlines, retail, and more. These systems, originally built in the 1960s–90s, still power trillions in global infrastructure today but have become increasingly opaque as original developers retire or leave the workforce. We are pioneering a new class of intelligence capable of understanding, reasoning about, and rebuilding the world’s foundational infrastructure. Learn more at hypercubic.ai

Fall 2025
Kestrel AI

AI Agents for Platform Engineering. Kestrel is the AI automation layer for platform engineering teams. Platform teams use Kestrel to automate incident response, cloud provisioning, CI/CD, security, and developer requests across their stack. Kestrel turns natural-language prompts into deterministic, production-ready workflows with 40+ integrations, 200+ pre-built actions, and support for custom HTTP and webhook actions. Developer-first, with a CLI, Python SDK, and MCP server to manage workflows from where platform teams already work.

Fall 2025
Metorial

Agentic infrastructure to power AI-native companies.. Metorial gives every employee, agent, and AI client in your company one place to connect tools and skills. Governance, access control, and tracing included.

Fall 2025
MOVEdot

AI Agents for Hardware Engineering. Our agents run hardware engineering tasks that normally take hours or days in just a few minutes, allowing engineers to process 100x more data and information. Our platform allows hardware engineers to orchestrate agents for tasks such as analyzing failures across entire test campaigns, pulling the right data and KPIs from their databases, checking how conditions (like temperature or load) affect performance and reliability, and then document findings in reports and dashboards.

Fall 2025
Scott AI

The planning layer for teams that build with coding agents. Coding agents made writing code fast. But 6 engineers in a room will probably still disagree on what needs to be built. Scott AI is a planning workspace where engineering teams align on what to build before their coding agents start building it.

Fall 2025
Deeptrace

AI agents for on-call. At Deeptrace, we’re building AI agents that investigate and resolve production alerts end-to-end. Deeptrace cuts through the noise, pinpoints root causes instantly, and gives engineering teams back what they need most: the freedom to build instead of firefighting. In production, we're already seeing a reduction in time spent triaging, investigating, and resolving alerts with some of the fastest growing companies in the world.

Fall 2025
dari.dev

The Routing Layer for AI Agents. We let developers run more agents while keeping your token bill low. We train custom models to determine how we can maintain performance while reducing your token bill. Integrate into your own apps, or use our router with Claude Code, Codex, or any agent of your choice.

Fall 2025
Hyperspell

Your Company Brain. Hyperspell is your Company Brain. AI agents are brilliant and clueless. They ace any test and still have no idea how your company works. Hyperspell connects your tools and synthesizes documents and conversations into a live, permissioned context graph. Any agent can read from it and write back to it like a filesystem, with every fact traced to source.

Fall 2025
Nessie

A shared context layer for you, your team, and your agents.. Knowledge work is being restructured by AI. Strategy happens in Claude. Research happens in ChatGPT. Building happens in Claude Code. The people defining the next decade of work are already thinking with AI every day. But none of that thinking compounds. Every session starts from zero. The reasoning behind decisions, the context behind strategies, the evolution of ideas across hundreds of conversations - all of it evaporates. Nessie is the infrastructure that makes it permanent. We auto-sync AI conversations and agent traces across every major provider - ChatGPT, Claude, Gemini, Perplexity, Claude Code, OpenClaw, Codex, and more - and turn them into a context layer that is queryable, reusable, and shareable by you, your team, and your agents. No browser extension. No manual capture. Your thinking flows in automatically and comp

Fall 2025
Nexus

We help non-technical teams build AI agents without engineers. Nexus enables non-technical teams in large organizations to build production-ready AI agents without code.

Inside Agentic AI Platforms

Other / unclassified

Measured-window members of Agentic AI Platforms that could not be assigned to a narrower shared YC tag or industry without forcing a classification.

Engineering, Product and Design

A primary internal company segment within Agentic AI Platforms, derived deterministically from the shared yc industry “Engineering, Product and Design”. This is a classification of current window members, not a causal layer or a separate time trend.

Infrastructure

A primary internal company segment within Agentic AI Platforms, derived deterministically from the shared yc tag “Infrastructure”. This is a classification of current window members, not a causal layer or a separate time trend.

Analytics

A primary internal company segment within Agentic AI Platforms, derived deterministically from the shared yc tag “Analytics”. This is a classification of current window members, not a causal layer or a separate time trend.

Cybersecurity

A primary internal company segment within Agentic AI Platforms, derived deterministically from the shared yc tag “Cybersecurity”. This is a classification of current window members, not a causal layer or a separate time trend.

Sales

A primary internal company segment within Agentic AI Platforms, derived deterministically from the shared yc industry “Sales”. This is a classification of current window members, not a causal layer or a separate time trend.

Outside corroboration — does anyone else see this?

No comparable outside activity is connected yet.

Related formations
AI Agent Infrastructure

85 completed-batch companies belong to both Agentic AI Platforms and AI Agent Infrastructure, versus 3.1 expected by chance (27.8× enrichment; false-discovery-adjusted q=7.9e-114). This is a statistically distinctive co-membership, not a causal or containment claim.

AI Agent Platforms

22 completed-batch companies belong to both Agentic AI Platforms and AI Agent Platforms, versus 1.9 expected by chance (11.9× enrichment; false-discovery-adjusted q=2.4e-16). This is a statistically distinctive co-membership, not a causal or containment claim.

Engineering, Product and Design

36 completed-batch companies belong to both Agentic AI Platforms and Engineering, Product and Design, versus 14.6 expected by chance (2.5× enrichment; false-discovery-adjusted q=0.0000097). This is a statistically distinctive co-membership, not a causal or containment claim.

Developer Tools

29 completed-batch companies belong to both Agentic AI Platforms and Developer Tools, versus 12.6 expected by chance (2.3× enrichment; false-discovery-adjusted q=0.00054). This is a statistically distinctive co-membership, not a causal or containment claim.

Workflow Automation Assistants

8 completed-batch companies belong to both Agentic AI Platforms and Workflow Automation Assistants, versus 2.0 expected by chance (4.0× enrichment; false-discovery-adjusted q=0.024). This is a statistically distinctive co-membership, not a causal or containment claim.

Infrastructure

18 completed-batch companies belong to both Agentic AI Platforms and Infrastructure, versus 7.9 expected by chance (2.3× enrichment; false-discovery-adjusted q=0.024). This is a statistically distinctive co-membership, not a causal or containment claim.

Similarly named categories — not necessarily the same thing

These share a word with “Agentic AI Platforms” but are tracked as separate categories. The real overlap below is the actual share of Agentic AI Platforms’s companies also found in that category — not a guess.

Citation

Cambrian Signal, “Agentic AI Platforms,” publication yc-2026-10-22-semantic-v8, snapshot October 22, 2026.
cambrian.jafar.com/formation/agentic-ai-platforms