Technology, Software & Semiconductors
Technology teams need AI that understands their stack, standards, customers, and production constraints.
AI use cases
Engineering copilots
Code, review, test, documentation, and operations tools tied to your repositories.
Developer support agents
Answer support, onboarding, API, and troubleshooting questions from docs and tickets.
Yield and design optimization
Use ML for fabrication, testing, hardware loops, simulation, and failure analysis.
Product analytics intelligence
Find churn, usage patterns, feature gaps, and customer health signals.
Security and incident workflows
Triage alerts, summarize incidents, draft postmortems, and route response tasks.
Internal knowledge systems
Search specs, RFCs, runbooks, tickets, docs, and customer conversations privately.
Selected work
Docs built for 8M+ developers
We built the official Thunder Client docs with static generation and fast markdown rendering.
An agent that learns from its own traces
The backend reviews execution traces, finds failure points, and improves its prompts through a controlled loop.
Local generation for full-stack apps
A private app generator that creates Next.js and Node builds, then validates and repairs its own output.
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