Best Place To BuildSuyash Singh, GalaxEye | "If I can't build a deep tech startup at IITM, I can never do it." | Ep. 10
CHAPTERS
Suyash’s “always smiling” origin story (and why it mattered for leadership)
The host opens by noticing Suyash Singh’s constant smile, which becomes a gateway into his early leadership lessons at IIT Madras. Suyash explains how blunt feedback during the first Hyperloop orientation pushed him to consciously practice positivity and approachability.
From mechanical engineer to IITM Aerospace: corporate years, GATE, and choosing application-driven mastery
Suyash traces his path from a 2013 mechanical engineering graduation through a corporate stint, experiments like UPSC prep, and finally GATE to IIT Madras. He frames his master’s as a way to rebuild fundamentals and become domain-expert while staying application-oriented rather than purely research-focused.
The SpaceX Hyperloop spark: “If I can’t build deep tech at IITM, I can’t do it anywhere”
A friend’s mention of the SpaceX Hyperloop competition becomes Suyash’s inflection point. The mix of challenge, ambition, and a desire to prove that world-class deep tech can be built in India drives him to start something unprecedented on campus.
Building Avishkar Hyperloop at IITM: overcoming the Master’s–BTech culture gap
Suyash describes how initiating Hyperloop was less about the idea and more about navigating campus culture and access. He credits key enablers who took a chance on a master’s student and explains how the team eventually became a bridge between research-minded postgrads and innovation-driven undergrads.
From Hyperloop to GalaxEye: a non-linear leap into space (driven by a problem, not romance)
Suyash explains that space wasn’t his original passion—even as Agnikul was starting nearby. After graduating (2019) and working briefly in corporate roles, a concrete, compelling problem statement led him to found GalaxEye in 2021.
What GalaxEye does: consistent Earth imagery as a data company (clouds + night are the enemy)
GalaxEye positions itself as a data company that captures Earth imagery from space, focusing on the hardest constraint: availability. Suyash details why optical satellites fail under clouds and at night, and how inconsistent access prevents reliable “SLA-like” imagery for real applications.
Where satellite imaging creates value: the four application pillars
Suyash lays out the major buckets that Earth imagery powers today and why each can spawn many SaaS-like products. He emphasizes that downstream innovation is capped unless imagery becomes consistent and easy to interpret.
Deep dive: SAR + multispectral fusion—making radar data usable and optical data available
The conversation goes technical: radar sees through clouds and works at night but is unintuitive; optical is intuitive but inconsistent. GalaxEye’s bet is to combine SAR (microwave) with multispectral (visible/NIR) on the same satellite to close the “availability + interpretability” gap.
SAR fundamentals in plain language: bands, frequencies, and penetration tradeoffs
Suyash breaks down SAR bands (L, C, X, etc.) and how frequency affects penetration and use cases. The chapter connects physics to practical imaging outcomes: foliage penetration vs urban detail, and why some bands struggle with clouds.
Imagery as the next GPS-like platform shift: enabling new startups and automation
The host draws an analogy to GPS enabling Google Maps, ride-hailing, and quick commerce once accuracy improved. Suyash argues consistent imaging could similarly unlock a new layer of applications once the data becomes dependable and productizable.
Mission Drishti: the end-to-end satellite build process (idea → PDR/CDR → AIT → launch)
Suyash explains how a first satellite mission is engineered and de-risked using structured systems engineering. He outlines the full lifecycle from concept to preliminary and comprehensive design reviews, then assembly/integration/testing in space-like environments, highlighting why it took ~3.5 years.
Testing before space: POEM as an in-orbit experiment and a team learning milestone
To reduce risk, GalaxEye uses ISRO’s PSLV Orbital Experimental Module (POEM) to test critical subsystems in real orbit before the full satellite launch. Beyond validation, it helps the team experience real launch integration workflows end-to-end.
From one satellite to a constellation: revisit rates, coverage, and the 6–8 satellite roadmap
After Drishti, the plan is to replicate the platform into a mesh/constellation to increase revisit frequency and data density. Suyash shares a concrete expansion target over the next several years.
Earth imaging evolution and India’s space inflection: from V2 photos to 28–30 cm resolution and 2020 privatization
The episode zooms out to the history of Earth imaging (from grainy 1946 V2 photos to modern high-resolution imagery like Burj Khalifa) and India’s imaging capabilities (Cartosat ~28 cm). Suyash then frames 2020 as a pivotal policy shift that opened space to private players, catalyzing a startup wave.
How GalaxEye de-risks execution and scales the ecosystem: aerial testing, SpaceX inspiration, team-building, and investors
Suyash explains a frugal, engineering-led approach: miniaturize payloads, test on drones/aircraft/HAPS, run hundreds of flights, then go to orbit. He also discusses why SpaceX changed innovation norms (vertical integration, COTS vs space-grade), how GalaxEye builds teams with ISRO/DRDO advisory depth, and what convinces investors to fund deep-tech space bets in India.
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