YC DATA · 6,287 COMPANIES · OCTOBER 2, 2026
FORMATION · FIRST SURFACED SPRING 2026

AIOps

Return to Signal
COOLED · SPRING 202685% confidenceObserved October 2, 2026Source: YC tagRadar flagged this 6 months early
The count
0.31×

18/652 → 6/707; -1.91 percentage points of formation share.

S14S19S22S24S25F26
The companies behind the signal — 6
Winter 2026
IncidentFox

AI SRE agents that automatically learn each customer’s system so they work just like an in-house engineer.

Winter 2026
Carrot Labs

The problem: AI has quietly become one of the largest and fastest-growing line items for companies. Spend is scattered across a dozen provider consoles that each show one number at the end of the month and nothing about why it moved. There's no unified view, and no way to trace a dollar back to the customer, feature, team, or even the pull request that caused it. Which customers are unprofitable once you subtract their AI costs? Which feature is quietly burning your Anthropic budget? Is this week's spike a runaway loop or real growth? How much did that AI-written PR actually cost to ship? Today teams reverse-engineer answers by exporting CSVs from each provider and stitching them together in a spreadsheet, and by the time they do, the money is already spent. What SuperPenguin does: SuperPenguin tracks AI spend across 14 providers (OpenAI, Anthropic, Google Gemini, Deepgram, Elev

Fall 2025
Kestrel AI

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.

Summer 2025
Adaptional

Adaptional is building agentic AI for insurance claims. Claims are 75% of every dollar in the $1T insurance industry -- and one of the most under-optimized areas, still managed by adjusters working hundreds of files by hand. We're changing this with AI claims review agents, already deployed at some of the major P&C carriers. In the future, claims will be powered by an intelligence layer that manages files and escalates actions to human adjusters. Adaptional is building the AI system that will be the foundation for every claims department across P&C insurance.

Summer 2025
Alter

Alter is a zero-trust identity and access control platform purpose-built for AI agents. It wraps every tool call in strong authentication, fine-grained authorization, and real-time guardrails, so agents can move fast without breaking things. Each request is verified at the parameter level, authorized against granular policies, executed with least-privilege access, and fully audited in real time. Unsafe actions, whether it’s a rogue DROP TABLE or a payment above policy limits, are blocked before they touch production. Behind the scenes, Alter manages credentials, issuing ephemeral, scope-narrowed access for every interaction, then rotating or expiring it in seconds. The result: no long-lived secrets, no blind spots, and no surprises in audit. With Alter, teams can move fast on AI agent initiatives while staying fully compliant with SOC 2, HIPAA, GDPR, and internal security standards

Summer 2025
Luminal

Luminal builds an ML framework and compiler that generates GPU code. Our stack 10x's model speed while simplifying deployment and cutting idle GPU costs Github: https://github.com/luminal-ai/luminal Discord: https://discord.gg/APjuwHAbGy

Inside AIOps

Developer Tools

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

Other / unclassified

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

Outside corroboration — does anyone else see this?

No comparable outside activity is connected yet.

Related formations
Developer Tools

25 completed-batch companies belong to both AIOps and Developer Tools, versus 5.8 expected by chance (4.3× enrichment; false-discovery-adjusted q=4.6e-9). This is a statistically distinctive co-membership, not a causal or containment claim.

LLM Application

6 completed-batch companies belong to both AIOps and LLM Application, versus 0.3 expected by chance (21.7× enrichment; false-discovery-adjusted q=0.000011). This is a statistically distinctive co-membership, not a causal or containment claim.

Infrastructure

14 completed-batch companies belong to both AIOps and Infrastructure, versus 3.5 expected by chance (4.0× enrichment; false-discovery-adjusted q=0.00029). This is a statistically distinctive co-membership, not a causal or containment claim.

Automation

6 completed-batch companies belong to both AIOps and Automation, versus 1.0 expected by chance (5.9× enrichment; false-discovery-adjusted q=0.015). This is a statistically distinctive co-membership, not a causal or containment claim.

Data Labeling

3 completed-batch companies belong to both AIOps and Data Labeling, versus 0.2 expected by chance (14.8× enrichment; false-discovery-adjusted q=0.028). This is a statistically distinctive co-membership, not a causal or containment claim.

Cloud Computing

4 completed-batch companies belong to both AIOps and Cloud Computing, versus 0.5 expected by chance (7.5× enrichment; false-discovery-adjusted q=0.049). This is a statistically distinctive co-membership, not a causal or containment claim.

Citation

Cambrian Signal, “AIOps,” publication yc-2026-10-02-semantic-v8, snapshot October 2, 2026.
cambrian.jafar.com/formation/aiops

AIOps · Cambrian Signal