operational: people who can help you get your work done
personal: people who can help you grow personally and professionally
strategic: people who help you shape your future direction and goals
Use this framework to get your message out into the market.
| Category | Have | Need | How? |
|---|---|---|---|
| Scanning | • PhD research in 3DGS & world models | ||
| • deep literature review pipeline; awareness of SOTA in generative world models, offline RL, and policy learning framework. | • Contacts in warehouse/logistics robotics who can share real pain points; | ||
| • industry insiders who know where current sim-to-real solutions fail | • Attend robotics industry events (ICRA, CoRL, RSS); join robotics Slack/Discord communities | ||
| • Reach out to warehouse automation engineers on LinkedIn | |||
| Ideating | • Conception-X cohort for peer feedback | ||
| • Academic supervisor and labmates for technical validation | |||
| • Strong technical vision for composable world models | • Product-minded co-founders or advisors who can stress-test the business model | ||
| • Robotics end-users who can validate the "composable" and “interpretable” value prop | • Pitch at Conception-X sessions and get structured feedback | ||
| • Book discovery calls with robotics teams at 3PLs and fulfillment centers | |||
| Customers | • Understanding of warehouse robotics use case; clear product concept (DodoLib as modular world-model foundry) | • Early design partners willing to trial world-model-based policies on real hardware; lighthouse customers for case studies | • Target mid-size warehouse robotics cos (Ocado Tech, Locus Robotics, GreyOrange); offer free pilots in exchange for feedback and data; leverage Conception-X alumni intros |
| Co-Founder | • @Karthik — strong ML/RL research skills | ||
| • Frank — 3DGS, world models, prior industry data engineering experience | |||
| • Deep technical credibility and academic network | • A commercially-minded co-founder with experience in B2B sales, partnerships, or business development in robotics/deep-tech | ||
| • Someone who can own fundraising, customer discovery, and GTM strategy | |||
| • Ideally has operator experience at a robotics or logistics startup | |||
| • Bonus: network into warehouse/3PL decision-makers | • Tap Entrepreneur First and Conception-X alumni network for business-side founders | ||
| • Attend deep-tech founder matching events (Antler, EF, Zinc) | |||
| • Post a co-founder search on Y Combinator Co-Founder Matching | |||
| • Ask Conception-X mentors for warm intros to commercially-minded operators in robotics | |||
| • Network at logistics/supply-chain conferences (Manifest, LogiMAT) | |||
| Funding | • Conception-X network and programme support; PhD stipend covering personal runway | • Pre-seed investors who understand deep tech / robotics AI; | |
| • Orrick | |||
| • Grant funding (Innovate UK, ARIA, EPSRC IAA); angel investors with robotics domain expertise | • Apply to Innovate UK Smart Grants; pitch at Conception-X demo day; build relationships with deep-tech VCs (Amadeus Capital, Kindred Capital, Lux Capital); | ||
| • Explore UKRI commercialisation grants | |||
| Hiring | • Access to Surrey CVSSP talent pool; | ||
| • Connections with MSc/PhD students in vision and RL | |||
| • Old connections in the Silicon Valley | |||
| • Connections to good engineers (Karthik’s friends) | • A robotics/sim engineer who can bridge world models → real hardware | ||
| • A product/business co-founder to handle GTM | • Post roles in CVSSP and Conception-X channels | ||
| • Attend university robotics hackathons | |||
| • Tap Entrepreneur First and other talent-dense programmes | |||
| Partners | • Academic collaborators at CVSSP | ||
| • Conception-X mentors and programme partners | |||
| • Robot hardware OEMs (for integration/testing) | |||
| • Simulation platform partners (e.g. NVIDIA Isaac, MuJoCo ecosystem) | |||
| • Cloud compute partners for training at scale | • Reach out to NVIDIA Inception programme | ||
| • Propose joint research with robot OEMs; explore AWS/GCP startup credits programmes | |||
| Diffusing | • Strong technical writing skills; academic publication pipeline; existing Notion-based knowledge base | • Broader visibility in the robotics startup ecosystem | |
| • Developer community around DodoLib | |||
| • Media/content that reaches non-academic audiences | • Publish technical blog posts and open-source demos | ||
| • Present at meetups (London Robotics, ROS meetups) | |||
| • Build a Twitter/X presence in the robotics ML community; submit to arXiv and promote on social |
Think of it like a favour bank — you store up reciprocation and fund future opportunities.