boldstart in 2017, enterprise tech in 2018

2017 Recap

2017 was another year of growing, learning, investing and partnering with amazing founders. Once again, we are grateful to have the opportunity to work with so many amazing founders, advisors, co-investors, and other collaborators to bring the boldstart family together.

Before diving into yet another year and list of predictions for enterprise in 2018, we’d like to recap a few thoughts and moments from 2017.

  1. We were first check leads in 8 founding teams including Wallaroo Labs, MState (fka hyperfab), blockdaemon, and 5 in stealth.
  2. Thematically our new investments include 4 targeting the “Rise of the Developer,” 3 in “Intelligent Automation,” and 1 in “Decentralized Computing;” geographically 4 are in NYC, 3 in Bay Area, and 1 in LA (more on our themes)
  3. 6 portfolio companies raised Series A financings including ManifoldHypr, and 4 unannounced, 1 raised a Series B (unannounced), and Security Scorecard raised a $28mm Series C.
  4. 2 exits including yhat (sold to Alteryx — AYX NYSE) and, one an early investment in a data science platform and the other on NLP for developers.
  5. We co-founded MState (fka hyperfab, read Coindesk article) with Rob Bailey to help bring enterprise company building expertise and Fortune 500 connections to the blockchain community. Our partners include IBM and one unannounced Fortune 50.
  6. We built out our CXO advisory board and further cemented our Fortune 500 relationships to help our portfolio cos scale from “founder-market” fit to product market fit in an accelerated timeframe (meet our advisors). This resulted in tons of collaboration with large enterprises ranging from product feedback to pilots and customer relationships.

Enterprise Tech in 2018:

“The Law of Accelerating Returns” by Ray Kurzweil is truer than ever before: the rate of change in a wide variety of evolutionary systems (including but not limited to the growth of technologies) tends to increase exponentially.


In other words, today is the slowest rate of technological change you will ever experience in your life and doing nothing is worse than doing something. Keep this in the back of your mind as you think about the biggest transformation in enterprise tech; the re-platforming of corporate America from legacy to cloud/hybrid cloud and monolithic software apps to microservices driven development. With this pace of change accelerating, everyone will have to move earlier in the food chain; corporates will need to work with earlier stage startups (we are experiencing that phenomenon in our portfolio) and VCs will have to go earlier to invest in those founders before they take off.

  1. NYC has deep enterprise tech: the NYC you imagine that is full of ad tech and media is not the NYC that we see. Some of our latest investments in NYC include founders building companies in serverless, open source data streaming, decentralized biometric security, splunk for customer data, and developer productivity for dynamic code testing. There will be more deep enterprise tech startups founded, funded, launched, and scaled out of NYC in 2018. The talent base is improving, the customers are here, and the west coast VCs are paying attention. A sidebar is that NYC is and will continue to be one of the best places to launch any crypto-related company with Consensys as a base, the large number of fin tech entrepreneurs in NYC, and also with IBM in close proximity, one of the leaders in the enterprise blockchain. That is why we are also so excited about Mstate.
  2. Continued barbelling of VC will continue in 2018:. Either we see lots of smaller or seed funds at one end of the barbell or mega funds on the other end. It’s increasingly becoming tough to be caught in the middle to maintain ownership in your winners, and we will see more established VCs like Sequoia raise mega funds to counter the Softbank Vision effect. As for us, we are continuing to double down on our old school VC model, first check in, leading or co-leading, and rolling up our sleeves.
  3. CIOs are the new VCs: this is the year that Chief Information Officers start acting more like VCs. Corporate America is pressured to decrease costs and improve customer interactions and every Fortune 500 is a technology company. Expect this trend to continue and what this means is that CIOs will take a portfolio approach, make some bets, and double down on their winners. There will be lots of room for startups to wedge their way into large corporates and they will have every opportunity to turn pilots into production. This speed of adoption of new tech will accelerate at the largest enterprises, and they will be reliant on early stage startups to do so.
  4. Rise of the developer in the Fortune 1000: According to Gartner 75% of app development supporting digital business will be built, not bought. There are more devs, more corporates who need more dev tools and services, and we are seeing continued adoption in the largest companies. Tied to this will be a need for a hybrid, cloud/on-prem deployment and we are excited about portfolio companies like replicated that play to this future.
  5. GDPR is the next Y2K: GDPR kicks off in May 2018, and we are convinced it is going to be a massive problem and will sneak up on many enterprises.GDPR is all encompassing and focuses on protecting a customer’s PII (personally identifiable information) and hits every segment of the data pipeline from how developers access data as they create new apps to finding and monitoring all of a company’s PII to eventually allowing end users the right to be forgotten. This will be a huge boon in data and security spend in 2018 directly tied to this.
  6. Enterprise blockchain will prove itself: Cryptocurrencies are hot but the tech powering this, blockchain gets less attention. 2018 will be the year that many Fortune 500s that are piloting this tech will bring applications into production. There’s been lots of buzz for the need for a shared, distributed ledger but 2018 is the year we see production level use cases in the wild.
  7. Rise of Chief Data Officers: As the value of an organization’s data continues to rise, we will see many more Fortune 500s create the Chief Data Officer position. This is a trend that kicked off over the last 2 years and will only accelerate in 2018. This role is crucial as companies look to consolidate to a data lake (cloud or hybrid cloud) to prep for a future driven by AI and machine learning. Investment opportunities will abound as data ops becomes the new dev ops and the need for pipelining software to go from raw data to prepped data increases. This Chief Data Officer will also be responsible to manage the impact of GDPR (see above).
  8. AI is not a market, AI is embedded in every application: AI is not a market, it’s an enabling technology just like Java, wireless, and blockchain are. We said this in our predictions last year for 2017 (AI is table stakes) and this will accelerate in 2018. Some call this “ambient AI” and I just call it software. The real enterprise use cases that will continue to scale is the automation of the back office and the move away from robotic process automation (RPA) to Intelligent Automation (cognitive layer) and the continued move from AI in the back office and moving to the front office in every industry.
  9. Move to cloud accelerates, serverless hits early majority: We are still at the tip of the iceberg as enterprises move from legacy to cloud or hyrbrid/cloud. AWS has dominant market share but multi-cloud becomes a must-have for most Fortune 1000 organizations. This includes choosing best of breed by cloud vendor (Google for tensorflow, AWS for s3 and serverless, etc) and also distributing workloads over multiple clouds. With this, serverless and event-driven workloads will continue to proliferate as companies move beyond AWS Lambda and start using Google Cloud Functions and other solutions.
  10. Dev Sec Ops is the hot topic in security: With the velocity of software development and the reuse of software components, building in security at developer level becomes a must have. Securing open source dependencies like our portfolio co Snyk, managing service to service authentication and policy, encrypting traffic and more become hot areas in 2018.
  11. Quantum dabbling: We will hear about more and more enterprises explore the use of quantum. In 2017, new languages were created from companies like Microsoft and IBM to take classical algorithms and help repurpose for quantum, and this will accelerate in 2018 as the Fortune 500s start building out skunkworks teams to explore use cases. We are still a few years away from having a quantum computer perform calculations faster than a classical machine but once that happens, there will be tremendous opportunity for startup activity.

Previously posted on Medium

Blurring lines in enterprise SaaS; the race to own customer data

I’ve written before about the competitive nature of SaaS and the amount of entrants in every category.

Lately after every conversation, I feel like the world is being divided into two camps and there is a massive battle going on in terms of who is going to own them and how. To oversimplify, I’ll call it pre-customer and post-customer domination. And there are companies looking to blur both of those categories as well.

It’s pretty hard to create a new system of record these days as Salesforce, Marketo, Gainsight and the like are building tighter lock-in around their products. That’s not to say it can’t be done as those companies have larger fish to fry, mainly huge enterprise customers and $1mm + deals. Opportunities abound in the SME (small, medium enterprise), and we’ve seeded a number of founders going after that space.

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Thoughts from Mulesoft and AppDynamics IPO Filings

I finally had a chance to take a quick read of the respective S1 filings for AppDynamics and Mulesoft. While the growth for each company is quite amazing, two thoughts jumped out at me.

As we move to a cloud-only world with instant-on capabilities and low friction in onboarding customers, why does professional services revenue keep increasing year over year for these enterprise cloud businesses. Secondly, as the world continues to move to the cloud, why does on-prem software exist any more?

Looking at both S1 filings, it’s clear that AppDynamics and Mulesoft have caught on to what Salesforce already knows – if you want to be a massive business you also need to sell professional services. As these tech companies get larger and larger, their target customer also increases in size as these vendors look to move from 6 to 7 figure deals. In order to support continued ARR growth upstream, some of the best companies successfully use professional services as a weapon and make implementation, support and training part of the sale. See Jeff Leventhal’s post (boldstart venture partner and Workrails cofounder/CEO) on why services continue to matter for cloud vendors.

Same goes for why on-prem. In both S1s, we can see Mulesoft and AppDynamics discussing the need for multiple delivery models as many larger customers have regulatory and compliance needs, esp. in banking, insurance, and health care. On-premise and hybrid cloud deployments are not going away despite the continued adoption of the cloud. There is a whole world of what being enterprise ready from a product perspective looks like, and how SaaS companies can use new technology like Docker to have the best of both worlds, SaaS and on-prem without multiple code bases. If interested, take a look at curated by Replicated (full disclosure: boldstart is an investor).

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Building AI on CXOTalk cutting through AI hype, "applied AI" to enterprise

I had a great time participating on CXOTalk by Michael Krigsman with boldstart portfolio co founders, Sean Chou from Catalytic and Keith Brisson from

When you get down to it, AI is going to be huge in the enterprise but you need to make sure to focus on solving real business problems. Watch to learn more on our discussion about “applied AI.”

Here are some nuggets of wisdom:

Companies are removing #data silos. This will enhance usage of applied #AI

@keithbrisson @edsim  on #CxOTalk

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Enterprise Collaboration Wars Lessons for SaaS startups

It’s going to be fun to watch the enterprise collaboration wars and how each company is approaching the market! In my mind it is a microcosm of many battles being played out with startups versus incumbents. Do large enterprises go for “best of breed” providers or the “one throat to choke” model? How does the bottom-up model work versus the traditional top-down enterprise sales model? As for collaboration, here is a view of some of the players:

  1. Slack – bottom up, adding enterprise features, but not on-prem yet, many early adopter enterprises but can they bridge gap to more traditional
  2. Microsoft – Teams, product not as fleshed out but starting with bases of thousands of enterprise clients due to enterprise company licenses, does that mean adoption?
  3. Box/Dropbox – coming at it from a technically commodity base layer of file sharing and storage, trying to add stickiness on top with Paper by Dropbox and Notes from Box
  4. Google – has Gsuite for Google Cloud – do they add a collaboration layer or do they just buy someone else?
  5. Salesforce – has Quip, do they keep adding layers on top?

and many others…

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Developer love vs revenue Going from Seed to Series A

Great blog post by CockroachDB on open source business models and their plans to make money:

If you’re serious about building a company around open source software, you must walk a narrow path: introduce paid features too soon, and risk curtailing adoption. Introduce paid features too late, and risk encouraging economic free riders. Stray too far in either direction, and your efforts will ultimately continue only as unpaid open source contributions.

I would say same goes for any developer-focused company whether OSS or some other hybrid free/premium model. It is truly an art form when it comes to striking that steady balance between developer and community love versus generating revenue and potentially alienating those who supported you.

This is also an important question as it relates to fundraising for dev-focused startups. Introduce your pricing page too soon and that is the metric that Series A investors will track religiously. Bet the farm on developer love and metrics only and you may never get enough traction to get to that next round.

From what I have seen in our portfolio, goal #1 is always to build an amazing community, focus on developer love and track the metrics and tweak. Without the developers, you have no customers.

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Thoughts on SaaS in 2017

When we started boldstart in 2010, a core thesis of ours was to invest in next-gen SaaS which we called SaaS 2.0 at the time and best highlighted in our end of 2015 review:

SaaS 2.0, reinventing for the mobile first workforce will continue to remain robust. We also see older school SaaS companies being rebuilt with more flexible back-end technologies like microservices and reimagined with a more responsive and beautiful UI.

While we continue to be excited about opportunities in SaaS startups, it is clear that the game has changed substantially since 2010. Despite the amazing productivity gains from open source, AWS, microservices and other new technologies, we have seen the time to launch extending and the cost of getting a minimally viable product (MVP) out the door increasing. So why is this the case?

  1. Most SaaS categories have multiple players and to build a transformative SaaS app means the bar to what a “minimally viable product” is much higher than it was 5 years ago. In other words, a MVP of 5–6 core features may now need 8–10 core. This takes more time, money, and resources. Founders need to make tough decisions on what their definition of feature parity is and what that one unique product angle will be to rise above the noise (more to come in a follow up post).
  2. The competition for talent has and continues to be fierce so as tech costs go down, human capital costs continue to increase.
  3. Cost of getting message to market has increased due to the noise from the many competitors in a particular space.

So what can a founder and investor do in this changing world?

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boldstart in 2016, enterprise tech in 2017 year in review, outlook for enterprise tech in 2017

2016 was a banner year for boldstart, and we could not have achieved any of this without the amazing support of our boldstart family and the founders who have given us the opportunity to invest in and partner with them.

Before diving into the standard year-end predictions on the enterprise, I thought I would share some data on our firm and our founding teams from 2016:

  1. we welcomed 9 new enterprise founding teams to the portfolio including Workrails (started by venture partner Jeff Leventhal), BigID, Hypr,, and 5 stealth companies
  2. Thematically our new investments include 5 infrastructure/dev platforms, 3 security, and 2 SaaS; 4 are using some form of AI or machine learning; geographically 4 are in NYC, 3 Bay Area, 1 Canada, 1 Chicago
  3. 8 of our portfolio companies raised follow on Series A rounds with > $70mm raised and an average size of almost $9mm — announced rounds include Kustomer, Robin, Emissary, Replicated and Front — geographically 2 in NYC, 3 Bay Area, 1 Canada, 1 LA, 1 Chicago
  4. 4 of our portfolio companies raised Series B financings with close to $70mm raised and an average financing size greater than $17mm — announced rounds include security scorecard, handshake, and wevr — geographically 2 in NYC, 1 LA, 1 Canada
  5. fund iii had an oversubscribed closing of $47mm

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our journey to an oversubscribed fund iii for first check enterprise boldstart closes $47mm fund iii for first check, enterprise founders


This is a story about starting an enterprise seed fund called Boldstart in 2010 and our journey in enterprise since 1996. Despite our firm being a little over 6 years old, our individual stories go further back. We each independently fell in love with enterprise software 20+ years ago as seed investors (cos like gotomeeting/Citrix, greenplum/EMC, livperson/IPO LPSN) and founders (workmarket, onforce/Adecco, spinback/buddymedia/salesf0rce) and are now benefiting from the ecosystems, knowledge and network that we’ve collectively developed.

What seemed like a big bet in early 2010 was only us pursuing our passion. Our goal was to be the best first check partner for enterprise founders, bringing the value add of a VC firm while moving with the speed and conviction of an angel investor. We set out to build boldstart at the height of mobile app mania and viral growth and were faced with questions about our focus on enterprise and NYC. At the time there were only a handful of micro-VCs in existence, and despite going against the tide, we felt that the opportunity to build the first and best enterprise seed fund was a dream worth pursuing.

Today, we are super excited to announce our final close of $47mm for fund iii. This was oversubscribed from our initial target of $30mm

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The 4 Kinds of Series A Rounds in Enterprise roadmap for understanding how to go from seed to Series A

A wise VC once told me when dinner is served, you eat. When it comes to fundraising, I’ve learned that if someone is trying to invest now, you should strike while the iron is hot. Given that the headwinds are getting stronger, we at boldstart have been advising all of our portfolio companies to raise as much as they can as soon as they can and to make sure that every dollar spent has a real ROI.

Related to this, the question I am often asked is “what metrics do I need to hit” to get that next round. While super important, I always like to understand where the business is in its lifecycle before answering. Having spent the last week in several meetings with startups going from seed to A, I thought I would break down the various types of A rounds and the major ??? to success:

The 4 kinds of A rounds:

  1. No A round. Sucks. — self explanatory
  2. Vision A round, super hard — raise on the promise and pre-launch, on the vision, huge market with the killer team that can build and scale. sometimes easier to raise on the promise and the expectations of amazing success than after the launch
  3. Metrics A round, easier — killer metrics, repeatable growth and predictable sales model, used to be $80–$100k MRR/$1mm ARR, the bar is raising…
  4. Hybrid A, toughest — this is where you are between 2 and 3 and the hardest to get done.

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