Telescope Innovations (TELI) investor relations material

Business model and markets

• Vancouver-based spin-out combines AI/ML, robotics, automation, sensors and chemistry expertise to automate chemical development; ~40 employees, including 30 PhD chemists, chemical engineers or software engineers.

• Business spans contract research, proprietary platforms and products, and self-driving laboratories (SDLs) for biopharma, high-value chemicals and clean energy.

• SDLs run 24/7 with minimal human interaction; direct deployments target large pharma and chemical firms, while subscription services target smaller pharma companies and CROs.

• Management estimates process development and scale-up costs pharma $700M and takes 3–3.5 years; SDLs could reduce cost 10–20x and shorten timelines by up to a year.

Commercialization and products

• SDL product launched in Q1 2026; three systems sold and installed, including two for Pfizer; KPBMA selected the platform for its Seoul training and feasibility site.

• One system installed at a major European pharma customer, with a second ordered; management expects 6–10 additional platform sales next year, versus three in 2026.

• DirectInject-LC (DI) enables real-time liquid chromatography analysis and is sold through Mettler Toledo; Asahi Glass signed a development contract and OEM agreement for a product planned for release next year.

• ReCRFT lithium carbonate purification and room-temperature lithium sulfide production are patented technologies being offered for licensing; a U.S. lithium purification project is underway, and reagent-free battery recycling is also in development.

• Management sees potential worth hundreds of millions of CAD from domestic production of chemical building blocks, through direct CRO work or licensing to CRO partners.

Technology and industry rationale

• Physical AI software designs experiments; robots dose and run reactions, while analytical and sensor tools track reaction progress, yields and impurities across multi-step processes.

• Management says pharmaceutical approval requires impurities below 0.1%; automation is intended to improve process control, data quality and productivity while reducing manual error.

• Differentiation rests on integrating expert chemistry teams into automation platforms tested under customer-use conditions; resulting process, visual, analytical and sensor data may also serve AI developers.