CVPR2010: Learnings from founding a computer vision startup: Chapter 5: Funding: who and how to ask for money
Funding alternatives Angel vs VC Pitching investors How much?Flickr: mmoorr
Learnings from founding a Computer Vision Startuphttp://en.wikipedia.org/wiki/Seed_money
Learnings from founding a Computer Vision Startup FFF (friends, family & fools) A small investment can take a small fresh team far E.g. early stage Web product <$10k/year for computing and tools Bootstrapping: Consulting work on the side (that hopefully also builds your product) Hire young, cheap, and hungry Minimum viable product (don’t build more than an absolute minimum)
Learnings from founding a Computer Vision Startup Sanity check! Do you really need to raise external funding? can you bootstrap of own investment, consultancy work, part time... What is the money for? after “how much?”, this is the next question investors will ask
Learnings from founding a Computer Vision Startup Grants & Research Funding Soft loans Regional & National grants EU research funding (FP7 etc) Beware of business plan competitions! “No one wins in business plan competitions“ -Steve Blank Flickr:denniswong
Learnings from founding a Computer Vision Startup Angels What is a business angel? someone with experience, energy and cash invests own money typical range 25-50k Angel networks groups of angels that co-invest needed since each angel has limited funds/investment makes passive investments possible Flickr: onkel_wart
Learnings from founding a Computer Vision Startup Venture Capital Fixed life funds (~8-10 years) Money comes from institutional investors pensions, universities, foundations, individuals Types regional vs. (inter)national, early vs. late, branch speciﬁc Flickr: markcoggins
Learnings from founding a Computer Vision StartupFlickr: courtneybolton How VCs work
Learnings from founding a Computer Vision Startup Organization partners & associates End-goal is an EXIT Trade sale IPO The VC business model (2/20) Expectations management fees - partners get ~2% of invested capital carried interest - partners’ management company get ~20% of proﬁts some form of control most investments fail the few that succeed should give high multiples >>> High risk is a part if the game but risk level depends on timing, spread of portfolio and ﬁnancial climate. Flickr: sophistechate
Learnings from founding a Computer Vision Startup Pitching investors Checklist: Storytelling + elevator pitch + slide deck (doubles as presentation and business plan) Problem & solution + exec summary (optional, very short!) (technology is secondary) - forget about NDAs - detailed plan comes later Show a market Flickr: akrobat77
Learnings from founding a Computer Vision Startup Pitching tips Pitching angels Pitching VCs chemistry: it’s about relationship and trust prepare: look at their portfolio & proﬁles often a group is needed (don’t worry, they ﬁnd a “champion” on the inside bring in “friends”) partners decide together - convince them all! if decisions don’t come quickly, it is a “no”, - pitch at partner meeting will be short, be move on. ﬂexible Be careful with revenue projections! (skip unless really good data exists) If you send material or a deck, make it .pdf with recipients name and date. If multiple investors, work the “lead” investor into agreement, then offer others same terms.
Learnings from founding a Computer Vision Startup David S. Rose on pitching to VCs http://www.ted.com/talks/david_s_rose_on_pitching_to_vcs.html
Learnings from founding a Computer Vision Startup Angels or VC? if possible: look for integrity, Angels VC “you can’t ﬁre your investors” less money more money quick exit vs. big exit for fun professionally quick slow beware that VC irreversibly sets company on path to EXIT no control lots of control seek investors who agree with your deﬁnition of success
Learnings from founding a Computer Vision Startup Negotiation Know your BATNA* “to get good terms you need multiple offers, to get multiple offers you need to tell a good story to several investors at the same time” There is no formula for valuation, it is decided on comfort levels. Actual terms are more important than valuation and dilution. * Best Alternative To a Negotiated Agreement
Learnings from founding a Computer Vision Startup How much to raise? “It depends”, 3 different views: 1) As little as possible 2) As much as you can (against reasonable equity, of course) 3) Whatever you can get and get on with building stuff 1) Sound in principle but risks spending time in “constant fundraising mode” which takes lots of energy from building stuff 2) “you are always going to need more than you think” 3) Fundraising is a distraction, time spent is distraction and reduces velocity Tip: If possible raise all at once, avoid tranche investments
What is special about Vision? In terms of raising capital
Learnings from founding a Computer Vision Startup What’s special about Vision? Research grants can be a serious option Visual demos can help pitching Currently lots of traction in consumer markets (people and businesses asking for vision) but few strong success (exit) cases. Vision is technology heavy - you will encounter the “here’s the solution where’s the problem” comments
Learnings from founding a Computer Vision Startup Polar Rose: How we did it Grants, Friends & Seed $300k over 2004-2006 Series A $5.4M in July 2006 from Nordic Venture Partners -> smaller follow up in 2009-2010 from Nordic Venture Partners
Learnings from founding a Computer Vision Startup Kooaba: How we did it Grants, work besides PhD ~ CHF 100k over 2006-2007 Loans seed round (bank + FFF) & Grants ~ CHF 700k seed (convertible loans), CHF 300k Grants (2008) Pre series A round & Grants ~ CHF 1.5 Million total (2009) Series A now
Learnings from founding a Computer Vision Startup Resources Twitter: @venturehacks (Startup advice on VC and entrepreneurship) @msuster (Mark Suster, entrepreneur gone VC, also at http://bothsid.es) @fdestin (Fred Destin, VC at Atlas Ventures) Seed funding: Ycombinator (North America) http://ycombinator.com/ Seedcamp (Europe) http://www.seedcamp.com/ Angels: http://venturehacks.com/angellist (list of angels on Twitter) Bootstrapping: http://blog.guykawasaki.com/2006/01/the_art_of_boot.html (Guy Kawasaki on bootstrapping)
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