Today, we’re excited to share what we’ve been building at ThirdAI Automation, and to announce our $3M seed funding round, co-led by Endiya Partners and Capria Ventures.

We’re using this capital to accelerate product development, expand our teams across India, Japan, and the US, and scale deployments with semiconductor equipment manufacturers and fabs.

RCA in the age of AI - where downtime is real

Semiconductor fabs run on thousands of tightly sequenced steps across dense networks of tools, sensors, and inspection systems. When a critical tool goes down, the cost shows up immediately in downtime, yield loss, and missed output.

The challenge isn’t lack of data, it’s that the evidence is fragmented and noisy, and the “why” is rarely explicit. RCA is still largely manual, often taking 20–40 hours per incident, relying on tribal knowledge and trial-and-error, at a time when experienced engineering talent is increasingly scarce.

Tool vendors are a crucial leverage point in this ecosystem: they’re accountable for tool uptime and field performance, and improvements in diagnostics can scale across every customer fab running that platform. Embedding causal intelligence at the equipment layer helps vendors deliver faster triage, fewer escalations, and more reliable tools across their installed base—not just at a single site.

The “why” gap: prediction isn’t diagnosis

Industrial analytics has made meaningful progress, but much of the market still focuses on:

• Anomaly detection (“something looks off”)

• Prediction (“this might fail soon”)

Those are useful. But when production is already disrupted, teams need something different:

Causation.
A system that can answer: What caused this? What evidence supports it? What should we check next?

That’s the gap ThirdAI is built to solve.

Introducing ThirdAI: Causal AI for root cause analysis at the equipment layer

ThirdAI is a semiconductor intelligence platform that applies causal AI to troubleshoot tool and process failures, so engineers can move from failure to resolution faster, with more confidence.

Our system unifies equipment logs, sensor streams, images, service/field reports, and technical documentation into a single causal-intelligence layer. On top of that, we provide an RCA copilot that maps true cause-and-effect relationships, helping teams pinpoint root causes instead of chasing symptoms.

We believe the highest-leverage place to deploy this intelligence is where uptime and yield are won or lost: the equipment layer, and by partnering directly with tool vendors, each integration can scale across many fabs.

What this funding enables

With Endiya and Capria’s support, we’re focused on three things:

1. Expand across fabs and tool-vendor environments: scaling deployments, integrations, and measurable outcomes

2. Scale the product: from RCA workflows to broader intelligence across tool lifecycle, service, and field issues

3. Grow the team:  across engineering, applied ML, and customer delivery in India, Japan, and the US

We’re grateful to Endiya Partners and Capria Ventures for backing this mission, and to our customers and partners who’ve trusted us in high-stakes production environments.

What’s next

Our wedge is root cause analysis, because it’s the highest-pain, highest-urgency moment. From there, we’re expanding the same causal-intelligence layer across the broader tool and operations lifecycle: from troubleshooting to prevention, service, and continuous improvement.

Our long-term vision is to build an operating system for industrial operations, where AI continuously reasons over complex data to guide decisions across the manufacturing lifecycle, helping teams improve uptime, yield, and resilience in the systems the world depends on.

If you’re a toolmaker, fab operator, or industrial leader facing these challenges—and you want to explore causal AI for RCA and troubleshooting, we’d love to talk.