The context layer of AI

Celestral understands context to give human-like instructions to AI agents

Founders have backgrounds from:

Stanford
University of Michigan
Tesla
Electric Hydrogen
Dolby
FEATURES

Human-like intelligence for your AI

Context Capture

Understands the what, where and how of various work tasks from images, meeting conversations and conducted voice interviews to build a shared context layer.

Context Capture Diagram showing how images, meeting conversations, and voice interviews flow into a shared context layer

Autonomous Task Identification

Generates a list of pending actions like reports to be made, follow-up emails to be sent, products and features to be made, or modifications in priorities automatically based on that context.

Autonomous Task Identification diagram showing a clipboard generating a list of pending actions

Cross-Tool Integration

Connects with tools (e.g., Gmail, Notion, Cursor, Vercel) and utilizes the captured context to generate tailored prompts for AI agents to operate autonomously without needing manual prompt engineering.

Cross-Tool Integration diagram showing AI prompt branching to Email, Product Documentation, and AI agents

Adaptive Memory & Learning

Remembers preferences, priorities, work styles, best practices, decision parameters, etc. and continuously improves accuracy over time by creating and updating long-context memory.

Adaptive Memory & Learning diagram showing long-context memory growth over time
Testimonials

What Experts Say

See how Celestral AI can transform industries such as manufacturing.

"Spreadsheets and emails are the bane of my existence. If a hardware company contacts a manufacturer, the DFM (Design for Manufacturability) process often involves making changes to the product. Using AI to automate different aspects of this process is highly needed."
Tina Murray
Tina Murray
Senior PLM Consultant, sold manufacturing software for 32+ years
"Email is like a compost pile of information. At the prototyping stage, the needs of a hardware company are so broad that we exchange endless emails with manufacturers. We have to maintain a 'living document' to track the status of these communications."
Brad Brinson
Brad Brinson
Senior Mechanical Engineer, Meta AR, mechanical engineer for 30+ years
"Customers in the automotive space have very long product development lifecycles because of very high volume. It takes 2-4 years to go from design to production. Everything has to be very custom since components vary based on the car."
Bill Aston
Bill Aston
Director, Accenture, reinventing manufacturing lifecycles using AI
Team

Meet Our Founders

Madhav Goenka

Madhav Goenka

Founder & CEO

Stanford alum. Built and sold custom AI solutions to hardware companies. Worked at Tesla and has 3+ years of experience in the hardware space.

FAQ

Frequently Asked Questions

Find answers to common questions about Celestral AI